Table of Contents

• Overview of BioASQ Tasks 12b and Synergy12 in CLEF2024Anastasios Nentidis, Georgios Katsimpras, Anastasia Krithara, Georgios Paliouras. 1-7 [doi]
• Overview of MultiCardioNER task at BioASQ 2024 on Medical Specialty and Language Adaptation of Clinical NER Systems for Spanish, English and ItalianSalvador Lima-López, Eulàlia Farré-Maduell, Jan Rodríguez-Miret, Miguel Rodríguez-Ortega, Livia Lilli, Jacopo Lenkowicz, Giovanna Ceroni, Jonathan Kossof, Anoop Shah, Anastasios Nentidis, Anastasia Krithara, Georgios Katsimpras, Georgios Paliouras, Martin Krallinger. 8-27 [doi]
• Overview of BioNNE Task on Biomedical Nested Named Entity Recognition at BioASQ 2024Vera Davydova, Natalia V. Loukachevitch, Elena Tutubalina. 28-34 [doi]
• Transformer-Based Disease and Drug Named Entity Recognition in Multilingual Clinical Texts: MultiCardioNER challengeAnna Aksenova, Aleksis Datseris, Sylvia Vassileva, Svetla Boytcheva. 35-46 [doi]
• BIT.UA at BioASQ 12: From Retrieval to Answer GenerationTiago Almeida, Richard A. A. Jonker, João António Reis, João Rafael Almeida, Sérgio Matos. 47-67 [doi]
• LLM Fine-Tuning With Biomedical Open-Source DataChristopher Anaya, Maria Fernandes, Francisco M. Couto. 68-77 [doi]
• Can Open-Source LLMs Compete with Commercial Models? Exploring the Few-Shot Performance of Current GPT Models in Biomedical TasksSamy Ateia, Udo Kruschwitz. 78-98 [doi]
• NCU-IISR: Enhancing Biomedical Question Answering with GPT-4 and Retrieval Augmented Generation in BioASQ 12b Phase BBing-Chen Chih, Jen-Chieh Han, Richard Tzong-Han Tsai. 99-105 [doi]
• Multilingual Clinical NER for Diseases and Medications Recognition in Cardiology Texts using BERT EmbeddingsManuela Daniela Danu, George Marica, Constantin Suciu, Lucian Mihai Itu, Oladimeji Farri. 106-116 [doi]
• Enhancing Biomedical Question Answering with Parameter-Efficient Fine-Tuning and Hierarchical Retrieval Augmented GenerationYichen Gao, Licheng Zong, Yu Li 0006. 117-129 [doi]
• Team NOVA LINCS @ BIOASQ12 MultiCardioNER Track: Entity Recognition with Additional Entity TypesRodrigo Gonçalves, André Lamúrias. 130-137 [doi]
• Generative Large Language Models Augmented Hybrid Retrieval System for Biomedical Question AnsweringBor-Woei Huang. 138-149 [doi]
• BIT.UA at MultiCardioNER: Adapting a Multi-head CRF for CardiologyRichard A. A. Jonker, Tiago Almeida, Sérgio Matos. 150-158 [doi]
• Comparative Analyses of Multilingual Drug Entity Recognition Systems for Clinical Case Reports In CardiologyChaeeun Lee, T. Ian Simpson, Joram M. Posma, Antoine D. Lain. 159-167 [doi]
• Enhancing Biomedical Document Ranking with Domain Knowledge Incorporation in a Multi-Stage Retrieval ApproachMaël Lesavourey, Gilles Hubert 0001. 168-175 [doi]
• MiBi at BioASQ 2024: Retrieval-Augmented Generation for Answering Biomedical QuestionsJan Heinrich Merker, Alexander Bondarenko 0001, Matthias Hagen, Adrian Viehweger. 176-187 [doi]
• Farming Open LLMs for Biomedical Question AnsweringDimitra N. Panou, Alexandros C. Dimopoulos, Martin Reczko. 188-196 [doi]
• Nested Named Entity Recognition using Multilayer BERT-based ModelHasin Rehana, Benu Bansal, Nur Bengisu Çam, Jie Zheng 0001, Yongqun He, Arzucan Özgür, Junguk Hur. 197-206 [doi]
• Identifying Cardiological Disorders in Spanish via Data Augmentation and Fine-Tuned Language ModelsAntonio Romano, Giuseppe Riccio, Marco Postiglione, Vincenzo Moscato. 207-222 [doi]
• Cross-Linguistic Disease and Drug Detection in Cardiology Clinical Texts: Methods and OutcomesPatrick Styll, Leonardo Campillos Llanos, Wojciech Kusa, Allan Hanbury. 223-244 [doi]
• Biomedical Nested NER with Large Language Model and UMLS HeuristicsWenxin Zhou. 245-252 [doi]
• Using Pretrained Large Language Model with Prompt Engineering to Answer Biomedical QuestionsWenxin Zhou, Thuy Hang Ngo. 253-268 [doi]
• HU-WBI at BioASQ12B Phase A: Exploring Rank Fusion of Dense Retrievers and Re-rankersOguz Serbetçi, Xing David Wang, Ulf Leser. 269-275 [doi]
• Overview of the CLEF-2024 CheckThat! Lab Task 1 on Check-Worthiness Estimation of Multigenre ContentMaram Hasanain, Reem Suwaileh, Sanne Weering, Chengkai Li 0001, Tommaso Caselli, Wajdi Zaghouani, Alberto Barrón-Cedeño, Preslav Nakov, Firoj Alam. 276-286 [doi]
• Overview of the CLEF-2024 CheckThat! Lab Task 2 on Subjectivity in News ArticlesJulia Maria Struß, Federico Ruggeri, Alberto Barrón-Cedeño, Firoj Alam, Dimitar Dimitrov, Andrea Galassi, Georgi Pachov, Ivan Koychev, Preslav Nakov, Melanie Siegel, Michael Wiegand, Maram Hasanain, Reem Suwaileh, Wajdi Zaghouani. 287-298 [doi]
• Overview of the CLEF-2024 CheckThat! Lab Task 3 on Persuasion TechniquesJakub Piskorski, Nicolas Stefanovitch, Firoj Alam, Ricardo Campos 0001, Dimitar Dimitrov, Alípio Jorge, Senja Pollak, Nikolay Ribin, Zoran Fijavz, Maram Hasanain, Purificação Silvano, Elisa Sartori, Nuno Guimarães, Ana Zwitter Vitez, Ana Filipa Pacheco, Ivan Koychev, Nana Yu, Preslav Nakov, Giovanni Da San Martino. 299-310 [doi]
• Overview of the CLEF-2024 CheckThat! Lab Task 5 on Rumor Verification using Evidence from AuthoritiesFatima Haouari, Tamer Elsayed, Reem Suwaileh. 311-320 [doi]
• Overview of the CLEF-2024 CheckThat! Lab Task 6 on Robustness of Credibility Assessment with Adversarial Examples (InCrediblAE)Piotr Przybyla, Ben Wu, Alexander V. Shvets, Yida Mu, Kim Cheng Sheang, Xingyi Song, Horacio Saggion. 321-338 [doi]
• IAI Group at CheckThat! 2024: Transformer models and data augmentation for checkworthy claim detectionPeter Røysland Aarnes, Vinay Setty, Petra Galuscáková. 339-350 [doi]
• DEFAULT at CheckThat! 2024: Retrieval Augmented Classification using Differentiable Top-K Operator for Rumor Verification based on Evidence from AuthoritiesSayanta Adhikari, Himanshu Sharma, Rupa Kumari, Shrey Satapara, Maunendra Desarkar. 351-360 [doi]
• Nullpointer at CheckThat! 2024: Identifying Subjectivity from Multilingual Text SequenceMd. Rafiul Biswas, Abrar Tasneem Abir, Wajdi Zaghouani. 361-368 [doi]
• TurQUaz at CheckThat! 2024: A Hybrid Approach of Fine-Tuning and In-Context Learning for Check-Worthiness EstimationMehmet Eren Bulut, Kaan Efe Keles, Mucahid Kutlu. 369-377 [doi]
• HYBRINFOX at CheckThat! 2024 - Task 2: Enriching BERT Models with the Expert System VAGO for Subjectivity DetectionMorgane Casanova, Julien Chanson, Benjamin Icard, Géraud Faye, Guillaume Gadek, Guillaume Gravier, Paul Égré. 378-386 [doi]
• Fired_from_NLP at CheckThat! 2024: Estimating the Check-Worthiness of Tweets Using a Fine-tuned Transformer-based ApproachMd. Sajid Alam Chowdhury, Anik Mahmud Shanto, Mostak Mahmud Chowdhury, Hasan Murad, Udoy Das. 387-395 [doi]
• TurQUaz at CheckThat! 2024: Creating Adversarial Examples using Genetic AlgorithmBasak Demirok, Selin Mergen, Bugra Oz, Mucahid Kutlu. 396-404 [doi]
• Mirela at CheckThat! 2024: Check-worthiness of Tweets with Multilingual Embeddings and Adversarial TrainingMirela Dryankova, Dimitar Dimitrov, Ivan Koychev, Preslav Nakov. 405-410 [doi]
• HYBRINFOX at CheckThat! 2024 - Task 1: Enhancing Language Models with Structured Information for Check-Worthiness EstimationGéraud Faye, Morgane Casanova, Benjamin Icard, Julien Chanson, Guillaume Gadek, Guillaume Gravier, Paul Egré. 411-418 [doi]
• Eevvgg at CheckThat! 2024: Evaluative Terms, Pronouns and Modal Verbs as Markers of Subjectivity in TextEwelina Gajewska. 419-425 [doi]
• UniBO at CheckThat! 2024: Multi-lingual and Multi-label Persuasion Technique Detection in News with Data Augmentation and Sequence-Token ClassifiersPaolo Gajo, Luca Giordano, Alberto Barrón-Cedeño. 426-434 [doi]
• DSHacker at CheckThat! 2024: LLMs and BERT for Check-Worthy Claims Detection with Propaganda Co-occurrence AnalysisPawel Golik, Arkadiusz Modzelewski, Aleksander Jochym. 435-445 [doi]
• CLaC-2 at CheckThat! 2024: A Zero-Shot Model for Check-Worthiness and Subjectivity ClassificationShayne Gruman, Leila Kosseim. 446-452 [doi]
• TextTrojaners at CheckThat! 2024: Robustness of Credibility Assessment with Adversarial Examples through BeamAttackDavid Guzman Piedrahita, Arnisa Fazla, Lucas Krauter. 453-472 [doi]
