Table of Contents

• Overview of BioASQ Tasks 13b and Synergy13 in CLEF2025Anastasios Nentidis, Georgios Katsimpras, Anastasia Krithara, Georgios Paliouras. 1-18 [doi]
• Overview of MultiClinSum Task at BioASQ 2025: Evaluation of Clinical Case Summarization Strategies for Multiple Languages: Data, Evaluation, Resources and ResultsMiguel Rodríguez-Ortega, Eduard Rodriguez-López, Salvador Lima-López, Carlos Escolano, Audrey Mash, Maite Melero, Lorenzo Pratesi, Laura Vigil-Gimenez, Leticia Fernandez-Lopez, Eulàlia Farré-Maduell, Martin Krallinger. 19-40 [doi]
• Overview of the BioASQ BioNNE-L Task on Biomedical Nested Entity Linking in CLEF 2025Andrey Sakhovskiy, Natalia V. Loukachevitch, Elena Tutubalina. 41-50 [doi]
• Overview of ElCardioCC Task on Clinical Coding in Cardiology at BioASQ 2025Dimitris Dimitriadis, Vasiliki Patsiou, Eleonora Stoikopoulou, Achilleas Toumpas, Alkis Kipouros, Alexandra Bekiaridou, Konstantinos Barmpagiannos, Anthi Vasilopoulou, Antonios Barmpagiannos, Athanasios Samaras, Dimitrios Papadopoulos, George Giannakoulas, Grigorios Tsoumakas. 51-64 [doi]
• Overview of GutBrainIE@CLEF 2025: Gut-Brain Interplay Information ExtractionMarco Martinelli 0003, Gianmaria Silvello, Vanessa Bonato, Giorgio Maria Di Nunzio, Nicola Ferro 0001, Ornella Irrera, Stefano Marchesin 0001, Laura Menotti, Federica Vezzani. 65-98 [doi]
• Trusting Gut Instincts: Transformer-Based Extraction of Structured Data from Gut-Brain Axis PublicationsLasse Ryge Andersen, Mikkel Hagerup Dolmer, Marius Ihlen Gardshodn, Juan Manuel Rodriguez, Daniele Dell'Aglio. 99-119 [doi]
• AQAMS and AQAMS2: Multi Agent Systems for Biomedical Question AnsweringJohanna Angulo, Víctor Yeste. 120-135 [doi]
• Agentic MCS: A Multilingual Clinical Summarization FrameworkJohanna Angulo, Víctor Yeste. 136-147 [doi]
• Can Language Models Critique Themselves? Investigating Self-Feedback for Retrieval Augmented Generation at BioASQ 2025Samy Ateia, Udo Kruschwitz. 148-164 [doi]
• UniTor at BioASQ 2025: Modular Biomedical QA with Synthetic Snippets and Multiple Task Answer GenerationFederico Borazio, Andriy Shcherbakov, Danilo Croce, Roberto Basili 0001. 165-197 [doi]
• Navigating Partial UMLS Terminology: GAT Embeddings and Confidence Analysis for Multilingual Concept LinkingAlbina Burlova. 198-205 [doi]
• NCU-IISR: Biomedical Question Answering via Gemini and GPT APIs in the BioASQ 13b Phase B ChallengeBing-Chen Chih, Jen-Chieh Han, Hsi-Chuan Hung, Richard Tzong-Han Tsai. 206-213 [doi]
• lasigeBioTM at BioASQ25 Task GutBrainIE - Lean Large Language Models with Syntactic FeaturesSofia I R. Conceição, Paulo R. C. Lopes, Francisco M. Couto. 214-225 [doi]
• Graphwise @ CLEF-2025 GutBrainIE: Towards Automated Discovery of Gut-Brain Interactions - Deep Learning for NER and Relation Extraction from PubMed AbstractsAleksis Datseris, Mario Kuzmanov, Ivelina Nikolova-Koleva, Dimitar Taskov, Svetla Boytcheva. 226-242 [doi]
• SINAI at BioASQ@CLEF 2025: A Multi-Stage RAG Pipeline for Biomedical Semantic Question AnsweringSara Dueñas-Romero, Luis Alfonso Ureña López, Eugenio Martínez-Cámara. 243-265 [doi]
• LLM Ensemble for RAG: Role of Context Length in Zero-Shot Question Answering for BioASQ ChallengeDima Galat, Diego Mollá Aliod. 266-272 [doi]
• Group Relative Policy Optimization for Spanish Clinical Case Report SummarizationGeorgi Grazhdanski. 273-280 [doi]
• SCIRE at BioASQ 2025: LLM Driven Biomedical Named Entity Recognition for GutBrainIE 2025Harsh Prakash Gupta, Ritwik Banerjee. 281-291 [doi]
• NCU-IISR: A Retrieval-Augmented Generation Approach for BioASQ 13b Phase A and A+Jen-Chieh Han, Bing-Chen Chih, Hsi-Chuan Hung, Richard Tzong-Han Tsai. 292-301 [doi]
• GutUZH at CLEF2025 BioASQ Task 6: a Method of SOTA Performance with the Best Results at GutBrainIE NER Subtask 1Jinyi Han, Yeyang Liu. 302-316 [doi]
• Clinical Entity Recognition and Linking in Greek Discharge Letters using Multilingual-LLM-Based Multi-Stage SystemBor-Woei Huang. 317-327 [doi]
• BIT.UA at BioASQ 13B: Revisiting Evaluation, DPRF-Enhanced Retrieval and Fine-Tuned LLMsRichard A. A. Jonker, Tiago Melo Almeida, João Rafael Almeida, Sérgio Matos. 328-342 [doi]
• Constrained Linked Entity ANnotation using RAG (CLEANR)Benedikt Kantz, Stefan Lengauer, Peter Waldert, Tobias Schreck. 343-358 [doi]
• From Named Entities to Relations: End-to-End Biomedical Information ExtractionRon Keinan, Amir David Nissan Cohen, Reut Tsarfaty. 359-372 [doi]
• Prompting Matters: Snippet-Aware Strategies for Biomedical QA with LLMs in BioASQ 13bHajung Kim, Hoonick Lee, Yewon Cho, Jungwoo Park, Jueon Park, Soyon Park, Yan Ting Chok, Seungheun Baek, Donghyeon Lee, Jaewoo Kang. 373-382 [doi]
• Multilingual and Nested Biomedical Named Entity Normalization via Candidate Retrieval and Lightweight Large Language Model DisambiguationAntoine D. Lain, Chaeeun Lee, Simona E. Doneva, Maria Juliana Rodriguez-Cubillos, Elisa Castagnari, T. Ian Simpson, Joram M. Posma. 383-392 [doi]
• Understanding Gut-Brain Interplay in Scientific Literature: A Hybrid Approach from Classification to Generative LLM ReasoningChaeeun Lee, Simona E. Doneva, Maria Juliana Rodriguez-Cubillos, Elisa Castagnari, Antoine D. Lain, Joram M. Posma, T. Ian Simpson. 393-410 [doi]
• BIBERT-Pipe on Biomedical Nested Named Entity Linking at BioASQ 2025Chunyu Li, Xindi Zheng, Siqi Liu. 411-419 [doi]
• LYX_DMIIP_FDU At BioASQ 2025: Utilizing BERT Embeddings For Biomedical Text MiningYuxuan Liu, Shanfeng Zhu. 420-432 [doi]
• lasigeBioTM: A Lean Biomedical QA System Empowered by Structured KnowledgePaulo R. C. Lopes, Sofia I. R. Conceição, Maria Fernandes, Francisco M. Couto. 433-451 [doi]
• Development of a Biomedical Question Answering System Based on Transformer ModelsLila López, Juan Carlos Martínez Santos, Edwin Puertas. 452-459 [doi]
• Enhancing Biomedical Named Entity Recognition using GLiNER-BioMed with Targeted Dictionary-Based Post-processing for BioASQ 2025 task 6Ritesh Mehta. 460-472 [doi]
• Comparing CRF vs BERT Models for Named Entity Recognition and Relation ExtractionLorenzo Pamio, Giorgio Maria Di Nunzio. 473-482 [doi]
• Harnessing Collective Intelligence of LLMs for Robust Biomedical QA: A Multi-Model ApproachDimitra N. Panou, Alexandros C. Dimopoulos, Manolis Koubarakis, Martin Reczko. 483-496 [doi]
• Hybrid Re-ranking for Biomedical Entity Linking using SapBERT Embeddings: A High-Performance System for BioNNE-L 2025-1Daniel Peña Gnecco, Jairo Serrano, Edwin Puertas, Juan Carlos Martínez Santos. 497-508 [doi]
• Named Entity Recognition with GLiNER and Relation Extraction with LLMsSamuel Piron, Giorgio Maria Di Nunzio. 509-519 [doi]
• MaLei at MultiClinSUM: Summarisation of Clinical Documents using Perspective-Aware Iterative Self-Prompting with LLMsLibo Ren, Yee Man Ng, Lifeng Han. 520-533 [doi]
• ExtraSum @ MultiClinSum: Extractive Summarization of English, Spanish, French and Portuguese Clinical Case ReportsSoukaina Rhazzafe, Simon Colreavy-Donnelly, Nikola S. Nikolov. 534-543 [doi]
• Using Decoder-Based Distillation for Enhancing Multilingual Clinical Case Report SummarizationNicolay Rusnachenko, Xiaoxiao Liu, Jian Chang, Jian-Jun Zhang. 544-553 [doi]
• Enhancing Multilingual Medical Summarization via Contextual Keyword AugmentationMd. Shahidul Salim, Lianne Fu, Arav Adikesh Ramakrishnan, Sunjae Kwon, Zonghai Yao, Hong Yu 0001. 554-568 [doi]
• Biomedical Semantic Question Answering - Answering Systems Using Different LLMs for SubtasksSamitinjaya, Dipankar Das 0001. 569-581 [doi]
• MedGemma-Sum-Pt: A Lightweight Model for Portuguese Clinical SummarizationElisa Terumi Rubel Schneider, Fernando Henrique Schneider, Emerson Cabrera Paraiso, Alceu de Souza Britto Jr., Rafael Menelau Oliveira Cruz. 582-594 [doi]
• Are Smaller Open-Weight LLMs Closing the Gap to Proprietary Models for Biomedical Question Answering?Damian Stachura, Joanna Konieczna, Artur Nowak. 595-604 [doi]
• Applying DeepSeek to BioASQ Task 13B: Using Supervised Fine-Tuning and Few-Shot LearningJie Tang 0001, Hua Yang, Kai Xiong, Hanyang Li, Paulo Quaresma, Hongbin Yu, Wenbo Zhang, Mingzhou Song. 605-616 [doi]
• NLP@VCU at BioASQ2025: Information Extraction on the GutBrainIE datasetScott Taylor, Charlie Dil, Aaron Shah, Jannat, Cyd Oldham, Ayush Upadhyay, Joanne Varughese, Nicole Yazbeck, Bridget T. McInnes. 617-625 [doi]
• Exploring Retrieval-Reranking and LLM-Based Answer Generation for Biomedical QAPoojan Vachharajani. 626-634 [doi]
• Multilingual Embedding and Prompt-Driven Approaches for Named Entity Recognition, Entity Linking, and Clinical Code Prediction in Greek Discharge SummariesPoojan Vachharajani. 635-641 [doi]
• pjmathematician at MultiClinSUM 2025: A Novel Automated Prompt Optimization Framework for Multilingual Clinical SummarizationPoojan Vachharajani. 642-650 [doi]
• Enigma @ ELCardioCC: Bridging NER and ICD-10 Entity Linking - A Hybrid Method for Greek Clinical NarrativesBoris Velichkov, Aleksis Datseris, Sylvia Vassileva, Svetla Boytcheva. 651-665 [doi]
• Beyond Retrieval: Ensembling Cross-Encoders and GPT Rerankers with LLMs for Biomedical QAShashank Verma, Fengyi Jiang, Xiangning Xue. 666-680 [doi]
