Table of Contents

• Centering Humans in Artificial IntelligenceCecilia O. Alm. 2-3 [doi]
• The Arithmetic of Machine Decision : How to Find the Symmetries of Complete ChaosOlivier Bartheye, Laurent Chaudron. 4-11 [doi]
• Toward Risk Frameworks for Autonomous Systems that Take Societal Safety-related Benefits into AccountEllen J. Bass, Steven Weber 0001. 12-13 [doi]
• Communicating Unnamable Risks: Aligning Open World Situation Models Using Strategies from Creative WritingBeth Cardier. 14-21 [doi]
• Subjectivity in Unsupervised Machine Learning Model SelectionWanyi Chen, Mary L. Cummings. 22-29 [doi]
• Learning Subjective Knowledge with Designer-Like Thinking and Interactive Machine TeachingYaliang Chuang, Poyang David Huang. 30-34 [doi]
• Shaped-Charge Architecture for Neuro-Symbolic SystemsBoris Galitsky. 35-42 [doi]
• Perception-Dominant Control Types for Human/Machine SystemsTed Goranson. 43-44 [doi]
• On Replacing Humans with Large Language Models in Voice-Based Human-in-the-Loop SystemsShih-Hong Huang, Ting-Hao (Kenneth) Huang. 45-49 [doi]
• Responsible Integration of Large Language Models (LLMs) in Navy Operational Plan GenerationSimon Kapiamba, Hesham Fouad, Ira S. Moskowitz. 50-53 [doi]
• Credit Assignment: Challenges and Opportunities in Developing Human-like Learning AgentsThuy Ngoc Nguyen 0001, Chase McDonald, Cleotilde Gonzalez. 54-57 [doi]
• Exploiting Machine Learning Bias: Predicting Medical DenialsStephen Russell, Fabio Montes Suros, Ashwin Kumar. 58-63 [doi]
• A Generative AI-Based Virtual Physician AssistantGeoffrey W. Rutledge, Alexander Sivura. 64-65 [doi]
• Human-AI Interaction in the Age of Large Language ModelsDiyi Yang. 66-67 [doi]
• Accounting for Human Engagement Behavior to Enhance AI-Assisted Decision MakingMing Yin. 68-70 [doi]
• Personalised Course Recommender: Linking Learning Objectives and Career Goals through CompetenciesNils Beutling, Maja Spahic-Bogdanovic. 72-81 [doi]
• GLaM: Fine-Tuning Large Language Models for Domain Knowledge Graph Alignment via Neighborhood Partitioning and Generative Subgraph EncodingStefan Dernbach, Khushbu Agarwal, Alejandro Zuniga, Michael Henry, Sutanay Choudhury. 82-89 [doi]
• Modeling Patterns for Neural-Symbolic Reasoning Using Energy-based ModelsCharles Dickens, Connor Pryor, Lise Getoor. 90-99 [doi]
• Concept-Guided LLM Agents for Human-AI Safety CodesignFlorian Geissler, Karsten Roscher, Mario Trapp. 100-104 [doi]
• Exploring Failure Cases in Multimodal Reasoning About Physical DynamicsSadaf Ghaffari, Nikhil Krishnaswamy. 105-114 [doi]
• Fusing Domain-Specific Content from Large Language Models into Knowledge Graphs for Enhanced Zero Shot Object State ClassificationFilippos Gouidis, Katerina Papantoniou, Konstantinos E. Papoutsakis, Theodore Patkos, Antonis A. Argyros, Dimitris Plexousakis. 115-124 [doi]
• Can LLMs Answer Investment Banking Questions? Using Domain-Tuned Functions to Improve LLM Performance on Knowledge-Intensive Analytical TasksNicholas Harvel, Felipe Bivort Haiek, Anupriya Ankolekar, David Brunner. 125-133 [doi]
• GPT-4V Takes the Wheel: Promises and Challenges for Pedestrian Behavior PredictionJia Huang, Peng Jiang, Alvika Gautam, Srikanth Saripalli. 134-142 [doi]
• LLMs in Automated Essay Evaluation: A Case StudyMilan Kostic, Hans Friedrich Witschel, Knut Hinkelmann, Maja Spahic-Bogdanovic. 143-147 [doi]
• An LLM-Aided Enterprise Knowledge Graph (EKG) Engineering ProcessEmanuele Laurenzi, Adrian Mathys, Andreas Martin 0001. 148-156 [doi]
• ASMR: Aggregated Semantic Matching Retrieval Unleashing Commonsense Ability of LLM through Open-Ended Question AnsweringPei-Ying Lin, Erick Chandra, Jane Yung-jen Hsu. 157-166 [doi]
• Empowering Large Language Models in Hybrid Intelligence Systems through Data-Centric Process ModelsCarsten Maletzki, Eric Rietzke, Ralph Bergmann. 167-174 [doi]