• Palöri at CheckThat! 2024 Shared Task 6: GloTa - Combining GloVe Embeddings with RoBERTa for Adversarial AttackHaokun He, Yafeng Song, Dylan Massey. 473-482 [doi]
• SSN-NLP at CheckThat! 2024: Assessing the Check-Worthiness of Tweets and Debate Excerpts Using Traditional Machine Learning and Transformer ModelsSanjai Balajee Kannan Giridharan, Sanjjit Sounderrajan, B. Bharathi, Nilu R. Salim. 483-488 [doi]
• AuthEv-LKolb at CheckThat! 2024: A Two-Stage Approach To Evidence-Based Social Media Claim VerificationLuis Kolb, Allan Hanbury. 489-505 [doi]
• OpenFact at CheckThat! 2024: Combining Multiple Attack Methods for Effective Adversarial Text GenerationWlodzimierz Lewoniewski, Piotr Stolarski, Milena Strózyna, Elzbieta Lewanska, Aleksandra Wojewoda, Ewelina Ksiezniak, Marcin Sawinski. 506-519 [doi]
• FactFinders at CheckThat! 2024: Refining Check-worthy Statement Detection with LLMs through Data PruningYufeng Li, Rrubaa Panchendrarajan, Arkaitz Zubiaga. 520-537 [doi]
• Trio Titans at Check That_ 2024 : Check Worthiness EstimationSai Geetha M, Prarthna M, Chiranjeev Prasannaa V. V, Saritha M. 538-545 [doi]
• Mela at CheckThat! 2024: Transferring Persuasion Detection from English to Arabic - A Multilingual BERT ApproachSara Nabhani, Md Abdur Razzaq Riyadh. 546-551 [doi]
• SemanticCuetSync at CheckThat! 2024: Finding Subjectivity in News Articles using LlamaAshraful Islam Paran, Md. Sajjad Hossain, Symom Hossain Shohan, Jawad Hossain, Shawly Ahsan, Mohammed Moshiul Hoque. 552-559 [doi]
• SEUPD@CLEF: Team Axolotl on Rumor Verification using Evidence from AuthoritiesAndrea Pasin, Nicola Ferro 0001. 560-569 [doi]
• SSN-NLP at CheckThat! 2024: From Feature-based Algorithms to Transformers: A Study on Detecting SubjectivityPooja Premnath, Pranav Vaithiya Subramani, Nilu R. Salim, Bharathi B. 570-579 [doi]
• MMU NLP at CheckThat! 2024: Homoglyphs are Adversarial AttacksCharlie Roadhouse, Matthew Shardlow, Ashley Williams. 580-589 [doi]
• Tonirodriguez at CheckThat!2024: Is it Possible to Use Zero-Shot Cross-Lingual Methods for Subjectivity Detection in Low-Resources Languages?Antonio Rodríguez, Elisabet Golobardes, Jaume Suau. 590-597 [doi]
• JK_PCIC_UNAM at CheckThat! 2024: Analysis of Subjectivity in News Sentences Using Transformers-Based ModelsKarla Salas-Jimenez, Iván Díaz, Helena Gómez-Adorno, Gemma Bel Enguix, Gerardo Sierra. 598-604 [doi]
• Indigo at CheckThat! 2024: Using Setfit: A Resource Efficient Technique for Subjectivity Detection in News ArticleSoumyadeep Sar, Dwaipayan Roy. 605-612 [doi]
• OpenFact at CheckThat! 2024: Cross-Lingual Transfer Learning for Check-Worthiness DetectionMarcin Sawinski, Krzysztof Wecel, Ewelina Ksiezniak. 613-631 [doi]
• SemanticCuetSync at CheckThat! 2024: Pre-trained Transformer-based Approach to Detect Check-Worthy TweetSymom Hossain Shohan, Md. Sajjad Hossain, Ashraful Islam Paran, Jawad Hossain, Shawly Ahsan, Mohammed Moshiul Hoque. 632-640 [doi]
• DataBees at CheckThat! 2024: Check-Worthiness EstimationTanisha Sriram, Yadushree Venkatesh, Sowmya Anand, Bharathi B. 641-650 [doi]
• SINAI at CheckThat! 2024: Transformer-based Approaches for Check-Worthiness ClassificationSergiu Stoia, Jaime Collado-Montañez, Cristian Ibáñez-Bautista, Arturo Montejo Ráez, María-Teresa Martín Valdivia, Manuel Carlos Díaz-Galiano. 651-657 [doi]
• SINAI at CheckThat! 2024: Stealthy Character-Level Adversarial Attacks Using Homoglyphs and Iterative SearchJosé Valle-Aguilera, Alberto José Gutiérrez-Megías, Salud María Jiménez Zafra, Luis Alfonso Ureña López, Eugenio Martínez-Cámara. 658-665 [doi]
• Fraunhofer SIT at CheckThat! 2024: Adapter Fusion for Check-Worthiness DetectionInna Vogel, Pauline Möhle. 666-671 [doi]
• FC_RUG at CheckThat! 2024: Few-shot Learning Using GEITje for Check-Worthiness Detection in DutchSanne Weering, Tommaso Caselli. 672-679 [doi]
• Checker Hacker at CheckThat! 2024: Detecting Check-Worthy Claims and Analyzing Subjectivity with TransformersSyeda Duae Zehra, Kushal Chandani, Muhammad Khubaib, Ahmed Ali Aun Muhammed, Faisal Alvi, Abdul-Samad. 680-686 [doi]
• ELOQUENT 2024 - Topical Quiz TaskJussi Karlgren, Aarne Talman. 687-690 [doi]
• Overview of the CLEF-2024 Eloquent Lab: Task 2 on HalluciGenLuise Dürlich, Evangelia Gogoulou, Liane Guillou, Joakim Nivre, Shorouq Zahra. 691-702 [doi]
• ELOQUENT 2024 - Robustness TaskMagnus Sahlgren, Jussi Karlgren, Luise Dürlich, Evangelia Gogoulou, Aarne Talman, Shorouq Zahra. 703-707 [doi]
• Evaluating Poro-34B-Chat and Mistral-7B-Instruct-v0.1: LLM System Description for ELOQUENT at CLEF 2024Vasumathi Neralla, Sander Bijl de Vroe. 708-711 [doi]
• GPT Hallucination Detection Through Prompt EngineeringMarco Siino, Ilenia Tinnirello. 712-721 [doi]
• Experimental Report on Robustness Task - ELOQUENT Lab @ CLEF 2024Annika Simonsen. 722-726 [doi]
• The Two Sides of the Coin: Hallucination Generation and Detection with LLMs as Evaluators for LLMsAnh Thu Maria Bui, Saskia Felizitas Brech, Natalie Hußfeldt, Tobias Jennert, Melanie Ullrich, Timo Breuer 0002, Narjes Nikzad-Khasmakhi, Philipp Schaer. 727-758 [doi]
• Overview of eRisk 2024: Early Risk Prediction on the Internet (Extended Overview)Javier Parapar, Patricia Martín-Rodilla, David E. Losada, Fabio Crestani. 759-781 [doi]
• NUS-IDS@eRisk2024: Ranking Sentences for Depression Symptoms using Early Maladaptive Schemas and EnsemblesBeng Heng Ang, Sujatha Das Gollapalli, See-Kiong Ng. 782-793 [doi]
• REBECCA at eRisk 2024: Search for Symptoms of Depression Using Sentence Embeddings and Prompt-Based FilteringAnna Barachanou, Filareti Tsalakanidou, Symeon Papadopoulos. 794-802 [doi]
• ELiRF-VRAIN at eRisk 2024: Using LongFormers for Early Detection of Signs of AnorexiaAndreu Casamayor, Vicent Ahuir, Antonio Molina, Lluís-Felip Hurtado. 803-812 [doi]
• NLP-UNED at eRisk 2024: Approximate Nearest Neighbors with Encoding Refinement for Early Detecting Signs of AnorexiaHermenegildo Fabregat, Daniel Deniz, Andrés Duque, Lourdes Araujo, Juan Martínez-Romo. 813-824 [doi]
• DS@GT eRisk 2024: Sentence Transformers for Social Media Risk AssessmentDavid Guecha, Aaryan Potdar, Anthony Miyaguchi. 825-833 [doi]
• MindwaveML at eRisk 2024: Identifying Depression Symptoms in Reddit UsersRaluca-Maria Hanciu. 834-840 [doi]
• Automatically Finding Evidence and Predicting Answers in Mental Health Self-Report QuestionnairesDiego Maupomé, Yves Ferstler, Sébastien Mosser 0001, Marie-Jean Meurs. 841-850 [doi]
• SINAI at eRisk@ CLEF 2024: Approaching the Search for Symptoms of Depression and Early Detection of Anorexia Signs using Natural Language ProcessingAlba María Mármol-Romero, Adrián Moreno-Muñoz, Pablo Álvarez-Ojeda, Karla María Valencia-Segura, Eugenio Martínez-Cámara, Manuel García Vega, Arturo Montejo Ráez. 851-861 [doi]
• UMUTeam at eRisk@CLEF 2024: Fine-Tuning Transformer Models with Sentiment Features for Early Detection and Severity Measurement of Eating DisordersRonghao Pan, José Antonio García-Díaz, Tomás Bernal-Beltrán, Rafael Valencia-García. 862-870 [doi]
• APB-UC3M at eRisk 2024: Natural Language Processing and Deep Learning for the Early Detection of Mental DisordersAlejandro Pardo Bascuñana, Isabel Segura-Bedmar. 871-880 [doi]
• Measuring the severity of the signs of Eating Disorders using Machine Learning TechniquesSachin Prasanna, Abhayjit Singh Gulati, Subhojit Karmakar, M. Yoga Hiranmayi, Anand Kumar Madasamy. 881-887 [doi]
• Combining Recommender Systems and Language Models in Early Detection of Signs of AnorexiaOskar Riewe-Perla, Agata Filipowska. 888-893 [doi]
• A Natural Language Processing Based Framework for Early Detection of Anorexia via Sequential Text ProcessingPrateek Sarangi, Sumit Kumar, Shraddha Agarwal, Tanmay Basu. 894-901 [doi]
• A Time-Aware Approach to Early Detection of Anorexia: UNSL at eRisk 2024Horacio Thompson, Marcelo Errecalde. 902-907 [doi]
• Overview of EXIST 2024 - Learning with Disagreement for Sexism Identification and Characterization in Tweets and Memes (Extended Overview)Laura Plaza, Jorge Carrillo-de-Albornoz, Víctor Ruiz, Alba Maeso, Berta Chulvi, Paolo Rosso, Enrique Amigó, Julio Gonzalo, Roser Morante, Damiano Spina. 908-941 [doi]