• Overview of the CLEF-2025 CheckThat! Lab Task 1 on Subjectivity in News ArticlesFederico Ruggeri, Arianna Muti, Katerina Korre, Julia Maria Struß, Melanie Siegel, Michael Wiegand, Firoj Alam, Md. Rafiul Biswas, Wajdi Zaghouani, Maria Nawrocka, Bogdan Ivasiuk, Gogu Razvan, Andreiana Mihail. 681-694 [doi]
• Overview of the CLEF-2025 CheckThat! Lab Task 2 on Claim NormalizationMegha Sundriyal, Tanmoy Chakraborty 0002, Preslav Nakov. 695-708 [doi]
• Overview of the CLEF-2025 CheckThat! Lab Task 3 on Fact-Checking Numerical ClaimsVenktesh V, Vinay Setty, Avishek Anand, Boushra Bendou, Maram Hasanain, Houda Bouamor, Gabriel Iturra-Bocaz, Petra Galuscáková, Firoj Alam. 709-721 [doi]
• Overview of the CLEF-2025 CheckThat! Lab Task 4 on Scientific Web DiscourseSalim Hafid, Yavuz Selim Kartal, Sebastian Schellhammer, Katarina Boland, Dimitar Dimitrov 0002, Sandra Bringay, Konstantin Todorov, Stefan Dietze. 722-732 [doi]
• NGU_Research at CheckThat! 2025: An LLM Based Hybrid Fact-Checking Pipeline for Numerical ClaimsMohamed A. Abdallah, Rokayah M. Fekry, Samhaa R. El-Beltagy. 733-742 [doi]
• UCOM_UNAM_PLN at CheckThat! 2025: Evaluating LLMs in a two-Step Architecture for Numerical Fact CheckingGuido Acosta, Eduardo Morales, Helena Gómez-Adorno. 743-753 [doi]
• CSECU-Learners at CheckThat! 2025: Multilingual Transformer-based Approach for Subjectivity Detection in News Articles Across Multilingual and Zero-shot SettingsMonir Ahmad, Abu Nowshed Chy. 754-762 [doi]
• QU-NLP at CheckThat! 2025: Multilingual Subjectivity in News Articles Detection Using Feature-Augmented Transformer Models with Sequential Cross-Lingual Fine-TuningMohammad Al-Smadi. 763-774 [doi]
• NapierNLP at CheckThat! 2025: Detecting Subjectivity with LLMs and Model FusionKatarina Alexander, Md. Zia Ullah, Dimitra Gkatzia. 775-781 [doi]
• Factiverse and IAI at CheckThat! 2025: Adaptive ICL for Claim ExtractionPratuat Amatya, Vinay Setty. 782-794 [doi]
• ClaimIQ at CheckThat! 2025: Comparing Prompted and Fine-Tuned Language Models for Verifying Numerical ClaimsAnirban Saha Anik, Md Fahimul Kabir Chowdhury, Andrew Wyckoff, Sagnik Ray Choudhury. 795-803 [doi]
• dfkinit2b at CheckThat! 2025: Leveraging LLMs and Ensemble of Methods for Multilingual Claim NormalizationTatiana Anikina, Ivan Vykopal, Sebastian Kula, Ravi Kiran Chikkala, Natalia Skachkova, Jing Yang, Veronika Solopova, Vera Schmitt, Simon Ostermann 0002. 804-825 [doi]
• AIRwaves at CheckThat! 2025: Retrieving Scientific Sources for Implicit Claims on Social Media with Dual Encoders and Neural Re-RankingCem Ashbaugh, Leon Baumgärtner, Tim Gress, Nikita Sidorov, Daniel Werner. 826-844 [doi]
• UmuTeam at CheckThat! 2025: Language-Specific versus Multilingual Models for Fact-CheckingTomás Bernal-Beltrán, Ronghao Pan, José Antonio García-Díaz, Rafael Valencia-García. 845-855 [doi]
• ClimateSense at CheckThat! 2025: Combining Fine-tuned Large Language Models and Conventional Machine Learning Models for Subjectivity and Scientific Web Discourse AnalysisGrégoire Burel, Pasquale Lisena, Enrico Daga, Raphaël Troncy, Harith Alani. 856-865 [doi]
• JU_NLP at CheckThat! 2025: A Confidence-guided Transformer-based Approach for Multilingual Subjectivity ClassificationSrijani Debnath, Dipankar Das 0001. 866-875 [doi]
• cepanca_UNAM at CheckThat! 2025: A Language-driven BERT Approach for Detection of Subjectivity in NewsIván Díaz, Jessica Barco, Joana Hernández, Edgar Lee-Romero, Gemma Bel Enguix. 876-884 [doi]
• CornellNLP at CheckThat! 2025: Hybrid LLaMA-GPT-4 Ensembles with Confidence Filtering for Numerical Claim VerificationLea Duesterwald, Adi Arora, Claire Cardie. 885-895 [doi]
• CEA-LIST at CheckThat! 2025: Evaluating LLMs as Detectors of Bias and Opinion in TextAkram Elbouanani, Evan Dufraisse, Aboubacar Tuo, Adrian Popescu 0001. 896-911 [doi]
• AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News ArticlesMatteo Fasulo, Luca Babboni, Luca Tedeschini. 912-925 [doi]
• KSU at CheckThat! 2025: Two-stage approach to fact-checking numerical claimsKeito Fukuoka, Hisashi Miyamori. 926-934 [doi]
• TIFIN at CheckThat! 2025: Cross-Lingual Subjectivity Classification in News through Monolingual, Multilingual, and Zero-Shot LearningKishan Gurumurthy, Ashish Shrivastava, Pawan Kumar Rajpoot, Prasanna Devadiga, Bharatdeep Hazarika, Manish Jain, Manan Sharma, Arya Suneesh, Anshuman B. Suresh, Aditya U. Baliga. 935-952 [doi]
• Investigators at CheckThat! 2025: Using LLMs to Improve Fact-CheckingSyed Muhammad Ather Hashmi, Sidra Aamir, Muhammad Anas, Turab Usmani, Faisal Alvi, Abdul-Samad. 953-963 [doi]
• TIFIN at CheckThat! 2025: X-VERIFY - Multi-lingual NLI-based Fact Checking with Condensed EvidenceBharatdeep Hazarika, Prasanna Devadiga, Pawan Kumar Rajpoot, Aditya U. Baliga, Kishan Gurumurthy, Manish Jain, Manan Sharma, Ashish Shrivastava, Arya Suneesh, Anshuman B. Suresh. 964-976 [doi]
• DS@GT at CheckThat! 2025: Detecting Subjectivity via Transfer-Learning and Corrective Data AugmentationMaximilian Heil, Dionne Bang. 977-987 [doi]
• DS@GT at CheckThat! 2025: Evaluating Context and Tokenization Strategies for Numerical Fact VerificationMaximilian Heil, Aleksandar Pramov. 988-996 [doi]
• Arcturus at CheckThat! 2025: DeBERTa-v3-base for Multilingual Subjectivity Detection in News ArticlesRahul Jambulkar, Aditya Aditya, Sukomal Pal. 997-1008 [doi]
• LIS at CheckThat! 2025: Multi-Stage Open-Source Large Language Models for Fact-Checking Numerical ClaimsQuy Thanh Le, Ismail Badache, Aznam Yacoub, Maâmar El-Amine Hamri. 1009-1023 [doi]
• AKCIT-FN at CheckThat! 2025: Switching Fine-Tuned SLMs and LLM Prompting for Multilingual Claim NormalizationFabrycio Leite Nakano Almada, Kauan Divino Pouso Mariano, Maykon Adriell Dutra, Victor Emanuel da Silva Monteiro, Juliana Resplande Sant'Anna Gomes, Arlindo Rodrigues Galvão Filho, Anderson da Silva Soares. 1024-1038 [doi]
• JU_NLP at CheckThat! 2025: Leveraging Hybrid Embeddings for Multi-Label Classification in Scientific Social Media DiscourseArpan Majumdar, Dipankar Das 0001, Pritam Pal. 1039-1044 [doi]
• Team SeRRa at CheckThat! CLEF 2025: Sequential Re-Ranking in a Scientific Claim Source Retrieval PipelineGuilherme A. Marchetti, Gil Rocha, Henrique Lopes Cardoso. 1045-1055 [doi]
• nlu@utn at CheckThat! 2025: Combining Bias Sensitivity, Linguistic Features, and Persuasion Cues in an Ensemble for Subjectivity DetectionSelina Meyer, Michael Roth. 1056-1070 [doi]
• JU_NLP@M&S at CheckThat! 2025: Automated Claim Extraction and Normalization for Misinformation Detection in Social Media ContentMalobika Mondal, Soumodeep Saha, Dipanjan Saha, Dipankar Das 0001. 1071-1083 [doi]
• DS@GT at CheckThat! 2025: Ensemble Methods for Detection of Scientific Discourse on Social MediaAyush Parikh, Hoang Thanh Thanh Truong, Jeanette Schofield, Maximilian Heil. 1084-1095 [doi]
• DS@GT at CheckThat! 2025: A Simple Retrieval-First, LLM-Backed Framework for Claim NormalizationAleksandar Pramov, Jiangqin Ma, Bina Patel. 1096-1106 [doi]
• SmolLab_SEU at CheckThat! 2025: How Well Do Multilingual Transformers Transfer Across News Domains for Cross-lingual Subjectivity Detection?Md. Abdur Rahman, Md Al-Amin, Md Sabbir Dewan, Md Jahid Hasan, Md Ashiqur Rahman. 1107-1120 [doi]
• Fraunhofer SIT at CheckThat! 2025: Multi-Instance Evidence Pooling for Numerical Claim VerificationAndré Runewicz, Paul Moritz Ranly, Inna Vogel, Martin Steinebach. 1121-1130 [doi]
• MMA at CheckThat! 2025: Multilingual Claim Normalization of Social-Media PostsMariam Saeed, Mazen Yasser, Marwan Torki, Nagwa M. El-Makky. 1131-1140 [doi]
• Deep Retrieval at CheckThat! 2025: Identifying Scientific Papers from Implicit Social Media Mentions via Hybrid Retrieval and Re-RankingPascal Sager, Ashwini Kamaraj, Benjamin F. Grewe, Thilo Stadelmann. 1141-1155 [doi]
• XplaiNLP at CheckThat! 2025: Multilingual Subjectivity Detection with Finetuned Transformers and Prompt-Based Inference with Large Language ModelsAriana Sahitaj, Jiaao Li, Pia Wenzel Neves, Fedor Splitt, Premtim Sahitaj, Charlott Jakob, Veronika Solopova, Vera Schmitt. 1156-1166 [doi]
• TurQUaz at CheckThat! 2025: Debating Large Language Models for Scientific Web Discourse DetectionTarik Saraç, Selin Mergen, Mucahid Kutlu. 1167-1182 [doi]
• OpenFact at CheckThat! 2025: Application of Self-Reflecting and Reasoning LLMs for Fact-Checking Claim NormalizationMarcin Sawinski, Krzysztof Wecel, Ewelina Ksiezniak. 1183-1192 [doi]
• DS@GT at CheckThat! 2025: Exploring Retrieval and Reranking Pipelines for Scientific Claim Source Retrieval on Social Media DiscourseJeanette Schofield, Shuyu Tian, Hoang Thanh Thanh Truong, Maximilian Heil. 1193-1202 [doi]
• Claim2Source at CheckThat! 2025: Zero-Shot Style Transfer for Scientific Claim-Source RetrievalTobias Schreieder, Michael Färber 0001. 1203-1216 [doi]
• TIFIN at CheckThat! 2025: Reasoning-Guided Claim Normalization for Noisy Multilingual Social Media PostsManan Sharma, Arya Suneesh, Manish Jain, Pawan Kumar Rajpoot, Prasanna Devadiga, Bharatdeep Hazarika, Ashish Shrivastava, Kishan Gurumurthy, Anshuman B. Suresh, Aditya U. Baliga. 1217-1227 [doi]