• Domain-specific Embeddings for Question-Answering Systems: FAQs for Health CoachingAndreas Martin 0001, Charuta Pande, Sandro Schwander, Ademola J. Ajuwon, Christoph Pimmer. 175-179 [doi]
• ChEdBot: Designing a Domain-Specific Conversational Agent in a Simulational Learning Environment Using LLMsAndreas Martin 0001, Charuta Pande, Hans Friedrich Witschel, Judith Mathez. 180-187 [doi]
• Semantic Verification in Large Language Model-based Retrieval Augmented GenerationAndreas Martin 0001, Hans Friedrich Witschel, Maximilian Mandl, Mona Stockhecke. 188-192 [doi]
• Rule-Based Explanations of Machine Learning Classifiers Using Knowledge GraphsOrfeas Menis-Mastromichalakis, Edmund Dervakos, Alexandros Chortaras, Giorgos Stamou. 193-202 [doi]
• Enhancing Knowledge Graph Consistency through Open Large Language Models: A Case StudyAnkur Padia, Francis Ferraro, Tim Finin. 203-208 [doi]
• LLMs Among Us: Generative AI Participating in Digital DiscourseKristina Radivojevic, Nicholas Clark, Paul R. Brenner. 209-218 [doi]
• K-PERM: Personalized Response Generation Using Dynamic Knowledge Retrieval and Persona-Adaptive QueriesKanak Raj, Kaushik Roy 0009, Vamshi Bonagiri, Priyanshul Govil, Krishnaprasad Thirunarayan, Raxit Goswami, Manas Gaur. 219-226 [doi]
• Causal Event Graph-Guided Language-based Spatiotemporal Question AnsweringKaushik Roy 0009, Alessandro Oltramari, Yuxin Zi, Chathurangi Shyalika, Vignesh Narayanan, Amit P. Sheth. 227-233 [doi]
• Multi-Modal Instruction-Tuning Small-Scale Language-and-Vision Assistant for Semiconductor Electron Micrograph AnalysisSakhinana Sagar Srinivas 0001, Geethan Sannidhi, Venkataramana Runkana. 234-242 [doi]
• A Framework for Enhancing Behavioral Science Research with Human-Guided Language ModelsJaelle Scheuerman, Dina M. Acklin. 243-247 [doi]
• What Can Computers Do Now? Dreyfus Revisited for the Third Wave of Artificial IntelligenceBen Schuering, Thomas Schmid. 248-252 [doi]
• Advancing Ontology Alignment in the Labor Market: Combining Large Language Models with Domain KnowledgeLucas L. Snijder, Quirine T. S. Smit, Maaike H. T. de Boer. 253-262 [doi]
• Faithful Reasoning over Scientific ClaimsNeset Özkan Tan, Niket Tandon, David Wadden, Oyvind Tafjord, Mark Gahegan, Michael Witbrock. 263-272 [doi]
• Retrieval-Augmented Generation and LLM Agents for Biomimicry Design SolutionsChristopher Toukmaji, Allison Tee. 273-278 [doi]
• Exploring Alternative Approaches to Language Modeling for Learning from Data and KnowledgeYuxin Zi, Kaushik Roy 0009, Vignesh Narayanan, Amit P. Sheth. 279-286 [doi]
• Building Communication Efficient Asynchronous Peer-to-Peer Federated LLMs with BlockchainSree Bhargavi Balija, Amitash Nanda, Debashis Sahoo. 288-292 [doi]
• Is Federated Learning Still Alive in the Foundation Model Era?Nathalie Baracaldo. 293 [doi]
• Advancing Federated Learning by Addressing Data and System HeterogeneityYiran Chen 0001. 294 [doi]
• Operational Environments at the Extreme Tactical EdgeMark J. Gerken. 295 [doi]
• Confluence of Random Walks, Interacting Particle Systems, and Distributed Machine Learning: Federated Learning through Crawling over NetworksSeyyedali Hosseinalipour. 296 [doi]
• Revolutionizing AI-Assisted Education with Federated Learning: A Pathway to Distributed, Privacy-Preserving, and Debiased Learning EcosystemsAnurata Prabha Hridi, Rajeev Sahay, Seyyedali Hosseinalipour, Bita Akram. 297-303 [doi]
• Framework for Federated Learning and Edge Deployment of Real-Time Reinforcement Learning Decision Engine on Software Defined RadioJithin Jagannath. 304 [doi]
• Resource-aware Federated Data Analytics in Edge-Enabled IoT SystemsHana Khamfroush. 305 [doi]
• Towards Fault-Tolerant Federated and Distributed Machine LearningSanmi Koyejo. 306 [doi]