• RoBEXedda: Sexism Detection in TweetsGiacomo Aru, Nicola Emmolo, Simone Marzeddu, Andrea Piras, Jacopo Raffi, Lucia C. Passaro. 942-957 [doi]
• Bilingual Sexism Classification: Fine-Tuned XLM-RoBERTa and GPT-3.5 Few-Shot LearningAmirMohammad Azadi, Baktash Ansari, Sina Zamani, Sauleh Eetemadi. 958-965 [doi]
• Penta ML at EXIST 2024: Tagging Sexism in Online Multimodal Content With Attention-enhanced Modal ContextDeeparghya Dutta Barua, Md Sakib Ul Rahman Sourove, Fabiha Haider, Fariha Tanjim Shifat, Md Farhan Ishmam, Md Fahim, Farhad Alam Bhuiyan. 966-977 [doi]
• I2C-UHU at EXIST 2024: Transformer-Based Detection of Sexism and Source Intention in Memes Using a Learning with Disagreement ApproachÁlvaro Carrillo-Casado, Javier Román Pásaro, Jacinto Mata Vázquez, Victoria Pachón Álvarez. 978-992 [doi]
• FraunhoferSIT@EXIST2024: Leveraging Stacking Ensemble Learning for Sexism DetectionShiying Fan, Raphael Antonius Frick, Martin Steinebach. 993-1002 [doi]
• NYCU-NLP at EXIST 2024: Leveraging Transformers with Diverse Annotations for Sexism Identification in Social NetworksYi-Zeng Fang, Lung-Hao Lee, Juinn-Dar Huang. 1003-1011 [doi]
• LightGBM for Sexism Identification in MemesArnau García i Cucó, Miquel Obrador Reina. 1012-1017 [doi]
• Automatic Classification of Gender Stereotypes in Social Media PostGersome Shimi, Jerin Mahibha C, Durairaj Thenmozhi. 1018-1025 [doi]
• I2C-UHU at EXIST2024: Learning from Divergence and Perspectivism for Sexism Identification and Source Intent ClassificationManuel Guerrero-García, Manuel Cerrejón-Naranjo, Jacinto Mata Vázquez, Victoria Pachón Álvarez. 1026-1042 [doi]
• Enhancing Sexism Detection in Tweets with Annotator-Integrated Ensemble Methods and Multimodal Embeddings for MemesMartha Paola Jimenez-Martinez, Joan Manuel Raygoza-Romero, Carlos Eduardo Sánchez-Torres, Irvin Hussein López-Nava, Manuel Montes-y-Gómez. 1043-1057 [doi]
• Sexism Identification in Social Networks using TF-IDF Embeddings, PreProccessing, Feature Selection, Word/Char N-Grams and Various Machine Learning Models In Spanish and EnglishRon Keinan. 1058-1069 [doi]
• Multilingual Sexism Identification via Fusion of Large Language ModelsSahrish Khan, Gabriele Pergola, Arshad Jhumka. 1070-1079 [doi]
• RoJiNG-CL at EXIST 2024: Leveraging Large Language Models for Multimodal Sexism Detection in MemesJing Ma, Rong Li. 1080-1090 [doi]
• A Contrastive Learning Based Approach to Detect Sexism in MemesFariha Maqbool, Elisabetta Fersini. 1091-1097 [doi]
• Sexism Identification in Social Networks: Advances in Automated Detection - A Report on the Exist Task at CLEFNimra Maqbool. 1098-1106 [doi]
• VerbaNex AI at CLEF EXIST 2024: Detection of Online Sexism using Transformer Models and Profiling TechniquesElizabeth Martinez, Juan Cuadrado, Juan Carlos Martínez Santos, Edwin Puertas. 1107-1113 [doi]
• DiTana-PV at sEXism Identification in Social neTworks (EXIST) tasks 4 and 6: The Effect of Translation in Sexism IdentificationAitana Menárguez-Box, Diego Torres-Bertomeu. 1114-1121 [doi]
• NICA at EXIST CLEF Tasks 2024Aylin Naebzadeh, Melika Nobakhtian, Sauleh Eetemadi. 1122-1134 [doi]
• UMUTeam at EXIST 2024: Multi-modal Identification and Categorization of Sexism by Feature IntegrationRonghao Pan, José Antonio García-Díaz, Tomás Bernal-Beltrán, Rafael Valencia-García. 1135-1147 [doi]
• UMUTeam at EXIST 2024: Multi-modal Identification and Categorization of Sexism by Feature IntegrationRonghao Pan, José Antonio García-Díaz, Tomás Bernal-Beltrán, Rafael Valencia-García. 1135-1147 [doi]
• UMUTeam at EXIST 2024: Multi-modal Identification and Categorization of Sexism by Feature IntegrationRonghao Pan, José Antonio García-Díaz, Tomás Bernal-Beltrán, Rafael Valencia-García. 1135-1147 [doi]
• Multilingual Sexism Detection in Memes, A CLIP-Enhanced Machine Learning ApproachUmera Wajeed Pasha. 1148-1156 [doi]
• Language-based Mixture of Transformers for EXIST2024Alexandru Petrescu, Ciprian-Octavian Truica, Elena Simona Apostol. 1157-1164 [doi]
• Sexism Identification in Social Networks with Generation-based Language ModelsLe Minh Quan, Dang Van Thin. 1165-1176 [doi]
• PINK at EXIST2024: A Cross-Lingual and Multi-Modal Transformer Approach for Sexism Detection in MemesGiulia Rizzi, David Gimeno-Gómez, Elisabetta Fersini, Carlos D. Martínez-Hinarejos. 1177-1186 [doi]
• Concatenated Transformer Models Based On Levels Of Agreements For Sexism DetectionVíctor Ruiz, Jorge Carrillo-de-Albornoz, Laura Plaza. 1187-1197 [doi]
• Team Aditya at EXIST 2024 - Detecting Sexism in Multilingual Tweets using Contrastive Learning ApproachAditya Shah, Aditya Gokhale. 1198-1202 [doi]
• The Wisdom of Weighing: Stacking Ensembles for a More Balanced Sexism DetectorAbhay Shanbhag, Suramya Jadhav, Atharva Date, Sumedh Joshi, Sheetal Sonawane. 1203-1213 [doi]
• Penta-nlp at EXIST 2024 Task 1-3: Sexism Identification, Source Intention, Sexism Categorization In TweetsFariha Tanjim Shifat, Fabiha Haider, Md Sakib Ul Rahman Sourove, Deeparghya Dutta Barua, Md Farhan Ishmam, Md Fahim, Farhad Alam Bhuiyan. 1214-1227 [doi]
• Prompt Engineering for Identifying Sexism using GPT Mistral 7BMarco Siino, Ilenia Tinnirello. 1228-1236 [doi]
• Prompt Engineering for Identifying Sexism using GPT Mistral 7BMarco Siino, Ilenia Tinnirello. 1228-1236 [doi]
• Prompt Engineering for Identifying Sexism using GPT Mistral 7BMarco Siino, Ilenia Tinnirello. 1228-1236 [doi]
• RMIT-IR at EXIST Lab at CLEF 2024Tony Smith, H. Ruda Nie, Johanne R. Trippas, Damiano Spina. 1237-1252 [doi]
• Sexism Identification in Tweets Using Machine Learning ApproachesMurari Sreekumar, Shreyas Karthik, Durairaj Thenmozhi, Shriram Gopalakrishnan, Krithika Swaminathan. 1253-1259 [doi]
• Better Together: LLM and Neural Classification Transformers to Detect SexismJudith Tavarez-Rodríguez, Fernando Sánchez-Vega, Alejandro Rosales-Pérez, Adrián Pastor López-Monroy. 1260-1273 [doi]
• Sexism Identification in Tweets using BERT and XLM - RobertaMaha Usmani, Rania Siddiqui, Samin Rizwan, Faryal Khan, Faisal Alvi, Abdul-Samad. 1274-1279 [doi]
• Cracking Down on Digital Misogyny with MULTILATE a MULTImodaL hATE Detection SystemAdvaitha Vetagiri, Prateek Mogha, Partha Pakray. 1280-1296 [doi]
• Stacked Reflective Reasoning in Large Neural Language ModelsKapioma Villarreal Haro, Fernando Sánchez-Vega, Alejandro Rosales-Pérez, Adrián Pastor López-Monroy. 1297-1311 [doi]
• Overview of iDPP@CLEF 2024: The Intelligent Disease Progression Prediction ChallengeGiovanni Birolo, Pietro Bosoni, Guglielmo Faggioli, Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Alessandro Guazzo, Enrico Longato, Sara C. Madeira, Umberto Manera, Stefano Marchesin 0001, Laura Menotti, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro 0001. 1312-1331 [doi]
• ALSFRS-R Score Prediction for Amyotrophic Lateral SclerosisGuido Barducci, Flavio Sartori, Giovanni Birolo, Tiziana Sanavia, Piero Fariselli. 1332-1340 [doi]
• Predicting Multiple Sclerosis Relapses Using Patient Exposure TrajectoriesPietro Bosoni, Mahin Vazifehdan, Daniele Pala, Eleonora Tavazzi, Roberto Bergamaschi, Riccardo Bellazzi, Arianna Dagliati. 1341-1352 [doi]
• Using Wearable and Environmental Data to Improve the Prediction of Amyotrophic Lateral Sclerosis and Multiple Sclerosis Progression: an Explorative StudyElena Marinello, Alessandro Guazzo, Enrico Longato, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo. 1353-1365 [doi]
• Predicting the Functional Rating Scale and Self-Assessment Status of ALS Patients with Sensor DataAndreia S. Martins, Daniela M. Amaral, Eduardo N. Castanho, Diogo F. Soares, Ruben Branco, Sara C. Madeira, Helena Aidos. 1366-1379 [doi]
• Machine Learning for ALSFRS-R Score Prediction: Making Sense of the Sensor DataRitesh Mehta, Aleksandar Pramov, Shashank Verma. 1380-1391 [doi]
• UBCS at IDPP: Predicting Patient Self-Assessment Score from Sensor Data using Machine Learning AlgorithmsChibuzor Chukwuemeka Okere, Edwin Thuma, Gontlafetse Mosweunyane. 1392-1400 [doi]
• BIT.UA at iDPP: Predictive Analytics on ALS Disease Progression Using Sensor Data with Machine LearningJorge Miguel Silva, José Luís Oliveira. 1401-1411 [doi]