• CUET_KCRL at CheckThat!2025: EnsembleNet with RoBERTa-Large for Subjectivity detection in News ArticlesMd. Tanvir Ahammed Shawon, Fariha Haq, Md. Ayon Mia, Golam Sarwar Md. Mursalin, Muhammad Ibrahim Khan. 1228-1236 [doi]
• VerbaNexAI Lab at CheckThat! 2025: Fine-Tuning DeBERTa for Multi-Label Scientific Discourse Detection in TweetsMervin Jesus Sosa Borrero, Jairo Enrique Serrano Castañeda, Juan Carlos Martínez Santos, Edwin Alexander Puertas Del Castillo. 1237-1245 [doi]
• ATOM at CheckThat! 2025: Retrieve the Implicit - Scientific Evidence RetrievalMoritz Staudinger, Alaa El-Ebshihy, Wojciech Kusa, Florina Piroi, Allan Hanbury. 1246-1255 [doi]
• SCIRE at CheckThat! 2025: Bridging Social Media, Scientific Discourse, and Scientific LiteratureParth Manish Thapliyal, Ritesh Sunil Chavan, Samridh Samridh, Chaoyuan Zuo, Ritwik Banerjee. 1256-1264 [doi]
• SINAI-UGPLN at CheckThat! 2025: Meta-Ensemble Strategies for Numerical Claim Verification in EnglishMariuxi del Carmen Toapanta-Bernabé, Miguel Angel García Cumbreras, Luis Alfonso Ureña López, Denisse Desiree Mora-Intriago, Carla Tatiana Bernal-García. 1265-1275 [doi]
• CheckMates At CheckThat! 2025: Transformer-Based Models For Subjectivity ClassificationKarthik V, R. Padmashri, V. Srikumar, Durairaj Thenmozhi. 1276-1283 [doi]
• Saivineetha at CheckThat! 2025: Exploring Fine-Tuning and Zero-Shot Approaches for Claim NormalizationBaddepudi Venkata Naga Sri Sai Vineetha. 1284-1289 [doi]
• UNH at CheckThat! 2025: Fine-tuning Vs Prompting in Claim ExtractionJoe Wilder, Nikhil Kadapala, Benji Xu, Mohammed Alsaadi, Aiden Parsons, Mitchell Rogers, Palash Agrawal, Adam Hassick, Laura Dietz. 1290-1305 [doi]
• Overview of Robustness and Consistency Task of the ELOQUENT 2025 Lab for Evaluating Generative Language Model QualityJussi Karlgren, Marie Isabel Engels, Maria Barrett, Rohit Raj Gunti, Mohanna Hoveyda, Bruno N. Sotic, Jaap Kamps, Mika Koistinen, Elaine Zosa. 1306-1319 [doi]
• Overview of the Preference Prediction Task at the ELOQUENT 2025 Lab for Evaluating Generative Language Model QualityVladislav Mikhailov, Ekaterina Artemova, Zoia Butenko, Lilja Øvrelid, Erik Velldal. 1320-1329 [doi]
• Overview of the Sensemaking Task at the ELOQUENT 2025 lab: LLMs as Teachers, Students and EvaluatorsPavel Sindelár, Ondrej Bojar. 1330-1359 [doi]
• Prediction of Human Preferences and Explanation Generation with LLM: An Approach Based on RAG, Few-Shot Learning, and Auto-CoTDanileth Almanza-Gonzalez, Jairo E. Serrano, Juan Carlos Martinez Santos, Edwin Puertas. 1360-1369 [doi]
• Predicting Human Preferences using a Multi-head BERT ClassifierFilip F. Andresen, Håkon L. Hyrve, Sander S. Løvaas. 1370-1380 [doi]
• Fake It 'Til You Make It HumanAldan Creo, Maximiliano Hormazábal-Lagos, Héctor Cerezo-Costas, Pedro Alonso Doval. 1381-1390 [doi]
• The Distinctive Data-Centric Approach for the Voight Kampff TaskRohit Raj Gunti. 1391-1400 [doi]
• Evaluating the Performance of the Finetuned Quantized Llama 3 Based on Relevance, Truthfulness, Naturalness, and SafetyRohit Raj Gunti, Abebe Rorissa. 1401-1407 [doi]
• ELOQUENT Sensemaking Task: LLMs in the Evaluator RoleKateryna Lutsai, Matyás Thér, Jonás Venc, Ondrej Bojar. 1408-1413 [doi]
• JUNLP_SS at Eloquent Lab 2025: Humanizing AI - Enhancing the Realism of Machine-Generated TextSoumodeep Saha, Ronit Das, Dipankar Das 0001. 1414-1426 [doi]
• Team LLMinds Submission for ELOQUENT Sensemaking TaskAnna Sajdoková, Matej Macek, Ondrej Hlava, Marek Stefanec, Antonín Kríz, Jakub Kucera, Ondrej Bojar. 1427-1434 [doi]
• University of Amsterdam at the CLEF 2025 Eloquent TrackBruno N. Sotic, Jaap Kamps. 1435-1442 [doi]
• Literal Re-translation as a Method for AI Text Disguise and Detection EvasionPoojan Vachharajani. 1443-1448 [doi]
• Overview of eRisk 2025: Early Risk Prediction on the Internet (Extended Overview)Javier Parapar, Anxo Pérez, Xi Wang 0012, Fabio Crestani. 1449-1473 [doi]
• INESC-ID @ eRisk 2025: Exploring Fine-Tuned, Similarity-Based, and Prompt-Based Approaches to Depression Symptom IdentificationDiogo A. P. Nunes, Eugénio Ribeiro. 1474-1485 [doi]
• THINKIR at eRisk 2025: Early Detection and Risk Assessment of Depression using Transformer ModelsSubinay Adhikary, Junsume Das, Dwaipayan Roy 0001. 1486-1495 [doi]
• LHS712Team-1 at eRisk@ CLEF 2025: Searching for Depression Symptoms Using Various Natural Language Processing AlgorithmsAisha Benloucif, Yashasvini Nannapuraju, Sripriya Bellam, Yuyan Hu, Zhe Zhao, V. G. Vinod Vydiswaran. 1496-1501 [doi]
• HULAT-UC3M at Task1@eRisk 2025: Detecting Depression Using Machine Learning ApproachesJavier Campos-Molina, Paloma Martinez. 1502-1512 [doi]
• ELiRF-UPV at eRisk 2025: New approaches to the Detection and Early Detection of Symptoms and Signs of DepressionAndreu Casamayor, Vicent Ahuir, Antonio Molina, Lluís-Felip Hurtado. 1513-1527 [doi]
• FU-TU-DFKI@eRisk 2025: A Linguistically Informed but Overdiagnosing Approach to Early Depression DetectionElif Kara, Rosa Esther Martín-Peña, Lisa Raithel. 1528-1541 [doi]
• Leveraging Conversational Context and Semantic Relabeling for Early Depression DetectionXabier Larrayoz, Arantza Casillas, Alicia Pérez. 1542-1549 [doi]
• UET@eRisk2025: Severity Estimation for Depression Symptoms Searching and Early Risk DetectionTu-Phuong Mai, Minh-Ha H. Le, Duc-Luong Tran, Duy-Cat Can, Hoang-Quynh Le. 1550-1561 [doi]
• COTECMAR-UTB at eRisk 2025: Semantic-Centroid Symptom Ranking and Early Depression Detection using Adaptive Decision RuleLuis Mendoza, Joan Suarez, Edwin Puertas, Juan Martinez, Jairo Serrano. 1562-1582 [doi]
• SonUIT eRisk2025: Enhanced Depression Detection on Social Media via Filtering and Re-RankingNguyen Minh Son, Dang Van Thin. 1583-1589 [doi]
• DS@GT at eRisk 2025: From Prompts to Predictions, Benchmarking Early Depression Detection with Conversational Agent-Based Assessments and Temporal Attention ModelsAnthony Miyaguchi, David Guecha, Yuwen Chiu, Sidharth Gaur. 1590-1610 [doi]
• Semantic Retrieval of BDI Symptoms in User WritingsNoam Munz, Eliya Naomi Aharon, Avi Segal, Kobi Gal. 1611-1619 [doi]
• SINAI at eRisk@CLEF 2025: Transformer-Based and Conversational Strategies for Depression DetectionAlba María Mármol-Romero, Manuel García Vega, Miguel Ángel García Cumbreras, Arturo Montejo Ráez. 1620-1635 [doi]
• Contextualized Early Detection of Depression - Hybrid and Time-Aware Approaches: HU at eRisk Task 2 2025Muhammad Saad, Asad Ullah Chaudhry, Meesum Abbas, Faisal Alvi, Abdul-Samad. 1636-1645 [doi]
• Transformer Ensembles and LLM-Powered Approaches for Depression Symptom Analysis and Contextualized Early Risk DetectionPoojan Vachharajani. 1646-1662 [doi]
• Detection of Depression with Symptom Similarity: Data Reduction and LLM PersonasAne Varela, Maite Oronoz, Arantza Casillas, Alicia Pérez. 1663-1679 [doi]
• HIT-SCIR@eRisk2025: Exploring the Potential of a Learnable Screening Model and Risk Post Buffer-Based Framework for Contextualized Early Prediction of Depression on Social MediaYuzhe Zi, Bichen Wang, Yanyan Zhao, Bing Qin 0001. 1680-1689 [doi]
• Overview of EXIST 2025: Learning with Disagreement for Sexism Identification and Characterization in Tweets, Memes, and TikTok Videos (Extended Overview)Laura Plaza, Jorge Carrillo-de-Albornoz, Iván Árcos, Paolo Rosso, Damiano Spina, Enrique Amigó, Julio Gonzalo, Roser Morante. 1690-1735 [doi]
• Sexism Identification in Tweets Using Ensembles & Augmentation: A Multilingual ApproachSyeda Rija Hasan Abidi, Muhammad Shoaib Khursheed, Sarah Faisal Sikandar, Sabahat Zahra, Faisal Alvi, Abdul-Samad. 1736-1751 [doi]
• Leveraging Model Confidence and Diversity: A Multi-Stage Framework for Sexism DetectionAnwar Alajmi, Gabriele Pergola. 1752-1760 [doi]
• CogniCIC at EXIST 2025: Identifying Sexist Content in Text and Visual Media using Transformers and Generative AI ModelsTania Alcántara, Omar García-Vázquez, Hiram Calvo, José E. Valdez Rodríguez. 1761-1776 [doi]
• Tackling Sexism in Multimodal Social Media: Exploring Hybrid Generative-Transformer modelsMoiz Ali, Lakshmi Yendapalli, Bishoy Tawfik, Matt Winzenried. 1777-1792 [doi]
• DUTH at EXIST 2025: Multilingual Sexism Detection with Soft Labels and TransformersGeorgios Arampatzis, Vasileios Perifanis, Symeon Symeonidis, Avi Arampatzis. 1793-1800 [doi]
• ArcosGPT at EXIST 2025: Identifying Sexism in Memes with Multimodal Deep Learning: Fusing Text and Visual CuesIván Árcos. 1801-1808 [doi]
• ANLP-Uniso at Exist! 2025 : Sexism Identification and Characterization in TweetsGhada Ben Amor, Nawres Medimagh, Sawsen Ben Chaabene, Omar Trigui. 1809-1827 [doi]
• CLTL at EXIST 2025: Identifying Sexist Memes Using an Ensemble of Shallow and Transformer ModelsAriana Britez, Ilia Markov. 1828-1839 [doi]
• Beyond Binary: 7-Class Sexism Identification via ModernBERT and SCLDonejie Chen, Haoliang Qi. 1840-1847 [doi]
• Modeling Annotator Subjectivity for Sexism Detection on Social MediaQizhang Chen, Leilei Kong, Yanfu Chen, Changxin Sun. 1848-1857 [doi]
• Generalizable BERT-Based Cross-Media Sexism ClassificationTim Chopard, Darren Rawlings. 1858-1865 [doi]
• NLPDame at EXIST: Sexism Categorization in Tweets via Multi-Head Multi-Task Models, LLM & RAG Voting SynergyChristina Christodoulou. 1866-1886 [doi]