• Overview of the 2024 ImageCLEFmedical GANs Task - Investigating Generative Models' Impact on Biomedical Synthetic ImagesAlexandra-Georgiana Andrei, Ahmedkhan Radzhabov, Dzmitry Karpenka, Yuri Prokopchuk, Vassili Kovalev, Bogdan Ionescu, Henning Müller. 1412-1428 [doi]
• Overview of ImageCLEFmedical 2024 - Medical Visual Question Answering for Gastrointestinal TractSteven Hicks, Andrea M. Storås, Pål Halvorsen, Michael Riegler 0001, Vajira Thambawita. 1429-1436 [doi]
• Overview of ImageCLEFmedical 2024 - Caption Prediction and Concept DetectionJohannes Rückert, Asma Ben Abacha, Alba Garcia Seco de Herrera, Louise Bloch, Raphael Brüngel, Ahmad Idrissi-Yaghir, Henning Schäfer, Benjamin Bracke, Hendrik Damm, Tabea Margareta Grace Pakull, Cynthia Sabrina Schmidt, Henning Müller, Christoph M. Friedrich. 1437-1455 [doi]
• Overview of the MEDIQA-MAGIC Task at ImageCLEF 2024: Multimodal And Generative TelemedICine in DermatologyWen-wai Yim, Asma Ben Abacha, Yujuan Fu, Zhaoyi Sun, Meliha Yetisgen, Fei Xia. 1456-1462 [doi]
• IRLab@IIT_BHU at MEDIQA-MAGIC 2024: Medical Question Answering using Classification modelArvind Agrawal, Sukomal Pal. 1463-1473 [doi]
• SSN-MLRG at Text to Picto 2024 : A BERT-Based Approach for Mapping French Sentences to Pictogram TermsBhavana Anand, Themozhi J, Shreyas Sai R, Charumathi P, Mirnalinee Tt. 1474-1479 [doi]
• AI Multimedia Lab at ImageCLEFmedical GANs 2024: Deep Learning Approaches for Analyzing Synthetic Medical ImagesAlexandra-Georgiana Andrei, Mihai Gabriel Constantin, Mihai Dogariu, Bogdan Ionescu. 1480-1489 [doi]
• Medical Image Captioning using CUI-based Classification and Feature SimilarityMasaki Aono, Tetsuya Asakawa, Kazuki Shimizu, Kei Nomura. 1490-1499 [doi]
• KDE-med-lab at ImageCLEF 2024: Identify data and detect generative models using CNN by lung segmentation based on U-netTetsuya Asakawa, Kazuki Shimizu, Kei Nomura, Masaki Aono. 1500-1507 [doi]
• Concept Detection and Caption Prediction of Radiology Images Using Convolutional Neural NetworksPrabavathy Balasundaram, Karthikeyan Swaminathan, Oviasree Sampath, Pradeep Km. 1508-1516 [doi]
• Evaluation of the Privacy of Images Generated by ImageCLEFmedical GANs 2024 Based on Similarity MethodsShitong Cao, Xiaobing Zhou. 1517-1524 [doi]
• VisualT5: Multitasking Caption and Concept Prediction with Pre-trained ViT, T5 and Customized Spatial Attention in Radiological ImagesDiedre Carmo, Letícia Rittner, Roberto de Alencar Lotufo. 1525-1532 [doi]
• MMCP Team at ImageCLEFmed MEDVQA-GI 2024 Task: Diffusion Models for Text-to-Image Generation of Colonoscopy ImagesMikhail Chaichuk, Elena Tutubalina. 1533-1544 [doi]
• VisionQAries at MEDIQA-MAGIC 2024: Small Vision Language Models for Dermatological DiagnosisPatrycja Cieplicka, Julia Klos, Maciej Morawski. 1545-1551 [doi]
• SSNMLRGKSR at ImageCLEFmedical Caption 2024: Medical Concept Detection using DenseNet-121 with MultiLabelBinarizerRamyaa Dhinagaran, Sheerin Sitara Noor Mohamed, Kavitha Srinivasan. 1552-1559 [doi]
• Advancing AI-Powered Medical Image Synthesis: Insights from MedVQA-GI Challenge Using CLIP, Fine-Tuned Stable Diffusion, and Dream-Booth + LoRAOjonugwa Oluwafemi Ejiga Peter, Md Mahmudur Rahman 0003, Fahmi Khalifa. 1560-1578 [doi]
• Text-To-Picto using Lexical SimplificationAbbhinav Elliah, Ananth Narayanan P, Bhuvan S, Palaniappan Mirunalini. 1579-1584 [doi]
• Fingerprint Identification of Generative Models Using a MultiFormer Ensemble ApproachMd. Ismail Siddiqi Emon, Mahmudul Hoque, Md. Rakibul Hasan, Fahmi Khalifa, Md Mahmudur Rahman 0003. 1585-1598 [doi]
• YuanAI at MEDIQA-MAGIC 2024: Improving Medical VQA Performance through Parameter-Efficient Fine-TuningHsian-Hong Fu, Hsien-Cheng Huang. 1599-1607 [doi]
• KDE Lab at ImageCLEFmedical GANs 2024Shota Fukuyama, Tetsuya Asakawa, Kazuki Shimizu, Kei Nomura, Masaki Aono. 1608-1612 [doi]
• Detecting Training Data and Generative Model Fingerprints in Synthetic CT Scans Using Machine LearningAmilcare Gentili. 1613-1618 [doi]
• Medical Image Interpretation with Large Multimodal ModelsMahmudul Hoque, Md. Rakibul Hasan, Md. Ismail Siddiqi Emon, Fahmi Khalifa, Md Mahmudur Rahman 0003. 1619-1639 [doi]
• Identifying Training Data "Fingerprints" Using Border Enhancing Image Processing Methods and Their EnsembleKoki Inoue, Tetsuya Asakawa, Kazuki Shimizu, Kei Nomura, Masaki Aono. 1640-1644 [doi]
• Predicting Captions and Detecting Concepts for Medical Images: Contributions of the DBS-HHU Team to ImageCLEFmedical Caption 2024Heiko Kauschke, Kirill Bogomasov, Stefan Conrad 0001. 1645-1655 [doi]
• A Transformer Based Approach for Text-to-Picto GenerationAvaneesh Koushik, Jithu Morrison S, Palaniappan Mirunalini, Jothir Aditya R. K. 1656-1661 [doi]
• Analyzing Generated Images using Machine LearningDiana Miranda, Aparna Rane, Bipin Naik. 1662-1667 [doi]
• Automatic Medical Concept Detection on Images: Dividing the Task into Smaller OnesAxel Moncloa-Muro, Graciela Ramírez Alonso, Fernando Martínez Reyes. 1668-1680 [doi]
• DS@BioMed at ImageCLEFmedical Caption 2024: Enhanced Attention Mechanisms in Medical Caption Generation through Concept Detection IntegrationNhi Ngoc-Yen Nguyen, Huy Le Tu, Phuong Dieu Nguyen, Tan Nhat Do, Triet Minh Thai, Thien B. Nguyen-Tat. 1681-1694 [doi]
• UIT-DarkCow team at ImageCLEFmedical Caption 2024: Diagnostic Captioning for Radiology Images Efficiency with Transformer ModelsQuan Van Nguyen, Huy Quang Pham, Dan Quang Tran, Thang Kien-Bao Nguyen, Nhat-Hao Nguyen-Dang, Thien B. Nguyen-Tat. 1695-1710 [doi]
• UIT-2Q2T at ImageCLEFmedical 2024 Caption: Multimodal medical image captioning using Bootstrapping Language-Image Pre-trainingThien V. Phan, Trinh K. Nguyen, Quang A. D. D. Hoang, Quan T. Phan, Thien B. Nguyen-Tat. 1711-1719 [doi]
• Leveraging Diverse CNN Architectures for Medical Image Captioning: DenseNet-121, MobileNetV2, and ResNet-50 in ImageCLEF 2024Sriram Ram, Shashaank Vinoth, Rahul Natesh Gopalakrishnan, Aastick Amirteswar Balakumar, Lekshmi Kalinathan, Thomas Abraham Joseph Velankanni. 1720-1728 [doi]
• AUEB NLP Group at ImageCLEFmedical Caption 2024Marina Samprovalaki, Anna Chatzipapadopoulou, Georgios Moschovis, Foivos Charalampakos, Panagiotis Kaliosis, John Pavlopoulos, Ion Androutsopoulos. 1729-1745 [doi]
• Classification of Real and Generated Images Based on Feature SimilarityHuihui Tang, Hancheng Wang, Jining Chen. 1746-1754 [doi]
• GAN-Amis: Evaluating Clustering of GAN-Generated Medical Images Using Custom and Pre-trained CNN Architectures to Identify GAN FingerprintsAman Upganlawar, Aarti Lad, Arnav Desai. 1755-1762 [doi]
• PCLmed: Champion Solution for ImageCLEFmedical 2024 Caption Prediction Challenge via Medical Vision-Language Foundation ModelsBang Yang, Yue Yu, Yuexian Zou, Tong Zhang. 1763-1774 [doi]
• Overview of the CLEF 2024 JOKER Task 1: Humour-aware Information RetrievalLiana Ermakova, Anne-Gwenn Bosser, Tristan Miller, Adam Jatowt. 1775-1785 [doi]
• Overview of the CLEF 2024 JOKER Task 2: Humour Classification According to Genre and TechniqueVictor Manuel Palma-Preciado, Grigori Sidorov, Liana Ermakova, Anne-Gwenn Bosser, Tristan Miller, Adam Jatowt. 1786-1799 [doi]
• Overview of the CLEF 2024 JOKER Task 3: Translate puns from English to FrenchLiana Ermakova, Anne-Gwenn Bosser, Tristan Miller, Adam Jatowt. 1800-1810 [doi]
• Overview of the CLEF 2024 JOKER Task 3: Translate puns from English to FrenchLiana Ermakova, Anne-Gwenn Bosser, Tristan Miller, Adam Jatowt. 1800-1810 [doi]
• Overview of the CLEF 2024 JOKER Task 3: Translate puns from English to FrenchLiana Ermakova, Anne-Gwenn Bosser, Tristan Miller, Adam Jatowt. 1800-1810 [doi]
• JOKER Track @ CLEF 2024: the Jokesters' approaches for retrieving, classifying, and translating wordplayHarouna Baguian, Huynh Nina Ashley. 1811-1817 [doi]
• University of Split and University of Malta (Team AB&DPV) at the CLEF 2024 JOKER Track: From 'LOL' to 'MDR' Using Artificial Intelligence Models to Retrieve and Translate PunsAntonia Bartulovic, Dóra Paula Váradi. 1818-1825 [doi]
• PunDerstand @ CLEF JOKER 2024: Who's Laughing Now? Humor Classification by Genre & TechniqueRyan Rony Dsilva, Nidhi Bhardwaj. 1826-1833 [doi]
• Working Notes of CLEF 2024: Effective Humor Analysis and TranslationRegina Elagina, Petra Vucic. 1834-1840 [doi]
• ORPAILLEUR & SyNaLP at CLEF 2024 Task 2: Good Old Cross Validation for Large Language Models Yields the Best Humorous DetectionPierre Epron, Gaël Guibon, Miguel Couceiro. 1841-1856 [doi]
• CLEF 2024 Joker Task 1: Exploring Pun Detection Using The T5 Transformer ModelArina Gepalova, Adrian-Gabriel Chifu, Sébastien Fournier. 1857-1861 [doi]
• Thinking, Fast and Slow: From the Speed of FastText to the Depth of Retrieval Augmented Large Language Models For Humour ClassificationJana Viktória Kováciková, Marek Suppa. 1862-1867 [doi]
• CLEF 2024 JOKER Tasks 1-3: Humour identification and classificationRowan Mann, Tomislav Mikulandric. 1868-1875 [doi]
• CLEF 2024 JOKER Task 2 : Using RoBERTa and Bert-uncased for Humour Classification According to Genre and TechniqueSarvesh Narayanan, Jayasimman J, Shiva Ganesh V. 1876-1879 [doi]
• NLPalma Joker 2024: Yet, no Humor with Humorousness - Task 2 Humour Classification According to Genre and TechniqueVictor Manuel Palma-Preciado, Carolina Palma Preciado, Grigori Sidorov. 1880-1888 [doi]
• Comparative Evaluation of Humour Translation from English to Spanish: A Study with BLOOM and GoogletransOlga Popova. 1889-1894 [doi]
• Vayam Solve Kurmaha @ CLEF 2024: Task 2: Humor Classification according to Genre and Technique using BERT Embeddings and TransformersDhannya S. M, Lakshmi Priya S, Shreedevi Seluka Balaji, Sai Nikitha N. S. R, Shwetha S, Surabhi Kamath, Srinidhi Lakshmi Narayanan. 1895-1901 [doi]
• CLEF 2024 JOKER Task 2: Using BERT and Random Forest Classifier for Humor Classification According to Genre and TechniqueM. Saipranav, Jaswanth Sridharan, Gautham Narayan G, Angel Deborah S, Rajalakshmi Sivanaiah, Mirnalinee T. T, Samyuktaa Sivakumar. 1902-1908 [doi]
• University of Amsterdam at the CLEF 2024 Joker TrackEmma Schuurman, Mick Cazemier, Luc Buijs, Jaap Kamps. 1909-1922 [doi]
• Team Humour Insights at JOKER 2024 Task 2: Humour Classification According To Genre And TechniqueRakshith Subramanian, Vaishnavi S, B. Bharathi. 1923-1932 [doi]
• Humour Classification by Fine-tuning LLMs: CYUT at CLEF 2024 JOKER Lab Subtask Humour Classification According to Genre and TechniqueShih-Hung Wu, Yu-Feng Huang, Tsz-Yeung Lau. 1933-1947 [doi]
• Overview of BirdCLEF 2024: Acoustic identification of under-studied bird species in the Western GhatsStefan Kahl, Tom Denton, Holger Klinck, Vijay Ramesh, Viral Joshi, Meghana Srivathsa, Akshay Anand, Chiti Arvind, Harikrishnan Cp, Suyash Sawant, Robin Vv, Hervé Glotin, Hervé Goëau, Willem-Pier Vellinga, Robert Planqué, Alexis Joly. 1948-1957 [doi]
• Overview of FungiCLEF 2024: Revisiting Fungi Species Recognition Beyond 0-1 CostLukás Picek, Milan Sulc, Jirí Matas. 1958-1965 [doi]
• Overview of GeoLifeCLEF 2024: Species Composition Prediction with High Spatial Resolution at Continental Scale using Remote SensingLukás Picek, Christophe Botella, Maximilien Servajean, César Leblanc, Rémi Palard, Théo Larcher, Benjamin Deneu, Diego Marcos, Joaquim Estopinan, Pierre Bonnet, Alexis Joly. 1966-1977 [doi]
• Overview of PlantCLEF 2024: Multi-species Plant Identification in Vegetation Plot ImagesHervé Goëau, Vincent Espitalier, Pierre Bonnet, Alexis Joly. 1978-1988 [doi]
• Overview of SnakeCLEF 2024: Revisiting Snake Species Identification in Medically Important ScenariosLukás Picek, Marek Hrúz, Andrew M. Durso. 1989-2000 [doi]
• Combining Present-Only and Present-Absent Data with Pseudo-Label Generation for Species Distribution ModelingYi-Chia Chen, Tai Peng, Wei-Hua Li, Chu-Song Chen. 2001-2008 [doi]
• Multi-modal Feature Fusion Networks for GeoLifeCLEF 2024Zehua Cheng, Wei Dai, Jiahao Sun. 2009-2015 [doi]
• Fine-Grained Classification for Poisonous Fungi Identification with Transfer LearningChristopher Chiu, Maximilian Heil, Teresa Kim, Anthony Miyaguchi. 2016-2026 [doi]
• Patch-wise Inference using Pre-trained Vision Transformers: NEUON Submission to PlantCLEF 2024Sophia Chulif, Hamza Ahmed Ishrat, Yang Loong Chang, Sue Han Lee. 2027-2043 [doi]
• Methods for Training Convolutional Neural Networks to Identify Bird Species in Complex Soundscape RecordingsKonstantin Dmitriev. 2044-2052 [doi]
• Generalizable Training Techniques for Fine-Grained Long-Tailed Image Recognition: Transferring Methods Optimized for FungiCLEF 2024 to SnakeCLEF 2024Jack N. Etheredge. 2053-2065 [doi]
• OpenWGAN-GP for Fine-Grained Open-Set Fungi ClassificationJack N. Etheredge. 2066-2082 [doi]
• OpenWGAN-GP for Fine-Grained Open-Set Fungi ClassificationJack N. Etheredge. 2066-2082 [doi]
• OpenWGAN-GP for Fine-Grained Open-Set Fungi ClassificationJack N. Etheredge. 2066-2082 [doi]
• Utilising DINOv2 for Domain Adaptation in Vegetation Plot AnalysisStephen Foy, Simon McLoughlin. 2083-2092 [doi]
• Multi-Label Plant Species Classification with Self-Supervised Vision TransformersMurilo Gustineli, Anthony Miyaguchi, Ian Stalter. 2093-2102 [doi]
• Domain Adaption for Birdcall Recognition: Progressive Knowledge Distillation with Semi-Supervised and Self-Supervised Soundscape LabelingLihang Hong. 2103-2109 [doi]
• Improving Bird Recognition using Pseudo-Labeled Recordings from the Target LocationMario Lasseck. 2110-2118 [doi]
• Tighnari: Multi-modal Plant Species Prediction Based on Hierarchical Cross-Attention Using Graph-Based and Vision Backbone-Extracted FeaturesHaixu Liu, Penghao Jiang, Zerui Tao, Muyan Wan, Qiuzhuang Sun. 2119-2143 [doi]
• Tile Compression and Embeddings for Multi-Label Classification in GeoLifeCLEF 2024Anthony Miyaguchi, Patcharapong Aphiwetsa, Mark McDuffie. 2144-2157 [doi]
• Transfer Learning with Pseudo Multi-Label Birdcall Classification for DS@GT BirdCLEF 2024Anthony Miyaguchi, Adrian Cheung, Murilo Gustineli, Ashley Kim. 2158-2169 [doi]
• Transfer Learning with Self-Supervised Vision Transformers for Snake IdentificationAnthony Miyaguchi, Murilo Gustineli, Austin Fischer, Ryan Lundqvist. 2170-2177 [doi]
• Bird-Species Audio Identification, Ensembling of EfficientNet-B0 and Pre-trained EfficientNet-B1 modelAaditya Porwal. 2178-2187 [doi]
• Exploring Biodiversity: A Multi-Model Approach to Multi-Label Plant Species PredictionDarren Rawlings, Tim Chopard. 2188-2200 [doi]
• TUC Media Computing at BirdCLEF 2024: Improving Birdsong Classification Through Single Learning ModelsArunodhayan Sampath Kumar, Tobias Schlosser, Danny Kowerko. 2201-2208 [doi]
• Do Not Lose to Losses for SnakeCLEF2024Matej Sieber, Tomas Zelezný. 2209-2214 [doi]
• Multimodal networks for Species Distribution ModelingAman R. Syayfetdinov. 2215-2222 [doi]
• Say No to the Poisonous Fungi: An Effective Strategy for Reducing 0-1 Cost in FungiCLEF2024Bao-Feng Tan, Yang-Yang Li, Peng Wang 0023, Lin Zhao, Xiu-Shen Wei. 2223-2233 [doi]
• Multibranch Co-training to Mine Venomous Feature Representation: A Solution to SnakeCLEF2024Peng Wang 0023, Yangyang Li, Bao-Feng Tan, Yi-Chao Zhou, Yong Li, Xiu-Shen Wei. 2234-2243 [doi]
• Addressing the Challenges of Domain Shift in Bird Call Classification for BirdCLEF 2024Emiel Witting, Hugo de Heer, Jeffrey Lim, Cahit Tolga Kopar, Kristóf Sándor. 2244-2259 [doi]
• Poison-Aware Open-Set Fungi Classification: Reducing the Risk of Poisonous ConfusionStefan Wolf, Philipp Thelen, Jürgen Beyerer. 2260-2266 [doi]
• Extended Overview of the CLEF 2024 LongEval Lab on Longitudinal Evaluation of Model PerformanceRabab Alkhalifa, Hsuvas Borkakoty, Romain Deveaud, Alaa El-Ebshihy, Luis Espinosa Anke, Tobias Fink, Petra Galuscáková, Gabriela González Sáez, Lorraine Goeuriot, David Iommi, Maria Liakata, Harish Tayyar Madabushi, Pablo Medina-Alias, Philippe Mulhem, Florina Piroi, Martin Popel, Arkaitz Zubiaga. 2267-2289 [doi]
• SEUPD@CLEF: Team Kalu on improving Search Engine Performance with Query Expansion and Re-Ranking ApproachKimia Abedini, Arwa Fahoud, Akan Akysh, Nicola Ferro 0001. 2290-2303 [doi]