• ECORBI-UPV at EXIST 2025: Large Language Models and Embedding Strategies for Sexism Detection in TweetsEurídice Corbí Verdú, Marc Franco-Salvador. 1887-1896 [doi]
• NetGuardAI at EXIST2025: Sexism Detection using mDeBERTaMaria-Diana Cotelin, Ciprian-Octavian Truica, Elena Simona Apostol. 1897-1905 [doi]
• Sexism Identification in Social Networks using LLMsLeire Dominguez-Sol Sastre, Isabel Segura-Bedmar. 1906-1946 [doi]
• ECA-SIMM-UVa at EXIST 2025: A Segmentation Oriented Approach to Sexism Detection in Tik Tok Videos Based on a "One Is Enough" ParadigmDavid Fernández-García, Enrique Amigó Cabrera, Valentín Cardeñoso-Payo. 1947-1958 [doi]
• COMFOR at EXIST 2025: Support Vector Machines vs. Large Language Models in Sexism DetectionFabio Fritzsche, Jenny Felser, Michael Spranger. 1959-1977 [doi]
• I2C-UHU-Altair at EXIST2025: Multimodal Sexism Detection and Classification Using Advanced Vision-Language Models BLIP2 and Qwen, Large Language Models, and Learning with Disagreement FrameworksManuel Guerrero-García, Fernando Carrillo García, Jacinto Mata Vázquez, Victoria Pachón Álvarez. 1978-1993 [doi]
• Dandys-de-BERTganim at EXSIST 2025: a Multi-task Learning Architecture for Sexism IdentificationMarc Hurtado, Aleixandre Tarrasó. 1994-2003 [doi]
• Sexism Detection in Multilingual TweetsAhmed Ibrahim, Rui Pedro Lopes. 2004-2011 [doi]
• TrankilTwice at EXIST2025: Detecting Sexism in Memes under Multi-Lingual SettingsPaolo Italiani, Fariha Maqbool, David Gimeno-Gómez, Elisabetta Fersini, Carlos D. Martínez-Hinarejos. 2012-2022 [doi]
• Sexism Identification using Annotator Ranking in Memes: A Multimodal Approach Using TransformersDeobrat Kumar Jha, Mitesh Kumar Mandal, Anand Kumar Madasamy. 2023-2035 [doi]
• Multilingual Sexism Detection through Domain Adaptation and Label-Augmented TranslationSahrish Khan, Arshad Jhumka, Gabriele Pergola. 2036-2045 [doi]
• FHSTP@EXIST 2025 Benchmark: Sexism Detection with Transparent Speech Concept Bottleneck ModelsRoberto Labadie Tamayo, Adrian Jaques Böck, Djordje Slijepcevic, Xihui Chen, Andreas Babic, Matthias Zeppelzauer. 2046-2057 [doi]
• GrootWatch at EXIST 2025: Automatic Sexism Detection on Social Networks - Classification of Tweets and MemesNathan Nowakowski, Lorenzo Calogiuri, Elöd Egyed-Zsigmond, Diana Nurbakova, Johan Erbani, Sylvie Calabretto. 2058-2083 [doi]
• UMUTeam at EXIST 2025: Multimodal Transformer Architectures and Soft-Label Learning for Sexism DetectionRonghao Pan, Tomás Bernal-Beltrán, José Antonio García-Díaz, Rafael Valencia-García. 2084-2099 [doi]
• CLiC at EXIST 2025: Combining Fine-tuning and Prompting with Learning with Disagreement for Sexism DetectionPol Pastells, Mauro Vázquez Chas, Mireia Farrús, Mariona Taulé. 2100-2111 [doi]
• Awakened at EXIST2025: Adaptive Mixture of TransformersAlexandru Petrescu, Elena Simona Apostol, Ciprian-Octavian Truica. 2112-2118 [doi]
• NYCU-NLP at EXIST 2025: An Empirical Study of Annotator-Aware Two-Stage Pipeline for Sexism Detection in TweetsJoy Chrissetyo Prajogo, Lung-Hao Lee, Hsien-I Lin. 2119-2132 [doi]
• Comparative Analysis of Transformer-Based Models for Sexism Detection in TextBeatriz Ruiz. 2133-2143 [doi]
• Mario at EXIST 2025: A Simple Gateway to Effective Multilingual Sexism DetectionLin Tian, Johanne R. Trippas, Marian-Andrei Rizoiu. 2144-2156 [doi]
• Knowledge Expansion Guided by Justification for Improved Sexism CategorizationKapioma Villarreal Haro, Fernando Sánchez-Vega, Adrián Pastor López-Monroy. 2157-2164 [doi]
• Leveraging Reasoning of Auto-Revealed Insights via Knowledge Injection and Evolutionary Prompting for Sexism AnalysisKapioma Villarreal Haro, Judith Tavarez-Rodríguez, Guillermo Segura-Gómez, Alejandro Rosales-Pérez, Fernando Sánchez-Vega, Adrián Pastor López-Monroy. 2165-2181 [doi]
• Overview of the ImageCLEFMedical 2025 GANs Task: Training Data Analysis and Fingerprint DetectionAlexandra-Georgiana Andrei, Mihai Gabriel Constantin, Mihai Dogariu, Ahmedkhan Radzhabov, Liviu-Daniel Stefan, Yuri Prokopchuk, Vassili Kovalev, Henning Müller, Bogdan Ionescu. 2182-2196 [doi]
• Overview of ImageCLEFmedical 2025 - Medical Concept Detection and Interpretable Caption GenerationHendrik Damm, Tabea Margareta Grace Pakull, Helmut Becker, Benjamin Bracke, Bahadir Eryilmaz, Louise Bloch, Raphael Brüngel, Cynthia S. Schmidt, Johannes Rückert, Obioma Pelka, Henning Schäfer, Ahmad Idrissi-Yaghir, Asma Ben Abacha, Alba Garcia Seco de Herrera, Henning Müller, Christoph M. Friedrich. 2197-2223 [doi]
• Overview of ImageCLEFmedical 2025 - Visual Question Answering and Synthetic Image Generation for Gastrointestinal TractSushant Gautam, Vajira Thambawita, Michael Riegler 0001, Pål Halvorsen, Steven Hicks. 2224-2232 [doi]
• Overview of the MEDIQA-MAGIC Task at ImageCLEF 2025: Multimodal And Generative TelemedICine in DermatologyWen-wai Yim, Asma Ben Abacha, Noel Codella, Roberto A. Novoa, Josep Malvehy. 2233-2240 [doi]
• Overview of the 2025 ImageCLEFtoPicto Task - Investigating the Generation of Pictogram Sequences from Text and SpeechCécile Macaire, Diandra Fabre, Benjamin Lecouteux, Didier Schwab. 2241-2248 [doi]
• Overview of ImageCLEF 2025 - Multimodal ReasoningDimitar Dimitrov 0003, Ming Shan Hee, Zhuohan Xie, Rocktim Jyoti Das, Momina Ahsan, Sarfraz Ahmad, Nikolay Paev, Ivan Koychev, Preslav Nakov. 2249-2263 [doi]
• Towards Better Gastrointestinal Diagnosis: Evaluating Vision-Language Models For GI VQAOmar Adjali. 2264-2274 [doi]
• MSA at ImageCLEF 2025 Multimodal Reasoning: Multilingual Multimodal Reasoning With Ensemble Vision-Language ModelsSeif Ahmed, Mohamed T. Younes, Abdelrahman Moustafa, Abdulrahman Allam, Hamza Moustafa. 2275-2283 [doi]
• Ayeshaamjad at ImageCLEF 2025 Multimodal Reasoning: Visual Question Answering with Structured Data Extraction and Robust ReasoningAyesha Amjad, Fatima Seemab, Saima Kausar, Seemab Latif, Mehwish Fatima. 2284-2300 [doi]
• AI Multimedia Lab at ImageCLEFmedical GANs 2025: Identifying Real-Image Usage in Generated Medical ImagesAlexandra-Georgiana Andrei, Mihai Gabriel Constantin, Mihai Dogariu, Liviu-Daniel Stefan, Bogdan Ionescu. 2301-2310 [doi]
• JJ-VMed: A Framework for Automated Concepts, Captions and Explainability of Medical ImageJohanna Angulo, Jenny Paula Aguilar Guiñez. 2311-2332 [doi]
• Controlling the Quality of Synthetic Medical Images Created via GANsFarhaan Areeb, Divyansh Vashist, Lekshmi Kalinathan. 2333-2340 [doi]
• The Kasukabe Defense Group at MEDIQA-MAGIC 2025: Clinical Visual Question Answering with Resource-Efficient Multi-modal LearningKhushi Bahadur Desai, Varunkumar S. Hiregoudar, Ishan G. Kulkarni, Ratan Dhane, Padmashree Desai, Sujatha C, Uma Mudenagudi, Ramesh Ashok Tabib. 2341-2349 [doi]
• Reverse Engineering Generative Fingerprints in Medical Images: A Deep Learning Approach to Training Data AttributionMitra Barve, Nikita Bhedasgaonkar, Isha Shah, Sara Nambiar, Atharva Date, Geetanjali Kale. 2350-2359 [doi]
• UIT-Oggy at ImageCLEFmedical 2025 Caption: CSRA-Enhanced Concept Detection and BLIP-Driven Vision-Language CaptioningGia-Phuc Bui-Hoang, My-Huyen Dinh-Doan, Van-Minh Luong, Thien B. Nguyen-Tat. 2360-2372 [doi]
• Detecting Training Data Fingerprints in GAN-Generated Medical ImagesShruti Chandrasekar, Vedajanaani R. S, Vijayalakshmi P. 2373-2381 [doi]
• Identify Training Data Subsets in GAN-Generated Medical ImagesShruti Chandrasekar, Vedajanaani R. S, Vijayalakshmi P. 2382-2390 [doi]
• AUEB NLP Group at ImageCLEFmedical Caption 2025Anna Chatzipapadopoulou, Ippokratis Pantelidis, Foivos Charalampakos, Marina Samprovalaki, Georgios Moschovis, Panagiotis Kaliosis, Kalliopi V. Dalakleidi, John Pavlopoulos, Ion Androutsopoulos. 2391-2414 [doi]
• Modality-Guided Radiology Caption Prediction with small Vision-Language Models and image classifierRaisa Nusrat Chowdhury, Mahmudul Hoque, Md. Rakibul Hasan, Ojonugwa Oluwafemi Ejiga Peter, Md Mahmudur Rahman 0003. 2415-2425 [doi]
• Bridging the Modality Gap Through CoT-Enhanced Multimodal ReasoningShengjun Deng, Guo Niu, Xiongfei Yao, Huanlin Mo, Tao Li, Shuaiwei Jiao. 2426-2431 [doi]
• Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025Sujata Gaihre, Amir Thapa Magar, Prasuna Pokharel, Laxmi Tiwari. 2432-2441 [doi]
• Identifying the Origins of Synthetic Biomedical Images: An Ensemble Approach with Pseudo-LabelingAmilcare Gentili. 2442-2447 [doi]
• DS4DH Group at ImageCLEFmedical Caption 2025Jiawei He, Sohrab Ferdowsi, Weibo Feng, Fernando Alves, Alexandra Platon, Douglas Teodoro. 2448-2460 [doi]
• Parlez-vous Picto? A Transformer-Based Approach for Text-to-Picto and Speech-to-Picto Translation in FrenchMaja J. Hjuler, Indira Fabre. 2461-2475 [doi]
• Team plutohbj at ImageCLEF 2025 Multimodal Reasoning: Meta-learning LoRa fine-tuning for MultimodalReasoningBaijian Huang, Changle Zhong, Kai Yan. 2476-2485 [doi]
• ContextDrift at ImageCLEF 2025 Multimodal Reasoning: Evaluating VLMs' Multimodal, Multilingual and Multidomain Reasoning Capabilities via Thinking Budget Variations and Textual AugmentationVasilena T. Krazheva, Diana Markova, Dimitar Dimitrov 0003, Ivan Koychev, Preslav Nakov. 2486-2499 [doi]