• Team OpenWebSearch at CLEF 2024: LongEvalDaria Alexander, Maik Fröbe, Gijs Hendriksen, Ferdinand Schlatt, Matthias Hagen, Djoerd Hiemstra, Martin Potthast, Arjen P. de Vries. 2304-2313 [doi]
• SEUPD@CLEF: Team DAM on Reranking Using Sentence EmbeddersAlberto Basaglia, Andrea Stocco, Milica Popovic, Nicola Ferro 0001. 2314-2335 [doi]
• SEUPD@CLEF: Team MOUSE on Enhancing Search Engines Effectiveness with Large Language ModelsLorenzo Cazzador, Francesco Luigi De Faveri, Filippo Franceschini, Lorenzo Pamio, Samuel Piron, Nicola Ferro 0001. 2336-2355 [doi]
• SEUPD@CLEF: Team IRIS on Temporal Evolution of Query Expansion and Rank Fusion Techniques Applied to Cross-Encoder Re-RankersFilippo Galli, Manuel Rigobello, Michela Schibuola, Riccardo Zuech, Nicola Ferro 0001. 2356-2383 [doi]
• Team Galápagos Tortoise at LongEval 2024: Neural Re-Ranking and Rank Fusion for Temporal StabilityMarlene Gründel, Malte Weber, Johannes Franke, Jan Heinrich Merker. 2384-2395 [doi]
• Leveraging Prior Relevance Signals in Web SearchJüri Keller, Timo Breuer 0002, Philipp Schaer. 2396-2406 [doi]
• Analyzing the Effectiveness of Listwise Reranking with Positional Invariance on Temporal GeneralizabilitySoyoung Yoon, Jongyoon Kim, Seung-won Hwang. 2407-2423 [doi]
• Overview of the Multi-Author Writing Style Analysis Task at PAN 2024Eva Zangerle, Maximilian Mayerl, Martin Potthast, Benno Stein 0001. 2424-2431 [doi]
• Overview of the Multilingual Text Detoxification Task at PAN 2024Daryna Dementieva, Daniil Moskovskiy, Nikolay Babakov, Abinew Ali Ayele, Naquee Rizwan, Florian Schneider 0001, Xintong Wang, Seid Muhie Yimam, Dmitry Ustalov, Elisei Stakovskii, Alisa Smirnova, Ashraf Elnagar, Animesh Mukherjee 0001, Alexander Panchenko. 2432-2461 [doi]
• Overview of the Oppositional Thinking Analysis PAN Task at CLEF 2024Damir Korencic, Berta Chulvi, Xavier Bonet Casals, Mariona Taulé, Paolo Rosso, Francisco Rangel. 2462-2485 [doi]
• Overview of the "Voight-Kampff" Generative AI Authorship Verification Task at PAN and ELOQUENT 2024Janek Bevendorff, Matti Wiegmann, Jussi Karlgren, Luise Dürlich, Evangelia Gogoulou, Aarne Talman, Efstathios Stamatatos, Martin Potthast, Benno Stein 0001. 2486-2506 [doi]
• Team Deloitte at PAN: A Novel Approach for Generative AI Text DetectionHarika Abburi, Nirmala Pudota, Balaji Veeramani, Edward Bowen, Sanmitra Bhattacharya. 2507-2510 [doi]
• Detection of Conspiracy vs. Critical Narratives and Their Elements using NLPAish Albladi, Cheryl Seals. 2511-2520 [doi]
• Oppositional Thinking Analysis: Conspiracy Theories vs Critical Thinking NarrativesPrabavathy Balasundaram, Karthikeyan Swaminathan, Oviasree Sampath, Pradeep Km. 2521-2526 [doi]
• Oppositional Thinking Analysis: Conspiracy Theories vs Critical Thinking NarrativesPrabavathy Balasundaram, Karthikeyan Swaminathan, Oviasree Sampath, Pradeep Km. 2521-2526 [doi]
• Oppositional Thinking Analysis: Conspiracy Theories vs Critical Thinking NarrativesPrabavathy Balasundaram, Karthikeyan Swaminathan, Oviasree Sampath, Pradeep Km. 2521-2526 [doi]
• Team ap-team at PAN: LLM Adapters for Various DatasetsGalina Boeva, German Gritsai, Andrey Grabovoy. 2527-2535 [doi]
• Enhancing Human-Machine Authorship Discrimination in Generative AI Verification Task with BERT and Augmented DataHaojie Cao, Zhongyuan Han, Jingyan Ye, Biao Liu, Yong Han. 2536-2540 [doi]
• Integrating Dual BERT Models and Causal Language Models for Enhanced Detection of Machine-Generated TextsJitong Chen, Leilei Kong. 2541-2546 [doi]
• Team Chen at PAN: Integrating R-Drop and Pre-trained Language Model for Multi-author Writing Style AnalysisZhaotian Chen, Yong Han, Yusheng Yi. 2547-2553 [doi]
• DSVS at PAN 2024: Ensemble Approach of Transformer-based Language Models for Analyzing Conspiracy Theories Against Critical Thinking NarrativesSergio Damián, Brian Herrera, David Vázquez, Hiram Calvo, Edgardo Manuel Felipe Riverón, Cornelio Yáñez-Márquez. 2554-2565 [doi]
• A Study on NLP Model Ensembles and Data Augmentation Techniques for Separating Critical Thinking from Conspiracy Theories in English TextsIñaki del Campo Sánchez-Hermosilla, Ángel Panizo-LLedot, David Camacho. 2566-2571 [doi]
• Automatic Identification of Conspiracy Theories Using BERTDaniel Yacob Espinosa, Grigori Sidorov, Eusebio Ricárdez Vázquez. 2572-2575 [doi]
• Linguistic_Hygenist at PAN 2024 TextDetox: HybridDetox - A Combination of Supervised and Unsupervised Methods for Effective Multilingual Text DetoxificationSusmita Gangopadhyay, M. Taimoor Khan, Hajira Jabeen. 2576-2584 [doi]
• BLGAV：Generative AI Author Verification Model Based on BERT and BiLSTMLinjiu Guo, Wenyin Yang, Li Ma 0011, Jinli Ruan. 2585-2592 [doi]
• A Machine-Generated Text Detection Model Based on Text Multi-Feature FusionMingcan Guo, Zhongyuan Han, Haoyang Chen, Jiangao Peng. 2593-2602 [doi]
• Detection of conspiracy-related messages in Telegram with anonymized named entitiesJuan Gómez-Romero, Santiago González-Silot, Andrés Montoro-Montarroso, Miguel Molina-Solana, Eugenio Martínez-Cámara. 2603-2612 [doi]
• An Oppositional Thinking Analysis Method Using BERT-based Model with BiGRUQingbiao Hu, Zhongyuan Han, Jiangao Peng, Mingcan Guo, Chang Liu. 2613-2618 [doi]
• Author Authentication of Generative AI Based on Bert by Regularization MethodBaijian Huang, Changle Zhong, Kai Yan, Yong Han. 2619-2626 [doi]
• Conspiracy Theory Text Classification Based on CT-BERT and BETO ModelsJiahong Huang, Zhongyuan Han, Ruihao Zhu, Mingcan Guo, Kaiyin Sun. 2627-2631 [doi]
• Generative AI Authorship Verification Of Tri-Sentence Analysis Base On The Bert ModelJijie Huang, Yang Chen, Man Luo, Yonglan Li. 2632-2637 [doi]
• Generative AI Authorship Verification Based on Contrastive Learning and Domain AdaptationKaicheng Huang, Haoliang Qi, Kai Yan. 2638-2644 [doi]
• Authorial Language Models For AI Authorship VerificationWeihang Huang, Jack Grieve. 2645-2652 [doi]
• Team Text Understanding and Analysis at PAN: Utilizing BERT Series Pre-training Model for Multi-Author Writing Style AnalysisYingzhou Huang, Leilei Kong. 2653-2657 [doi]
• DeBERTa-v3 with R-Drop regularization for Multi-Author Writing Style AnalysisZhijian Huang, Leilei Kong. 2658-2664 [doi]
• DeBERTa-v3 with R-Drop regularization for Multi-Author Writing Style AnalysisZhijian Huang, Leilei Kong. 2658-2664 [doi]
• DeBERTa-v3 with R-Drop regularization for Multi-Author Writing Style AnalysisZhijian Huang, Leilei Kong. 2658-2664 [doi]
• Small Language Models and Large Language Models in Oppositional thinking analysis: Capabilities, Biases and ChallengesÁlvaro Huertas-García, Carlos Martí-González, Javier Muñoz, Enrique De Miguel Ambite. 2665-2675 [doi]
• Team karami-sh at PAN: Transformer-based Ensemble Learning for Multi-Author Writing Style AnalysisMohammad Karami Sheykhlan, Saleh Kheiri Abdoljabbar, Mona Nouri Mahmoudabad. 2676-2681 [doi]
• Team karami-kheiri at PAN: Enhancing Machine-Generated Text Detection with Ensemble Learning Based on Transformer ModelsMohammad Karami Sheykhlan, Saleh Kheiri Abdoljabbar, Mona Nouri Mahmoudabad. 2682-2687 [doi]
• Team karami-kheiri at PAN: Enhancing Machine-Generated Text Detection with Ensemble Learning Based on Transformer ModelsMohammad Karami Sheykhlan, Saleh Kheiri Abdoljabbar, Mona Nouri Mahmoudabad. 2682-2687 [doi]
• Team karami-kheiri at PAN: Enhancing Machine-Generated Text Detection with Ensemble Learning Based on Transformer ModelsMohammad Karami Sheykhlan, Saleh Kheiri Abdoljabbar, Mona Nouri Mahmoudabad. 2682-2687 [doi]
• Team Gladiators at PAN: Improving Author Identification: A Comparative Analysis of Pre-Trained Transformers for Multi-Author ClassificationAreeb Adnan Khan, Mohit Rai, Khuzaima Ali Khan, Syed Jahania Shah, Faisal Alvi, Abdul-Samad. 2688-2694 [doi]
• Team OpenFact at PAN 2024: Fine-Tuning BERT Models with Stylometric EnhancementsEwelina Ksiezniak, Krzysztof Wecel, Marcin Sawinski. 2695-2703 [doi]
• Generative AI Authorship Verification based on ChatGLMHaotian Lei, Xiangyu Liu, Guo Niu, Yan Zhou, Yuexia Zhou. 2704-2709 [doi]
• Fine-Tuned Reasoning for Writing Style AnalysisXiaofeng Liang, Fanzhi Zeng, Yan Zhou, Xiangyu Liu, Yuexia Zhou. 2710-2715 [doi]
• NYCU-NLP at PAN 2024: Integrating Transformers with Similarity Adjustments for Multi-Author Writing Style AnalysisTzu-Mi Lin, Yu-Hsin Wu, Lung-Hao Lee. 2716-2721 [doi]
• Voight-Kampff Generative AI Authorship Verification Based on T5Zhaojian Lin, Fanzhi Zeng, Yan Zhou, Xiangyu Liu, Yuexia Zhou. 2722-2727 [doi]
• A Verifying Generative Text Authorship Model With Regularized DropoutZijie Lin, Zhongyuan Han, Leilei Kong, Miaoling Chen, Shuyi Zhang, Jiangao Peng, Kaiyin Sun. 2728-2734 [doi]
• Team nlpln at PAN 2024: An Approach to Classifying Conspiratorial and Critical Public Health Narratives With Zero-shot and Sequence LabelingBiao Liu, Zhongyuan Han, Haojie Cao. 2735-2743 [doi]
• Team Liuc0757 at PAN: A Writing Style Embedding Method Based on Contrastive Learning for Multi-Author Writing Style AnalysisChang Liu, Zhongyuan Han, Haoyang Chen, Qingbiao Hu. 2744-2749 [doi]
• Team foshan-university-of-guangdong at PAN: Adaptive Entropy-Based Stability-Plasticity for Multi-Author Writing Style AnalysisXurong Liu, Hui Chen, Jiajun Lv. 2750-2754 [doi]
• AI Text Detection Method Based on Perplexity Features with Strided Sliding WindowXurong Liu, Leilei Kong. 2755-2760 [doi]
• BaselineAvengers at PAN 2024: Often-Forgotten Baselines for LLM-Generated Text DetectionLudwig Lorenz, Funda Zeynep Aygüler, Ferdinand Schlatt, Nailia Mirzakhmedova. 2761-2768 [doi]
• Multilingual Text Detoxification Using Google Cloud Translation and Post-ProcessingZhongyu Luo, Man Luo, Aiguo Wang. 2769-2774 [doi]
• Meta-Contrastive Learning for Generative AI Authorship VerificationJiajun Lv, Yong Han, Leilei Kong. 2775-2780 [doi]
• Team fosu-stu at PAN: Supervised Fine-Tuning of Large Language Models for Multi Author Writing Style AnalysisJiajun Lv, Yusheng Yi, Haoliang Qi. 2781-2786 [doi]
• Binary Battle: Leveraging Machine Learning and Transfer Learning Models to Distinguish between Conspiracy Theories and Critical ThinkingSidharth Mahesh, Sonith Divakaran, Kavya Girish, Hosahalli Lakshmaiah Shashirekha. 2787-2796 [doi]
• IUCL at PAN 2024: Using Data Augmentation for Conspiracy Theory DetectionShrirang Mhalgi, Srikar Kashyap Pulipaka, Sandra Kübler. 2797-2806 [doi]
• Team aida at PAN: Ensembling Normalized Log ProbabilitiesPablo Miralles, Alejandro Martín, David Camacho. 2807-2813 [doi]
• Marsan at PAN 2024 TextDetox: ToxiCleanse RL, Paving the Way for Toxicity-Free Online DiscourseMaryam Najafi, Ehsan Tavan, Simon Colreavy. 2814-2823 [doi]
• AI Authorship Verification: An Ensembled ApproachBenjamin Ostrower, Jacob Wessell, Abhinav Bindal. 2824-2828 [doi]
• A Multilingual Text Detoxification Method Based on Few-shot Learning and CO-STAR FrameworkJiangao Peng, Zhongyuan Han, Huan Zhang, Jingyan Ye, Chang Liu, Biao Liu, Mingcan Guo, Haoyang Chen, Zijie Lin, Yujiao Tang. 2829-2837 [doi]
• RoBERTa and Bi-LSTM for Human vs AI Generated Text DetectionPanagiotis Petropoulos, Vasilis Petropoulos. 2838-2842 [doi]
• SomethingAwful at PAN 2024 TextDetox: Uncensored Llama 3 Helps to Censor BetterSergey Pletenev. 2843-2851 [doi]
• PAN 2024 Multilingual TextDetox: Exploring Cross-lingual Transfer Using Large Language ModelsVitaly Protasov. 2852-2857 [doi]
• A Model Fusion Approach for Generative AI Authorship VerificationRui Qin, Haoliang Qi, Yusheng Yi. 2858-2865 [doi]
• SmurfCat at PAN 2024 TextDetox: Alignment of Multilingual Transformers for Text DetoxificationElisei Rykov, Konstantin Zaytsev, Ivan Anisimov, Alexandr Voronin. 2866-2871 [doi]
• Towards a Computational Framework for Distinguishing Critical and Conspiratorial Texts by Elaborating on the Context and Argumentation with LLMsAriana Sahitaj, Premtim Sahitaj, Salar Mohtaj, Sebastian Möller 0001, Vera Schmitt. 2872-2880 [doi]
• Team riyahsanjesh at PAN: Multi-feature with CNN and Bi-LSTM Neural Network Approach to Style Change DetectionRiya Sanjesh, Alamelu Mangai. 2881-2885 [doi]
• BCAV: A Generative AI Author Verification Model Based on the Integration of Bert and CNNGuihong Sun, Wenyin Yang, Li Ma. 2886-2891 [doi]
• PAN 2024 Multilingual TextDetox: Exploring Different Regimes For Synthetic Data Training For Multilingual Text DetoxificationNikita Sushko. 2892-2900 [doi]
• MarSan at PAN: BinocularsLLM, Fusing Binoculars' Insight with the Proficiency of Large Language Models for Machine-Generated Text DetectionEhsan Tavan, Maryam Najafi. 2901-2912 [doi]
• Conspiracy vs Critical Thinking Using an Ensemble of Transformers with Data Augmentation TechniquesAngelo Maximilian Tulbure, Mariona Coll Ardanuy. 2913-2922 [doi]
• Team iimasnlp at PAN: Leveraging Graph Neural Networks and Large Language Models for Generative AI Authorship VerificationAndric Valdez-Valenzuela, Helena Gómez-Adorno. 2923-2929 [doi]
• SINAI at PAN 2024 Oppositional Thinking Analysis: Exploring the Fine-Tuning Performance of Large Language ModelsMaría Estrella Vallecillo Rodríguez, María-Teresa Martín Valdivia, Arturo Montejo Ráez. 2930-2940 [doi]
• SINAI at PAN 2024 TextDetox: Application of Chain of Thought with Self-Consistency Strategy in Large Language Models for Multilingual Text DetoxificationMaría Estrella Vallecillo Rodríguez, Arturo Montejo Ráez, María-Teresa Martín Valdivia. 2941-2950 [doi]
• SINAI at PAN 2024 TextDetox: Application of Chain of Thought with Self-Consistency Strategy in Large Language Models for Multilingual Text DetoxificationMaría Estrella Vallecillo Rodríguez, Arturo Montejo Ráez, María-Teresa Martín Valdivia. 2941-2950 [doi]
• SINAI at PAN 2024 TextDetox: Application of Chain of Thought with Self-Consistency Strategy in Large Language Models for Multilingual Text DetoxificationMaría Estrella Vallecillo Rodríguez, Arturo Montejo Ráez, María-Teresa Martín Valdivia. 2941-2950 [doi]
• Team baker at PAN: Enhancing Writing Style Change Detection with Virtual SoftmaxBingpei Wu, Yong Han, Kai Yan, Haoliang Qi. 2951-2955 [doi]
• Team lm-detector at PAN: Can NLI be an Appropriate Approach to Machine-Generated Text DetectionGuojun Wu, Qinghao Guan. 2956-2962 [doi]
• Team bingezzzleep at PAN: A Writing Style Change Analysis Model Based on RoBERTa Encoding and Contrastive Learning for Multi-Author Writing Style AnalysisQida Wu, Leilei Kong, Zhanhong Ye. 2963-2968 [doi]
• BertT: A Hybrid Neural Network Model for Generative AI Authorship VerificationZepeng Wu, Wenyin Yang, Li Ma, Zikai Zhao. 2969-2975 [doi]
• Team cnlp-nits-pp at PAN: Leveraging BERT for Accurate Authorship Verification: A Novel Approach to Textual AttributionAnnepaka Yadagiri, Dimpal Kalita, Abhishek Ranjan, Ashish Kumar Bostan, Parthib Toppo, Partha Pakray. 2976-2987 [doi]
• Continual Transfer Learning with Progress Prompt for Multi-Author Writing Style AnalysisZhanhong Ye, Yutong Zhong, Chen Huang, Leilei Kong. 2988-2994 [doi]
• Token Prediction as Implicit Classification for Generative AI Authorship VerificationZhanhong Ye, Yutong Zhong, Zhen Huang, Leilei Kong. 2995-3001 [doi]
• Token Prediction as Implicit Classification for Generative AI Authorship VerificationZhanhong Ye, Yutong Zhong, Zhen Huang, Leilei Kong. 2995-3001 [doi]
• Token Prediction as Implicit Classification for Generative AI Authorship VerificationZhanhong Ye, Yutong Zhong, Zhen Huang, Leilei Kong. 2995-3001 [doi]
• A Conspiracy Theory Text Detection Method based on RoBERTa and XLM-RoBERTa ModelsZhengqiao Zeng, Zhongyuan Han, Jingyan Ye, Yaozu Tan, Haojie Cao, Zengyao Li, Runjin Huang. 3002-3006 [doi]
• AI Authorship Verification Based On Deberta ModelYe Zhu, Leilei Kong. 3007-3011 [doi]
• Conspiracy Theory Detection using Transformers with Multi-task and Multilingual ApproachesLeon Zrnic. 3012-3020 [doi]
• RAG Meets Detox: Enhancing Text Detoxification Using Open Large Language Models with Retrieval Augmented GenerationErik Rehulka, Marek Suppa. 3021-3031 [doi]
• QuantumCLEF 2024: Overview of the Quantum Computing Challenge for Information Retrieval and Recommender Systems at CLEFAndrea Pasin, Maurizio Ferrari Dacrema, Paolo Cremonesi, Nicola Ferro 0001. 3032-3053 [doi]
• Towards a Hyperparameter-Free QUBO Formulation for Feature Selection in IRTiago Almeida, Sérgio Matos. 3054-3063 [doi]