• Anastasia at MEDIQA-MAGIC 2025: A Multi-Approach Segmentation Framework with Extensive AugmentationTung Thanh Le, Tri Minh Ngo, Khoi Dinh Nguyen, Trung Hieu Dang, Trong Hoang Pham, Thien B. Nguyen-Tat. 2500-2510 [doi]
• AI Stat Lab: A Modular Framework for Clinically Accurate Medical Image Captioning Using Vision-Language ModelsYunseo Lee, Hyun-Jun Kim, Heeseung Shin, Changwon Lim. 2511-2523 [doi]
• Multimodal Learning for Skin Lesion Segmentation and Closed Visual Question AnsweringBhagyashree Mallanaikar, Shradha Kekare, Padmashree Desai, Sujata C, Uma Mudenagudi, Ramesh Ashok Tabib, Anjali Savalkar, Aishwarya S. H. 2524-2531 [doi]
• Multimodal Reasoning in Multilingual Visual Question Answering: A Prompt-Tuned Qwen2.5-vl-plus ApproachHuanlin Mo, Guo Niu, Shengjun Deng, Xiongfei Yao, Tao Li, Shuaiwei Jiao. 2532-2538 [doi]
• Solving Medical Data Limitations Through AI: Multi-Modal Vision-Language Learning for Gastrointestinal VQA and Synthetic Training Data GenerationOjonugwa Oluwafemi Ejiga Peter, Mahmudul Hoque, Ejiga Frederick Akor, Raisa Nusrat Chowdhury, Abdullahi Umar, Md Mahmudur Rahman 0003. 2539-2552 [doi]
• UMUTeam at ImageCLEF 2025: Fine-Tuning a Vision-Language Model for Medical Image Captioning and SapBERT-Based Reranking for Concept DetectionRonghao Pan, Tomás Bernal-Beltrán, José Antonio García-Díaz, Rafael Valencia-García. 2553-2563 [doi]
• Querying GI Endoscopy Images: A VQA ApproachGaurav Parajuli. 2564-2570 [doi]
• DermoSegDiff and DermKEM for Comprehensive Dermatology AINguyen Pham Hoang Le, Hoang Pham Duc Huy, Hien Thai Dinh Nhat, Hoang Thach Minh, Thien B. Nguyen-Tat. 2571-2588 [doi]
• Evaluating Deep CNNs for Multi-Label Concept Detection in ROCOv2 Radiology Image Dataset by Team LekshmiscopeVITAryan Sahni, Rachit Gupta, Raamigaani Venugopal Reddy, Lekshmi Kalinathan. 2589-2595 [doi]
• Detecting Concepts for Medical Images: Contributions of the DeepLens Team at IUST to ImageCLEFmedical Caption 2025Amir Hossein Salimi Rudsari, Bahareh Kavousi Nejad, Malihe Hajihosseini, Sauleh Eetemadi. 2596-2608 [doi]
• Detecting Training Data Usage in Synthetic Images Using Machine Learning TechniquesKrithikha Sanju Saravanan, Mohanavalli Subramaniam, R. B. Anirudh Narayanan, Bharath P, Karunanidhi Ayyamperumal. 2609-2618 [doi]
• Leveraging Qwen2.5-VL-72B-Instruct for Visual Question Answering: A Study on the EXAMS-V Benchmark in ImageCLEF 2025Tarun Srikumar, Sathish Kesavan, Abinayaa Morekonda Balan, Derrick Samuel, Maneesh Ram Kalugasala Moorthy, Gobi Elangovan, Vinayak Kumar Singh, Lekshmi Kalinathan. 2619-2624 [doi]
• Advancing Vision and Language in GI Diagnosis: Florence2 for Question Answering and Stable Diffusion for Image SynthesisKrishna Tewari, Sukomal Pal. 2625-2639 [doi]
• IReL, IIT(BHU) at MEDIQA-MAGIC 2025: Tackling Multimodal Dermatology with CLIPSeg-Based Segmentation and BERT-Swin Question AnsweringKrishna Tewari, Abhyudaya Verma, Sukomal Pal. 2640-2650 [doi]
• Cultivating Multimodal Intelligence: Interpretive Reasoning and Agentic RAG Approaches to Dermatological DiagnosisKarishma Thakrar, Shreyas Basavatia, Akshay Daftardar. 2651-2680 [doi]
• ImageCLEF-Medical 2025: MedCLIP Model for Medical Caption Prediction and Concept DetectionSakthi Mukesh Thanga Mariappan, Beulah Arul, Muthulakshmi Ramasamy. 2681-2689 [doi]
• Zero-Shot Reasoning with BLIP and SmolLMElena Tosheva, Dimitar Dimitrov 0003, Ivan Koychev, Preslav Nakov. 2690-2694 [doi]
• A Multimodal Feature Alignment Prompt-Enhanced Method for Multimodal ReasoningQida Wu, Leilei Kong, Jianzhong Yan, Junyi Li. 2695-2703 [doi]
• Multi-Prompt Ensemble Reasoning for MultimodalReasoningJianzhong Yan, Leilei Kong, Qida Wu, Junyi Li. 2704-2711 [doi]
• Enhancing Multilingual VQA with Structured Prompts and Vision-Language AlignmentXiongfei Yao, Guo Niu, Tao Li, Huanlin Mo, Shengjun Deng, Shuaiwei Jiao. 2712-2717 [doi]
• Evaluation of the Privacy of Images Generated by ImageCLEFmedical GANs 2025 Based on Pre-trained Model Feature Extraction MethodsDengtao Zhang, Xutao Yang. 2718-2727 [doi]
• ViT-based Generative Model FingerprintingYijiang Zhou, Haiyan Ding. 2728-2735 [doi]
• Evaluating of the Privacy of Images Generated by ImageCLEFmedical GAN 2025 Using Similarity Classification Method Based on Image Enhancement and Deep Learning ModelHaojie Zuo, Xiaobing Zhou. 2736-2743 [doi]
• Overview of the CLEF 2025 JOKER Task 1: Humour-aware Information RetrievalLiana Ermakova, Ricardo Campos 0001, Anne-Gwenn Bosser, Tristan Miller. 2744-2760 [doi]
• Overview of the CLEF 2025 JOKER Task 2: Wordplay Translation from English into FrenchLiana Ermakova, Ricardo Campos 0001, Anne-Gwenn Bosser, Tristan Miller. 2761-2779 [doi]
• Overview of the CLEF 2025 JOKER Task 3: Onomastic Wordplay TranslationLiana Ermakova, Tristan Miller, Yaël Naud, Anne-Gwenn Bosser, Ricardo Campos 0001. 2780-2790 [doi]
• DUTH at CLEF JOKER 2025 Tasks 2 and 3: Translating Puns and Proper Names with Neural ApproachesGeorgios Arampatzis, Avi Arampatzis. 2791-2802 [doi]
• PICT at CLEF 2025 JOKER Track: Humour-Aware Information Retrieval using BERT-Enhanced Ensemble MethodsTanish Chaudhari, Ashni A. Vora, Sanjeev Hotha, Sheetal Sonawane. 2803-2812 [doi]
• CLEF 2025 JOKER Track Enhancing Humor-Aware Information Retrieval with Relevance-Aware ClassificationBo Chen, Changle Zhong, Leilei Kong. 2813-2820 [doi]
• University of Amsterdam at the CLEF 2025 JOKER TrackAlecsandru Kreefft-Libiu, Finley Helms, Cem Selçuk, Jan Bakker, Jaap Kamps. 2821-2828 [doi]
• CLEF 2025 JOKER Track: No Pun Left BehindIgor Kuzmin. 2829-2837 [doi]
• UTBNLP at CLEF JOKER 2025 Task 2: mBART-50 Fine-Tuning with Dictionary-Guided Forced Decoding and Phoneme-Based Techniques for English-French Pun TranslationDuván-Andrés Marrugo-Tobón, Jeison D. Jimenez, Jairo E. Serrano, Juan Carlos Martínez Santos, Edwin Puertas. 2838-2848 [doi]
• REC_Cryptix at JOKER CLEF 2025: Teaching Machines to Laugh: Multilingual Humor Detection and TranslationSarath Kumar P, Beulah A, Sushmitha M, Thanalaxmi S. 2849-2859 [doi]
• VerbaNexAI at CLEF 2025 JOKER Task 3: Multi-Model LLM Approach for Onomastic Wordplay TranslationMaria Paz Ramirez Atencio, Jeison D. Jimenez, Deyson Gómez Sánchez, Jairo E. Serrano, Juan Carlos Martínez Santos, Edwin Puertas. 2860-2869 [doi]
• Pun Intended: Multi-Agent Translation of Wordplay with Contrastive Learning and Phonetic-Semantic Embeddings for CLEF JOKER 2025 Task 2Russell Taylor, Benajmin Herbert, Michael Sana. 2870-2888 [doi]
• pjmathematician at the CLEF 2025 JOKER Lab Tasks 1, 2 & 3: A Unified Approach to Humour Retrieval and Translation using the Qwen LLM FamilyPoojan Vachharajani. 2889-2897 [doi]
• Overview of AnimalCLEF 2025: Recognizing Individual Animals in ImagesLukás Adam, Kostas Papafitsoros, Roman Kovár, Vojtech Cermák, Lukás Picek. 2898-2908 [doi]
• Overview of BirdCLEF+ 2025: Multi-Taxonomic Sound Identification in the Middle Magdalena, ColombiaJuan Sebastián Cañas, Stefan Kahl, Tom Denton, Maria Paula Toro-Gómez, Susana Rodríguez-Buritica, Jose Luis Benavides-Lopez, Juan Sebastian Ulloa, Paula Caycedo-Rosales, Holger Klinck, Hervé Goëau, Willem-Pier Vellinga, Robert Planqué, Alexis Joly. 2909-2919 [doi]
• Overview of FungiCLEF 2025: Few-Shot Classification With Rare Fungi SpeciesKlára Janousková, Jirí Matas, Lukás Picek. 2920-2931 [doi]
• Overview of GeoLifeCLEF 2025: Plant Species Presence Prediction with Environmental and High-resolution Remote Sensing DataLukás Picek, César Leblanc, Théo Larcher, Maximilien Servajean, Pierre Bonnet, Alexis Joly. 2932-2941 [doi]
• Overview of PlantCLEF 2025: Multi-Species Plant Identification in Vegetation Quadrat ImagesGiulio Martellucci, Hervé Goëau, Pierre Bonnet, Fabrice Vinatier, Alexis Joly. 2942-2954 [doi]
• I2C-UHU-PEGASUS at FungiCLEF 2025: Multimodal Pipeline for Rare Fungal Species Classification Using Fine-Tuned VLMs and Ecological ContextFernando Carrillo García, Victoria Pachón Álvarez, Jacinto Mata Vázquez, Manuel Guerrero-García. 2955-2968 [doi]
• Enhancing Presence-Absence Prediction Models Using Presence-Only DataTim Chopard, Darren Rawlings. 2969-2978 [doi]
• Preprocessing Is All You Need: TheHeartOfNoise Submission to PlantCLEF 2025Vincent Espitalier. 2979-3000 [doi]
• Few-Shot Fungi Classification with Prototypical Networks Using Multiple Pretrained Embedding ModelsJack N. Etheredge. 3001-3010 [doi]
• Gradient Boosting Similarity in Entity MatchingSergei Fedorchenko, Sergei Arefiev. 3011-3018 [doi]
• Zero-Shot Segmentation through Prototype-Guidance for Multi-Label Plant Species IdentificationLuciano Araujo Dourado Filho, Almir Moreira da Silva Neto, Rodrigo Pereira David, Rodrigo Tripodi Calumby. 3019-3028 [doi]
• Tile-Based ViT Inference with Visual-Cluster Priors for Zero-Shot Multi-Species Plant IdentificationMurilo Gustineli, Anthony Miyaguchi, Adrian Cheung, Divyansh Khattak. 3029-3038 [doi]
• Multi-Label Plant Species Prediction with Metadata-Enhanced Multi-Head Vision TransformersHanna Herasimchyk, Robin Labryga, Tomislav Prusina. 3039-3049 [doi]
• Post-Hoc Aggregation as a Competitive Alternative to Model-Centric Pipelines: NEUON Submission to PlantCLEF 2025Hamza Ahmed Ishrat, Sue Han Lee, Yang Loong Chang, Kok Chin Chai. 3050-3068 [doi]
• Fusion of Global and Local Descriptors with Feature Calibration for Multi-Species Animal Re-Identification: AnimalCLEF 2025Dongyeon Kim, Bohee Park, Hanjun Bae, Sua Lee, Chaeyeon Lee. 3069-3079 [doi]
• Tighnari v2: Mitigating Label Noise and Distribution Shift in Multimodal Plant Distribution Prediction via Mixture of Experts and Weakly Supervised LearningHaixu Liu, Yufei Wang, Tianxiang Xu, Chuancheng Shi, Hongsheng Xing. 3080-3093 [doi]
• Few-Shot Classification of Fungi Species Using Contrastive Representation Learning and Multimodal FusionLianping Lu, Heng Yang, Shuo Li 0010, Fang Liu 0034, Puhua Chen, Wenping Ma 0001. 3094-3101 [doi]
• Tiles-wise Inference with Vision Transformers for Multispecies Identification in Vegetation ImagesAndrea Menco-Tovar, Jairo E. Serrano, Juan Carlos Martínez Santos, Edwin Puertas. 3102-3110 [doi]
• Distilling Spectrograms into Tokens: Fast and Lightweight Bioacoustic Classification for BirdCLEF+ 2025Anthony Miyaguchi, Murilo Gustineli, Adrian Cheung. 3111-3127 [doi]
• DS@GT AnimalCLEF: Triplet Learning over ViT Manifolds with Nearest Neighbor Classification for Animal Re-identificationAnthony Miyaguchi, Chandrasekaran Maruthaiyannan, Charles R. Clark. 3128-3138 [doi]
• Individual Wildlife Recognition via Hybrid Global-Local Matching and Segmentation-Aware FilteringRoman Pakhomov, Grigory Demidov, Kristian Bogdan, Svyatoslav Lanskikh, Danis Dinmuhametov, Andrey Khlopotnykh. 3139-3146 [doi]
• Shadow Spark at PlantCLEF 2025 : Multi-Label Plant Species Classification using Tiling-based InferenceJayasree R, P. Mirunalini, Kawvya M. K, Harini J. 3147-3153 [doi]
• Meta‑Algorithm for Open‑Set Animal Re-ID: WildFusion, XGBoost, and Dual‑Backbone ArcFaceNelly Semenova. 3154-3165 [doi]
• Optimizing a Vision Transformer with Ecological Context for Multi-Label Plant Species IdentificationNelly Semenova. 3166-3178 [doi]
• One Detector per Bird: A Scalable Binary Classification Approach for BirdCLEF 2025Shreejith Suthraye Gokulnath, Chandrima Das, Arya Gaikwad, Keerthana Senthilnathan, Shruti Sawant. 3179-3198 [doi]
• Predicting Plant Species Distribution with a Multimodal Swin Transformer Network: A GeoLifeCLEF 2025 ReportAman R. Syayfetdinov. 3199-3207 [doi]
• Tackling Domain Shift in Bird Audio Classification via Transfer Learning and Semi-Supervised Distillation: A Case Study on BirdCLEF+ 2025Volodymyr Sydorskyi, Fernando Gonçalves. 3208-3228 [doi]
• Transfer Learning and Mixup for Fine-Grained Few-Shot Fungi ClassificationJason Kahei Tam, Murilo Gustineli, Anthony Miyaguchi. 3229-3241 [doi]
• Open-set Animal Re-identification via Multilevel Feature FusionJingyin Tan, Aiguo Wang. 3242-3247 [doi]
• Dual-branch Network for Species Identification via Passive Acoustic MonitoringJingyin Tan, Aiguo Wang. 3248-3253 [doi]
• I2C-UHU-PERSEUS at PlantClef 2025: Multi-Label Identification and Classification of Plant Species in Images Using Object Detection TechniquesJesús Tejón Carrillo, David Prieto Araujo, Victoria Pachón Álvarez, Jacinto Mata Vázquez. 3254-3262 [doi]
• Synthesizing Joint and Deep Species Distribution Modeling to Enhance Spatial Prediction of Plant Communities at Continental ScaleGleb Tikhonov, Dmitry A. Tikhonov. 3263-3274 [doi]
• Improving Fungi Prototype Representations for Few-Shot ClassificationAbdarahmane Traoré, Éric Hervet, Andy Couturier. 3275-3286 [doi]
• Mushroom for Improvement: Prototypical Few-Shot Learning with Multimodal Fungal FeaturesTuan-Anh Yang, Minh-Quang Nguyen. 3287-3295 [doi]
• Extended Abstract of LongEval at CLEF 2025: Longitudinal Evaluation of IR Systems on Web and Scientific DataMatteo Cancellieri, Alaa El-Ebshihy, Tobias Fink, Maik Fröbe, Petra Galuscáková, Gabriela González Sáez, Lorraine Goeuriot, David Iommi, Jüri Keller, Petr Knoth, Philippe Mulhem, Florina Piroi, David Pride, Philipp Schaer. 3296-3299 [doi]
• DataHunter at LongEval: Temporal Stability Analysis of Boolean and CamemBERT-Based Retrieval SystemsMukhtar Abenov, Leonardo Pontello, Francesca Zaccarin, Shen Zhang, Nicola Ferro 0001. 3300-3315 [doi]
• Team OpenWebSearch at LongEval: Using Historical Data for Scientific SearchDaria Alexander, Maik Fröbe, Gijs Hendriksen, Matthias Hagen, Djoerd Hiemstra, Martin Potthast, Arjen P. de Vries. 3316-3326 [doi]
• Team RAND at LongEval: Composable Information Retrieval with Semantic and Language-Aware ComponentsGiorgia Amato, Nicolas Brentel, Alessio Demo, Steven Laghetto, Francesco Pivotto, Iegor Toporov, Nicola Ferro. 3327-3344 [doi]
• SEUPD@CLEF: Team BASETTE at LongEval: IR System for Basic HardwareAlberto Bottari, Lorenzo Croce, Fatemeh Mahvari Habib Abadi, Nicola Ferro 0001. 3345-3373 [doi]
• CIR at LongEval 2025: Exploring Temporal Sensitivity in Web RetrievalFlorian Braun, Timo Busch, Muhammed Sirac Coban, Maryam El Ghadioui, Davit Hovhannisyan, Kristine Jonina, Andreas Large, Felix Zhi Yong Lin, Eric Loewenstein, Lars Maaßen, Nadine Maron, Mark Henri Mörsheim, Joshua Azimoh Nduka Ofunim, Vadims Romanovskis, Alexander Simon, Jan Witalla, Max Wollenberg, Jüri Keller, Philipp Schaer. 3374-3382 [doi]
• Team 3DS2A at LongEval: Performance Evaluation over Time of IR Systems with Proximity Search and Reranking ComponentsAndrea Bruttomesso, Daniele Cavazza, Alessandro Corrò, Simone Peraro, Davide Seghetto, Nicola Ferro 0001. 3383-3411 [doi]
• SARD at LongEval: On Longitudinal Evaluation of IR Systems by Using Query Rewriting and Hybrid QueriesDamiano Caon, Riccardo Dal Maschio, Alessandro Disarò, Sofia Maule, Nicola Ferro 0001. 3412-3432 [doi]
• SEUPD@CLEF Team RISE at LongEval: Improving Search by Crafting Titles and Matching URLsDavide Furlan, Giulia Gibellato, Seyedeh Sara Nazirialhashem, Emanuele Pase, Alberto Pasqualetto, Filippo Tiberio, Nicola Ferro 0001. 3433-3453 [doi]
• SEUPD2425-RACOON at LongEval 2025: A novel approach to Information Retrieval with LLM-based query expansion and temporal relevance feedback techniquesGiovanni Gaio, Filippo Mazzarotto, Matteo Meneghin, Enrico Saro, Francesco Visonà, Nicola Ferro 0001. 3454-3474 [doi]
• DS@GT at LongEval: Evaluating Temporal Performance in Web Search Systems and Topics with Two-Stage RetrievalAnthony Miyaguchi, Imran Afrulbasha, Aleksandar Pramov. 3475-3487 [doi]
• CIR_cluster at LongEval 2025: Clustering Query Variants for Temporal GeneralizationArthur Muanza Ndiema, Jüri Keller, Philipp Schaer. 3488-3494 [doi]
• AGH IR at LongEval: Improving Scientific Information Retrieval with Dense Representations and Cross-Encoder Re-rankingJan Stryszewski, Wiktor Prosowicz, Tomasz Kawiak, Adrian Jaskowiec. 3495-3503 [doi]
• Overview of the "Voight-Kampff" Generative AI Authorship Verification Task at PAN and ELOQUENT 2025Janek Bevendorff, Yuxia Wang 0003, Jussi Karlgren, Matti Wiegmann, Maik Fröbe, Akim Tsivgun, Jinyan Su, Zhuohan Xie, Mervat Abassy, Jonibek Mansurov, Rui Xing 0002, Minh Ngoc Ta, Kareem Ashraf Elozeiri, Tianle Gu, Raj Vardhan Tomar, Jiahui Geng, Ekaterina Artemova, Artem Shelmanov, Nizar Habash, Efstathios Stamatatos, Iryna Gurevych, Preslav Nakov, Martin Potthast, Benno Stein 0001. 3504-3534 [doi]
• Overview of the Multilingual Text Detoxification Task at PAN 2025Daryna Dementieva, Vitaly Protasov, Nikolay Babakov, Naquee Rizwan, Ilseyar Alimova, Caroline Brun, Vasily Konovalov, Arianna Muti, Chaya Liebeskind, Marina Litvak, Debora Nozza, Shehryaar Shah Khan, Sotaro Takeshita, Natalia Vanetik, Abinew Ali Ayele, Florian Schneider 0001, Xintong Wang 0001, Seid Muhie Yimam, Ashraf Elnagar, Animesh Mukherjee 0001, Alexander Panchenko. 3535-3567 [doi]
• Overview of the Multi-Author Writing Style Analysis Task at PAN 2025Eva Zangerle, Maximilian Mayerl, Martin Potthast, Benno Stein 0001. 3568-3574 [doi]
• Overview of the Plagiarism Detection Task at PAN 2025André Greiner-Petter, Maik Fröbe, Jan Philip Wahle, Terry Ruas, Bela Gipp, Akiko Aizawa, Martin Potthast. 3575-3585 [doi]
• Team KSU at PAN 2025: Multi-Author Writing Style Analysis in English Texts Based on Graph Convolutional NetworksAbeer Saad Alsheddi, Mohamed El-bachir Menai. 3586-3596 [doi]
• DivEye at PAN 2025: Diversity Boosts AI-Generated Text DetectionAdvik Raj Basani, Pin-Yu Chen. 3597-3608 [doi]
• Style Change Detection Using Graph and Structural Linguistic Features for Multi-Author Writing AnalysisIoana-Roxana Boriceanu, Andra-Elena Baltoiu. 3609-3616 [doi]
• Team TMU at PAN 2025: An Ensemble of Fine-Tuned LaBSE and Siamese Neural Network for Multi-Author Writing Style AnalysisSara Bourbour Hosseinbeigi, Ali Mehrani. 3617-3624 [doi]
• MetaDetox at TextDetox CLEF 2025: Detoxification with Few-Chain PromptingSara Bourbour Hosseinbeigi, Amin Saeidi Kelishami, Maryam Gheysari, Fatemeh Rahimzadeh. 3625-3633 [doi]
• Team cornell-1 at PAN: Ensembling Fine-Tuned Transformer Models for Writing Style AnalysisDeniz Bölöni-Turgut, Dhriti Verma, Claire Cardie. 3634-3640 [doi]
• Llama-3 with 4-bit Quantization and IA3 Tuning for Multi-Author Writing Style AnalysisDonejie Chen, Jijie Li, Haoliang Qi. 3641-3647 [doi]
• GemDetox at TextDetox CLEF 2025: Enhancing a Massively Multilingual Model for Text Detoxification on Low-resource LanguagesTrung Duc Anh Dang, Ferdinando Pio D'Elia. 3648-3663 [doi]