• Team qIIMAS on Task 2 - ClusteringWilliam Alvarez-Giron, Jorge Tellezz-Torres, Javier Tovar-Cortes, Helena Gómez-Adorno. 3064-3074 [doi]
• Team OpenWebSearch at CLEF 2024: QuantumCLEFMaik Fröbe, Daria Alexander, Gijs Hendriksen, Ferdinand Schlatt, Matthias Hagen, Martin Potthast. 3075-3081 [doi]
• Quantum Feature SelectionGersome Shimi, Jerin Mahibha C, Durairaj Thenmozhi. 3082-3086 [doi]
• Quantum Feature SelectionGersome Shimi, Jerin Mahibha C, Durairaj Thenmozhi. 3082-3086 [doi]
• Quantum Feature SelectionGersome Shimi, Jerin Mahibha C, Durairaj Thenmozhi. 3082-3086 [doi]
• NICA at Quantum Computing CLEF Tasks 2024Aylin Naebzadeh, Sauleh Eetemadi. 3087-3095 [doi]
• CRUISE on Quantum Computing for Feature Selection in Recommender SystemsJiayang Niu, Jie Li, Ke Deng, Yongli Ren. 3096-3104 [doi]
• Team QTB on Feature Selection Via Quantum Annealing and Hybrid ModelsEsteban Payares, Edwin Puertas, Juan Carlos Martínez Santos. 3105-3114 [doi]
• Overview of the CLEF 2024 SimpleText Task 1: Retrieve Passages to Include in a Simplified SummaryEric SanJuan, Stéphane Huet, Jaap Kamps, Liana Ermakova. 3115-3128 [doi]
• Overview of the CLEF 2024 SimpleText Task 2: Identify and Explain Difficult ConceptsGiorgio Maria Di Nunzio, Federica Vezzani, Vanessa Bonato, Hosein Azarbonyad, Jaap Kamps, Liana Ermakova. 3129-3146 [doi]
• Overview of the CLEF 2024 SimpleText Task 3: Simplify Scientific TextLiana Ermakova, Valentin Laimé, Helen McCombie, Jaap Kamps. 3147-3162 [doi]
• Overview of the CLEF 2024 SimpleText Task 4: SOTA? Tracking the State-of-the-Art in Scholarly PublicationsJennifer D'Souza 0001, Salomon Kabongo, Hamed Babaei Giglou, Yue Zhang. 3163-3173 [doi]
• Team Sharingans at SimpleText: Fine-tuned LLM based approach to Scientific Text SimplificationSyed Muhammad Ali, Hammad Sajid, Owais Aijaz, Owais Waheed, Faisal Alvi, Abdul-Samad. 3174-3181 [doi]
• University of Amsterdam at the CLEF 2024 SimpleText TrackJan Bakker, Göksenin Yüksel, Jaap Kamps. 3182-3194 [doi]
• University of Split and University of Malta (Team AB&DPV) at the CLEF 2024 SimpleText Track: Scientific Text Made Simpler Through the Use of Artificial IntelligenceAntonia Bartulovic, Dóra Paula Váradi. 3195-3205 [doi]
• University of Split and University of Malta (Team AB&DPV) at the CLEF 2024 SimpleText Track: Scientific Text Made Simpler Through the Use of Artificial IntelligenceAntonia Bartulovic, Dóra Paula Váradi. 3195-3205 [doi]
• University of Split and University of Malta (Team AB&DPV) at the CLEF 2024 SimpleText Track: Scientific Text Made Simpler Through the Use of Artificial IntelligenceAntonia Bartulovic, Dóra Paula Váradi. 3195-3205 [doi]
• Enhancing Scientific Document Simplification through Adaptive Retrieval and Generative ModelsArtemis Çapari, Hosein Azarbonyad, Zubair Afzal, Georgios Tsatsaronis. 3206-3229 [doi]
• UNIPD@SimpleText2024: A Semi-Manual Approach on Prompting ChatGPT for Extracting Terms and Write Terminological DefinitionsGiorgio Maria Di Nunzio, Elena Gallina, Federica Vezzani. 3230-3237 [doi]
• AI Contributions to Simplifying Scientific Discourse in SimpleText 2024Regina Elagina, Petra Vucic. 3238-3245 [doi]
• AI Contributions to Simplifying Scientific Discourse in SimpleText 2024Regina Elagina, Petra Vucic. 3238-3245 [doi]
• AI Contributions to Simplifying Scientific Discourse in SimpleText 2024Regina Elagina, Petra Vucic. 3238-3245 [doi]
• Exploring the Latest LLMs for Leaderboard ExtractionSalomon Kabongo, Jennifer D'Souza 0001, Sören Auer. 3246-3260 [doi]
• AIIR Lab Systems for CLEF 2024 SimpleText: Large Language Models for Text SimplificationNicholas Largey, Reihaneh Maarefdoust, Shea Durgin, Behrooz Mansouri. 3261-3273 [doi]
• CLEF 2024 SimpleText Tasks 1-3: Use of Llama-2 for Text SimplificationRowan Mann, Tomislav Mikulandric. 3274-3283 [doi]
• CLEF 2024 SimpleText Tasks 1-3: Use of Llama-2 for Text SimplificationRowan Mann, Tomislav Mikulandric. 3274-3283 [doi]
• CLEF 2024 SimpleText Tasks 1-3: Use of Llama-2 for Text SimplificationRowan Mann, Tomislav Mikulandric. 3274-3283 [doi]
• UZH Pandas at SimpleText2024: Multi-Prompt Minimum Bayes Risk with Diverse PromptsAndrianos Michail, Pascal Severin Andermatt, Tobias Fankhauser. 3284-3287 [doi]
• SINAI Participation in SimpleText Task 2 at CLEF 2024: Zero-shot Prompting on GPT-4-Turbo for Lexical Complexity PredictionJenny Ortiz-Zambrano, César Espin-Riofrio, Arturo Montejo Ráez. 3288-3299 [doi]
• AMATU@Simpletext2024: Are LLMs Any Good for Scientific Leaderboard Extraction?Moritz Staudinger, Alaa El-Ebshihy, Annisa Maulida Ningtyas, Florina Piroi, Allan Hanbury. 3300-3316 [doi]
• UBO NLP Report on the SimpleText track at CLEF 2024Benjamin Vendeville, Liana Ermakova, Pierre De Loor. 3317-3340 [doi]
• Overview of Touché 2024: Argumentation SystemsJohannes Kiesel, Çagri Çöltekin, Maximilian Heinrich, Maik Fröbe, Milad Alshomary, Bertrand De Longueville, Tomaz Erjavec, Nicolas Handke, Matyás Kopp, Nikola Ljubesic, Katja Meden, Nailia Mirzakhmedova, Vaidas Morkevicius, Theresa Reitis-Münstermann, Mario Scharfbillig, Nicolas Stefanovitch, Henning Wachsmuth, Martin Potthast, Benno Stein 0001. 3341-3366 [doi]
• Team INSA Passau at Touché: Multi-lingual Parliamentary Speech ClassificationMaud Andruszak, Alaa Alhamzeh, Elöd Egyed-Zsigmond, Anton Carlsson, Johan Leydet, Yasser Otiefy. 3367-3378 [doi]
• Edward Said at Touché: Human Value Detection Using Transformers and UpsamplingAisha Nur Aydin, Shaden Shaar, Claire Cardie. 3379-3383 [doi]
• gerber at Touché: Ideology and Power Identification in Parliamentary Debates 2024Christian Gerber. 3384-3392 [doi]
• Pixel Phantoms at Touché: Ideology and Power Identification in Parliamentary Debates using Linear SVCJanani Hariharakrishnan, Jithu Morrison S, Palaniappan Mirunalini. 3393-3400 [doi]
• HTW-DIL at Touché: Multimodal Dense Information Retrieval for ArgumentsTamás Janusko, Aaron Kämpf, Denis Keiling, Jessica Knick, David Schäfer, Maik Thiele. 3401-3406 [doi]
• SCaLAR NITK at Touché: Comparative Analysis of Machine Learning Models for Human Value IdentificationPraveen K, Darshan R. K, Chinta Tejdeep Reddy, Anand Kumar M. 3407-3413 [doi]
• JU_NLP_DID at Touché: An Attempt to Identify Aspects of Power from Parliamentary DebatesAdnan Khurshid, Dipankar Das, Rajdeep Khaskel, Suchanda Datta. 3414-3418 [doi]
• Hierocles of Alexandria at Touché: Multi-task & Multi-head Custom Architecture with Transformer-based Models for Human Value DetectionSotirios Legkas, Christina Christodoulou, Matthaios Zidianakis, Dimitrios Koutrintzes, Maria Dagioglou, Georgios Petasis. 3419-3432 [doi]
• Eric Fromm at Touché: Prompts vs FineTuning for Human Value DetectionRanjan Mishra, Meike Morren. 3433-3446 [doi]
• DS@GT at Touché: Image Search and Ranking via CLIP and Image GenerationBenjamin Ostrower, Patcharapong Aphiwetsa. 3447-3450 [doi]
• Policy Parsing Panthers at Touché: Ideology and Power Identification in Parliamentary DebatesOscar Palmqvist, Johan Jiremalm, Pablo Picazo-Sanchez. 3451-3477 [doi]
• Trojan Horses at Touché: Logistic Regression for Classification of Political DebatesDeepak Chandar S, Diya Seshan, Avaneesh Koushik, Palaniappan Mirunalini. 3478-3482 [doi]
• Vayam Solve Kurmaha at Touché: Power Identification in Parliamentary Speeches Using TF-IDF Vectorizer and SVM ClassifierLakshmi Priya S, Dhannya S. M, S. Shwetha, Surabhi Kamath, Shreedevi Seluka Balaji, Sai Nikitha N. S. R, Srinidhi Lakshmi Narayanan. 3483-3488 [doi]
• HALE Lab NITK at Touché 2024: A Hybrid Approach for Identifying Political Ideology and Power in Multilingual Parliamentary SpeechesSimhadri Sevitha, Mauli Mehulkumar Patel, Sowmya Kamath S.. 3489-3495 [doi]
• Ssnites at Touché: Ideology and Power Identification in Parliamentary Debates using BERT ModeKeerthick V, Kaushik Ananth Kumar S, Kathir Kaman A, Palaniappan Mirunalini, Sripriya N. 3496-3502 [doi]
• Philo of Alexandria at Touché: A Cascade Model Approach to Human Value DetectionVíctor Yeste, Mariona Coll Ardanuy, Paolo Rosso. 3503-3508 [doi]
• Arthur Schopenhauer at Touché 2024: Multi-Lingual Text Classification Using Ensembles of Large Language ModelsHamza Yunis. 3509-3517 [doi]