• HF_Detox at TextDetox CLEF 2025: Prompt-Driven Multilingual DetoxificationHumaira Farid, Zainab Ahmad, Ahmad Mahmood, Iqra Ameer. 3664-3671 [doi]
• RoBERT-IA: Human-AI Collaborative Text ClassificationDeyson Gómez Sánchez, Jeison D. Jimenez, María Paz Ramírez, Jairo E. Serrano, Juan Carlos Martínez Santos, Edwin Puertas. 3672-3680 [doi]
• Application and Analysis of Roberta-base Model Fine Tuning Based on Data Enhancement in AI Text DetectionJiancheng Huang, Haojie Cao, Xiaocan Lin, Zhongyuan Han. 3681-3688 [doi]
• ReText.Ai Team at PAN 2025: Applying a Multiple Classification Heads to a Transformer Model for Human-AI Collaborative Text ClassificationDaria Ignatenko, Konstantin Zaitsev, Olga Shkriaba. 3689-3697 [doi]
• Team SINAI-INTA at PAN 2025: Uncovering Machine Generated Text with Linguistic FeaturesMaria Jimeno-Gonzalez, Eugenio Martínez-Cámara, Noelia Fernandez, Pedro Díaz-García, Luis Alfonso Ureña López. 3698-3706 [doi]
• SVATS at PAN 2025 TextDetox: Can Small Models Outperform Large Ones in Text Detoxification?Vladislav Kozlovskiy, Sameer Tantry, Alexander Ploskin, Tatyana Matveeva, Sofya Savelyeva. 3707-3726 [doi]
• OpenFact at PAN 2025: Punctuation-Guided Pretraining for Sentence-Level Style Change DetectionEwelina Ksiezniak, Krzysztof Wecel, Marcin Sawinski. 3727-3733 [doi]
• Voight-Kampff AI Detection SensitivityRitesh Kumar, Arya Trivedi, Ojaswa Varshney. 3734-3739 [doi]
• ylmmcl at Multilingual Text Detoxification 2025: Lexicon-Guided Detoxification and Classifier-Gated RewritingNicole Lai-Lopez, Lusha Wang, Su Yuan, Lisa Zhang. 3740-3755 [doi]
• Generative AI detection using simple Feature Selection and SVMJoseph Larson. 3756-3762 [doi]
• Team Bohan Li at PAN: DeBERTa-v3 with R-Drop Regularization for Human-AI Collaborative Text ClassificationBohan Li, Haoliang Qi, Kai Yan. 3763-3769 [doi]
• Fine-Grained Human-AI Collaborative Text Classification Using DeBERTaTao Li, Guo Niu. 3770-3774 [doi]
• Text Author Classification: A ModernBERT Approach with Gradient Loss FunctionZhankeng Liang, Kaiyin Sun, Haojie Cao, Jieren Luo, Zhongyuan Han. 3775-3780 [doi]
• SCL-DeBERTa: Multi-Author Writing Style Change Detection Enhanced by Supervised Contrastive LearningKaichuan Lin, Chang Liu, Fuchuan Ye, Zhongyuan Han. 3781-3787 [doi]
• Team wqd at Style Change Detection in Multi-Author Writing: A Deep Learning Approach Based on DeBERTaXiaocan Lin, Chang Liu, Xianbing Duan, Zhongyuan Han. 3788-3792 [doi]
• Generative AI Authorship Verification Based on Contrastive-Enhanced Dual-Model Decision SystemJunlang Liu, Leilei Kong, Zhenyu Peng, Feifan Chen. 3793-3802 [doi]
• TextDetox CLEF 2025/Multilingual Text Detoxification 2025 Jiaozipi: A Multilingual Text Detoxification Method Based on Large Language Model-Based Ensemble LearningXiaohui Liu, Yusheng Yi, Zhaotian Chen, Simin Xu, Zijun Ke, Xin Guo, Yubo Huang, Wenxuan Zhang, Jiayi Chen, Yong Han. 3803-3812 [doi]
• Team jr at Generative Plagiarism Detection 2025: A Two-Stage Approach: From TF-IDF/Jaccard Filtering to Transformer ClassificationJieren Luo, Mancheng Huang, Biao Liu, Zhongyuan Han. 3813-3818 [doi]
• mdok of KInIT: Robustly Fine-tuned LLM for Binary and Multiclass AI-Generated Text DetectionDominik Macko. 3819-3826 [doi]
• Unibuc - NLP at "Voight-Kampff" Generative AI Detection PAN 2025Teodor-George Marchitan, Claudiu Creanga, Liviu P. Dinu. 3827-3841 [doi]
• Team HHU - An Ensemble-Based Approach to Multi-Author Writing Style Analysis Combining Experts for Different Difficulty LevelsPhilipp Meier, Katarina Boland, Laura Kallmeyer, Stefan Dietze. 3842-3849 [doi]
• Using Semantic Similarity and Overlap Ratio Optimized for Generated Plagiarism DetectionDerui Mo, Huaiyu Zhang, Xiaojun Zhang, Leilei Kong. 3850-3857 [doi]
• Team Detox at PAN: Multilingual Text Detoxification using LLMSiva Gopala Krishna Nuthakki, Sai Teja Lekkala, Atul Mishra. 3858-3864 [doi]
• StylOch at PAN: Gradient-boosted trees with frequency-based stylometric featuresJeremi K. Ochab, Mateusz Matias, Tymoteusz Boba, Tomasz Walkowiak. 3865-3874 [doi]
• Binoculars, BART, and Adversaries: Multi-Faceted AI Text Detection for PAN 2025Benjamin Ostrower, Poonam Dongare, Mahitha Thekkinkattuvalappil Unnikrishnan. 3875-3883 [doi]
• Team cake at TextDetox CLEF 2025/Multilingual Text Detoxification 2025: A Multilingual Text Detoxification Method Based on Chain-of-Thoughts Prompting ApproachJiangao Peng, Kaiyin Sun, Kaichuan Lin, Zhankeng Liang, Zhongyuan Han. 3884-3888 [doi]
• Enhancing AI Text Detection with Frozen Pretrained Encoders and Ensemble LearningShushanta Pudasaini, Luis Miralles Pechuán, David Lillis, Marisa Llorens-Salvador. 3889-3897 [doi]
• Sentence-Level Style Change Detection with RoBERTa for Multi-Author Writing Style AnalysisHarjas Rohra, Nirbhay Shah, Sheetal Sonawane. 3898-3903 [doi]
• Team CNLP-NITS-PP at PAN: Advancing Generative AI Detection: Mixture of Experts with Transformer ModelsSai Teja Lekkala, Annepaka Yadagiri, Partha Pakray. 3904-3915 [doi]
• Team "better_call_claude": Style Change Detection using a Sequential Sentence Pair ClassifierGleb Schmidt, Johannes Römisch, Mariia Halchynska, Svetlana Gorovaia, Ivan P. Yamshchikov. 3916-3928 [doi]
• Human or Not? Light-Weight and Interpretable Detection of AI-Generated TextMaximilian Seeliger, Patrick Styll, Moritz Staudinger, Allan Hanbury. 3929-3941 [doi]
• Team Pratham at TextDetox CLEF 2025/Multilingual Text Detoxification 2025: Exploring Different Methods for Multilingual Text Detoxification via Prompted MT0-XL,Lexical Filtering and BacktranslationPratham Shah, Vatsal Shah, Sunil Kale. 3942-3952 [doi]
• Hierarchical Generative Plagiarism Detection MethodZongbao Su, Yong Han, YiHao Jia, Leilei Kong. 3953-3959 [doi]
• DeBERTa-FPN: Fusion Feature Pyramid Network for Human-AI Collaborative Text ClassificationQiyuan Sun, Li Ma 0011, Wenyin Yang, Tufeng Xian, Meifang Xie, Weidong Wu, Zhiliang Zhang, Miaoji Zheng. 3960-3965 [doi]
• Bi-Directional Cross-Entropy Loss and Stylometric Feature Combined ClassifierYitao Sun, Svetlana Afanaseva, Kevin Stowe, Kailash Patil. 3966-3971 [doi]
• Efficient Plagiarism Detection via Sentence Embeddings and FAISS-based RetrievalJiacheng Tang, Qingbiao Hu, Zhongyuan Han. 3972-3976 [doi]
• LOG-AID: Logit-Based Statistical Features for AI Text DetectionSophie Titze, Oren Halvani. 3977-3984 [doi]
• Team The Toxinators 2000 at TextDetox CLEF 2025/Multilingual Text Detoxification 2025: The Evolution of Methods for Text Detoxification: The Role of Language in Method SelectionAndrei Totok, Artemiy Ermolaev, Anastasia Izyumova, Evgeniy Finogeev. 3985-3994 [doi]
• nikita.sushko at TextDetox CLEF 2025: Exploring A Sage-T5-like Approach For Text DetoxificationAlexandr Voronin, Daniil Moskovsky, Nikita Sushko. 3995-4006 [doi]
• Team Advacheck at PAN: Multitasking Does All the MagicAnastasia Voznyuk, German Gritsai, Andrey V. Grabovoy. 4007-4014 [doi]
• Adept: AI-Generated Text Detection Based on Phrasal Category N-GramsFelix Völpel, Oren Halvani. 4015-4025 [doi]
• Bert_T for Human-AI Collaborative Text ClassificationWeidong Wu, Wenyin Yang, Zhen Shen, Meifang Xie, Zhiliang Zhang, Miaoji Zheng, Tufeng Xian, Qiyuan Sun. 4026-4032 [doi]
• DBG: Human-AI Collaborative Text Classification with DeBERTa-enhanced Contextual and Geometric AttentionTufeng Xian, Yong Zhong, Fen Liu, Meifang Xie, Qiyuan Sun, Miaoji Zheng, Weidong Wu, Zhiliang Zhang. 4033-4041 [doi]
• Sky.Duan at TextDetox CLEF 2025/Multilingual Text Detoxification 2025: An Intelligent Approach Integrating Local Models and Large Language ModelsXianbing Duan, Jiangao Peng, Kaiyin Sun, Zhongyuan Han. 4042-4052 [doi]
• Genre-Aware Contrastive Learning for AI Text Detection: A RoBERTa-Based ApproachJunlong Yang, Kai Yan. 4053-4058 [doi]
• A Sentence-level AI-Generated Text Detection Approach with Fine-Tuned BERTFuchuan Ye, Zhongyuan Han, Haojie Cao. 4059-4062 [doi]
• Team Nexus Interrogators at PAN: Voight-Kampff Generative AI DetectionSamiya Ali Zaidi, Huzaifah Tariq Ahmed, Sarrah Ali Akbar, Ziaullah Shakeel, Faisal Alvi, Abdul-Samad. 4063-4072 [doi]
• DBA: A Hybrid Neural Network Model for Generative Human-AI Collaborative Text ClassificationZhiliang Zhang, Wenyin Yang, Weidong Wu, Meifang Xie, Miaoji Zheng, Qiyuan Sun, Tufeng Xian. 4073-4079 [doi]
• StarBERT: A Hybrid Neural Network Model for Human-AI Collaborative Text ClassificationMiaoji Zheng, Yong Zhong, Fen Liu, Tufeng Xian, Meifang Xie, Weidong Wu, Zhiliang Zhang, Qiyuan Sun. 4080-4085 [doi]
• QuantumCLEF 2025: Overview of the Second Quantum Computing Challenge for Information Retrieval and Recommender Systems at CLEFAndrea Pasin, Maurizio Ferrari Dacrema, Washington Cunha, Marcos André Gonçalves, Paolo Cremonesi, Nicola Ferro 0001. 4086-4104 [doi]
• Team GPLSI at QClef 2025: Quantum-Inspired Instance Selection and ClusteringJuan Pablo Consuegra-Ayala, Aitana Morote Martínez, Francisco Valero-Abellón, Elena Lloret, Paloma Moreda, Manuel Palomar. 4105-4123 [doi]
• Quantum Feature Selection from Interpretable Models using a QUBO FormulationFlavio Giobergia, Claudio Savelli, Alkis Koudounas, Elena Baralis. 4124-4132 [doi]
• SINAI team at QuantumCLEF 2025: Quantum Feature Selection Based on Energy with D-WaveLucas Molino-Piñar, Jaime Collado-Montañez, Arturo Montejo Ráez. 4133-4140 [doi]
• Quantum Annealing for Machine Learning: Applications in Feature Selection, Instance Selection, and ClusteringChloe Pomeroy, Aleksandar Pramov, Karishma Thakrar, Lakshmi Yendapalli. 4141-4157 [doi]
• Feature Selection Using Quantum Annealing: A Mutual Information Based QUBO ApproachMuhammad Talha Shaikh, Muhammad Hamza, Syed Bilal Ali, Muhammad Rafi, Sumaiyah Zahid. 4158-4166 [doi]
• Overview of the CLEF 2025 SimpleText Task 1: Simplify Scientific TextJan Bakker, Benjamin Vendeville, Liana Ermakova, Jaap Kamps. 4167-4185 [doi]
• Overview of the CLEF 2025 SimpleText Task 2: Identify and Avoid HallucinationBenjamin Vendeville, Jan Bakker, Hosein Azarbonyad, Liana Ermakova, Jaap Kamps. 4186-4204 [doi]
• Sentence-level Scientific Text Simplification With Just a Pinch of DataMarvin M. Agüero-Torales, Carlos Rodríguez Abellán, Carlos A. Castaño-Moraga. 4205-4210 [doi]
• DUTH at CLEF 2025 SimpleText Track: Tackling Scientific Text Simplification and Hallucination DetectionGeorgios Arampatzis, Avi Arampatzis. 4211-4224 [doi]
• SINAI in SimpleText CLEF 2025: Simplifying Biomedical Scientific Texts and Identifying Hallucinations Using GPT-4.1 and Pattern DetectionJaime Collado-Montañez, Jenny Alexandra Ortiz Zambrano, César Espin-Riofrio, Arturo Montejo Ráez. 4225-4239 [doi]
• NITK SCaLAR Lab at the CLEF 2025 SimpleText Track: Transformer-Based Models for Biomedical Sentence Simplification (Task 1.1)Arya Adwait Dongre, Ankita Vaadiraaju, Anand Kumar Madasamy. 4240-4254 [doi]
• RECAIDSTechTitans at CLEF 2025: Simplifying Scientific Text and Identifying Spurious Sentences using T5Stergio Eugin, Beulah A, Sathvikha V, Sangamithra V. 4255-4262 [doi]
• University of Avignon at the CLEF 2025 SimpleText Track: Guided Medical Abstract SimplificationYgor Gallina, Tania Jiménez, Stéphane Huet. 4263-4275 [doi]
• THM@SimpleText 2025 - Task 1.1: Revisiting Text Simplification based on Complex Terms for Non-ExpertsNico Hofmann, Julian Dauenhauer, Nils Ole Dietzler, Idehen Daniel Idahor, Christin Katharina Kreutz. 4276-4285 [doi]
• A Benchmark Collection for Assessing Scholarly Search by Non-Educated UsersStéphane Huet, Eric SanJuan. 4286-4300 [doi]
• UM_FHS at the CLEF 2025 SimpleText Track: Comparing No-Context and Fine-Tune Approaches for GPT-4.1 Models in Sentence and Document-Level Text SimplificationPrimoz Kocbek, Gregor Stiglic. 4301-4310 [doi]
• AIIRLab Systems for CLEF 2025 SimpleText: Cross-Encoders to Avoid Spurious GenerationNicholas Largey, Deiby Wu, Behrooz Mansouri. 4311-4323 [doi]
• Hallucination Detection and Mitigation in Scientific Text Simplification using Ensemble Approaches: DS@GT at CLEF 2025 SimpleTextKrishna Chaitanya Marturi, Heba H. Elwazzan. 4324-4337 [doi]
• LLM-Guided Planning and Summary-Based Scientific Text Simplification: DS@GT at CLEF 2025 SimpleTextKrishna Chaitanya Marturi, Heba H. Elwazzan. 4338-4347 [doi]
• LIS at SimpleText 2025: Enhancing Scientific Text Accessibility with LLMs and Retrieval-Augmented GenerationAnya Amel Nait Djoudi, Sarah Nouali, Mohsine Aabid, Ismail Badache, Adrian-Gabriel Chifu, Patrice Bellot. 4348-4355 [doi]
• University of Amsterdam at the CLEF 2025 SimpleText TrackTaiki Papandreou, Jan Bakker, Jaap Kamps. 4356-4362 [doi]
• UBOnlp Report at the SimpleText lab of CLEF 2025Benjamin Vendeville, Liana Ermakova, Pierre De Loor, Jaap Kamps. 4363-4375 [doi]
• S-3 Pipeline for Biomedical Text SimplificationAnsh Vora, Tanish Chaudhari, Sanjeev Hotha, Sheetal Sonawane. 4376-4387 [doi]
• Brief Overview of TalentCLEF 2025Luis Gascó, Hermenegildo Fabregat, Laura García-Sardiña, Paula Estrella, Daniel Deniz, Álvaro Rodrigo, Rabih Zbib. 4388-4391 [doi]
• Enhancing Job-Skill Matching with LLM-Driven Data Augmentation and Fine-Tuned Bi-EncodersMohab Ali. 4392-4400 [doi]
• AlexU-NLP at TalentCLEF 2025: Curriculum-Driven Hybrid Retrieval for Multilingual Job Title MatchingRana Barakat, Omar Mokhtar, Marwan Torki, Nagwa M. El-Makky. 4401-4410 [doi]
• Fine-Tuned Sentence Transformer for Multilingual Job Title MatchingChinmay Satish Bhangale, Prajwal Anil Gabhane, Anand Kumar Madasamy. 4411-4420 [doi]
• Multilingual Job Title Matching with MPNet-Based Sentence TransformersAdam Brikman, Michael Sana, Holden Ruegger. 4421-4427 [doi]
• Multilingual JobBERT for Cross-Lingual Job Title MatchingJens-Joris Decorte, Matthias De Lange, Jeroen Van Hautte. 4428-4437 [doi]
• COTECMAR-UTB at TalentCLEF 2025: Linking Job Titles and ESCO Skills with Sentence Transformer EmbeddingsJhonattan Llamas, Edwin Puertas, Jairo Serrano, Juan Martinez. 4438-4447 [doi]
• VerbaNex at TalenCLEF2025: Semantic Matching of Multilingual Job Titles through a Framework Integrating ESCO TaxonomyMelissa Moreno Novoa, Juan Carlos Martínez Santos, Jairo Serrano, Edwin Puertas. 4448-4458 [doi]
• NT Team at Multilingual Job Title Matching Task A: Job Matching via Large Language Model-Based Description Generation and RetrievalHo Thuy Nga, Ho Thi Thanh Tuyen, Dang Van Thin. 4459-4467 [doi]
• Enhancing Human Capital Management: AI Techniques for Candidate Matching and Skill ExtractionMuhammad Hasan Nizami, Ahtisham Uddin, Muhammad Talha Salani, Ayesha Saeed, Faisal Alvi, Abdul-Samad. 4468-4478 [doi]
• A Two-Stage Multilingual Job Title Matching System: Combining Expert Knowledge and LLM-based RankingMar Rodríguez, Olatz Perez-de-Viñaspre, Naiara Pérez. 4479-4493 [doi]
• UDII-UPM at TalentCLEF 2025: Task A-Multilingual Job Title MatchingJavier Rodríguez-Vidal, Ascensión López-Vargas, Pablo Manuel Vigara Gallego, Francisco Javier del Álamo, Ángel García-Beltrán. 4494-4498 [doi]
• HULAT-UC3M at TalentCLEF: Artificial Intelligence and Natural Language Processing Applied to HR ManagementÁlvaro Tejera Villar, Isabel Segura-Bedmar. 4499-4512 [doi]
• pjmathematician at TalentCLEF 2025: Enhancing Job Title and Skill Matching with GISTEmbed and LLM-Augmented DataPoojan Vachharajani. 4513-4518 [doi]
• Beyond Titles: Semantic Matching of Jobs and Skills Using LLMs and S-BERTIago Xabier Vázquez, Rodrigo Sedano, Silvia González, Javier Sedano. 4519-4524 [doi]
• NLPnorth @ TalentCLEF 2025: Comparing Discriminative, Contrastive, and Prompt-Based Methods for Job Title and Skill MatchingMike Zhang, Rob van der Goot. 4525-4535 [doi]
• Overview of Touché 2025: Argumentation SystemsJohannes Kiesel, Çagri Çöltekin, Marcel Gohsen, Sebastian Heineking, Maximilian Heinrich, Maik Fröbe, Tim Hagen, Mohammad Aliannejadi, Sharat Anand, Tomaz Erjavec, Matthias Hagen, Matyás Kopp, Nikola Ljubesic, Katja Meden, Nailia Mirzakhmedova, Vaidas Morkevicius, Harrisen Scells, Moritz Wolter, Ines Zelch, Martin Potthast, Benno Stein 0001. 4536-4562 [doi]
• Pirate Passau at Touché: Do We Need to Get Complex? A Comparative Analysis of Traditional and Advanced NLP Approaches for Advertisement ClassificationTarek Al Bouhairi, Alaa Alhamzeh. 4563-4570 [doi]
• Hanuman at Touché: Image Generation with Argument-Aspect FusionSharat Anand, Maximilian Heinrich. 4571-4579 [doi]
• DEMA²IN at Touché: Salient Events Extraction for Ideology and Power Identification in Parliamentary DebatesBenjamin Callac, Anne-Gwenn Bosser, Florence Dupin de Saint-Cyr, Eric Maisel. 4580-4585 [doi]
• JU-NLP at Touché: Covert Advertisement in Conversational AI-Generation and Detection StrategiesArka Dutta, Agrik Majumdar, Sombrata Biswas, Dipankar Das 0001, Sivaji Bandyopadhyay. 4586-4600 [doi]
• CEDNAV-UTB: Efficient Image Retrieval for Arguments with CLIPDiego Alberto Guevara Amaya, Jairo Enrique Serrano Castañeda, Juan Carlos Martínez Santos, Edwin Puertas. 4601-4609 [doi]
• Git Gud at Touché: Unified RAG Pipeline for Native Ad Generation and DetectionSameer Kamani, Muhammad Taqi, Muhammad Ansab Chaudhary, Muhammad Ahmad Humayun Hanif, Faisal Alvi, Abdul-Samad. 4610-4618 [doi]
• TeamCMU at Touché: Adversarial Co-Evolution for Advertisement Integration and Detection in Conversational SearchTo Eun Kim, João Coelho, Gbemileke Onilude, Jai Singh. 4619-4634 [doi]
• Munibuc at Touché: Generalist Embeddings for Ideology and Populism DetectionMarius Marogel, Silviu Florin Gheorghe. 4635-4640 [doi]
• DS@GT at Touché: Large Language Models for Retrieval-Augmented DebateAnthony Miyaguchi, Conor Johnston, Aaryan Potdar. 4641-4649 [doi]
• Infotec+CentroGEO at Touché: MCIP, CLIP and SBERT as Retrieval ScoreTania A. Ramirez-delReal, Daniela Moctezuma 0001, Guillermo Ruiz, Mario Graff, Eric Sadit Tellez. 4650-4655 [doi]
• TüNLP at Touché: Finetuning Multilingual Models for Ideology DetectionAydemir Shamsutdinov, Joaquin Cherta-Rodríguez. 4656-4661 [doi]
• SINAI at Touché: From Generation to Evaluation through Multistep and Comparative Prompting for Retrieval-Augmented DebateMaría Estrella Vallecillo Rodríguez, María-Teresa Martín Valdivia, Arturo Montejo Ráez. 4662-4679 [doi]
• GIL_UNAM_Iztacala at Touché: Benchmarking Classical Models for Multilingual Political Stance and Power ClassificationAntonio Miranda-Escalada, Jesús Vázquez-Osorio, Adrián Juárez-Pérez, Gerardo Sierra, Gemma Bel Enguix. 4680-4691 [doi]