• Federated Learning of Things - Expanding the Heterogeneity in Federated LearningScott Kuzdeba. 307 [doi]
• Towards Robust Multi-Agent Reinforcement LearningAritra Mitra. 308 [doi]
• Adaptive Federated Learning for Automatic Modulation Classification Under Class and Noise ImbalanceJose Sanchez-Viloria, Dimitris Stripelis, Panos P. Markopoulos, George Sklivanitis, Dimitris A. Pados. 309 [doi]
• Now It Sounds Like You: Learning Personalized Vocabulary On DeviceAshish Shenoy, Sid Wang, Pierce Chuang, John Nguyen. 310-315 [doi]
• You Can Have Your Cake and Eat It Too: Ensuring Practical Robustness and Privacy in Federated LearningNojan Sheybani, Farinaz Koushanfar. 316 [doi]
• Advancing Neuro-Inspired Lifelong Learning for Edge with Co-DesignNicholas Soures, Vedant Karia, Dhireesha Kudithipudi. 317 [doi]
• Multi-Criterion Client Selection for Efficient Federated LearningMehreen Tahir, Muhammad Intizar Ali. 318-322 [doi]
• Federated Variational Inference: Towards Improved Personalization and GeneralizationElahe Vedadi, Joshua V. Dillon, Philip Andrew Mansfield, Karan Singhal, Arash Afkanpour, Warren Richard Morningstar. 323-327 [doi]
• Reconciling Privacy and Byzantine-robustness in Federated LearningLun Wang. 328 [doi]
• GenAI and Socially Responsible AI in Natural Language Processing Applications: A Linguistic PerspectiveChristina Alexandris. 330-337 [doi]
• A Dataset for Estimating Participant Inspiration in Meetings toward AI-Based Meeting Support System to Improve Worker WellbeingSoki Arai, Yuki Yamamoto, Yuji Nozaki, Haruka Matsukura, Maki Sakamoto. 338-339 [doi]
• How Can Generative AI Enhance the Well-being of Blind?Oliver Bendel. 340-347 [doi]
• Diversity, Equity, and Inclusion, and the Deployment of Artificial Intelligence Within the Department of DefenseSara Darwish, Alison Bragaw-Butler, Paul Marcelli, Kaylee Gassner. 348-353 [doi]
• How Can GenAI Foster Well-being in Self-regulated Learning?Stefanie Hauske, Oliver Bendel. 354-361 [doi]
• Engineering Approach to Explore Language Reflecting Well-BeingKazuhiro Ito, Junko Hayashi, Shoko Wakamiya, Masae Manabe, Yasushi Watanabe, Masataka Nakayama, Yukiko Uchida, Eiji Aramaki. 362-364 [doi]
• The Challenges for GenAI in Social and Individual Well-BeingTakashi Kido, Keiki Takadama. 365-367 [doi]
• Sleep Stage Estimation by Introduction of Sleep Domain Knowledge to AI: Towards Personalized Sleep Counseling System with GenAIIko Nakari, Keiki Takadama. 368-373 [doi]
• Personalized Image Generation Through SwipingYuto Nakashima. 374-375 [doi]
• Artificial Intelligence: The Biggest Threat to Democracy Today?Michelle Nie. 376-379 [doi]
• Cultural Algorithm Guided Policy Gradient with Parameter ExplorationMark Nuppnau, Khalid Kattan, Robert G. Reynolds. 380-386 [doi]
• Collect and Connect Data Leaves to Feature Concepts: Interactive Graph Generation Toward WellbeingYukio Ohsawa, Tomohide Maekawa, Hiroki Yamaguchi, Hiro Yoshida, Kaira Sekiguchi. 387-388 [doi]
• Generating a Map of Well-being Regions Using Multi-scale Moving Direction Entropy on Mobile SensorsYukio Ohsawa, Sae Kondo, Yi Sun, Kaira Sekiguchi. 389-390 [doi]
• Ethical Considerations of Generative AI: A Survey Exploring the Role of Decision Makers in the LoopYohn Jairo Parra Bautista, Carlos Theran, Richard A. Aló. 391-398 [doi]
• Generative AI Applications in Helping Children with Speech Language IssuesHelen Qin. 399-400 [doi]
• How Can Large Language Models Enable Better Socially Assistive Human-Robot Interaction: A Brief SurveyZhonghao Shi, Ellen Landrum, Amy O'Connell, Mina J. Kian, Leticia Pinto-Alva, Kaleen Shrestha, Xiaoyuan Zhu, Maja J. Mataric. 401-404 [doi]
• NREM3 Sleep Stage Estimation Based on Accelerometer by Body Movement Count and Biological RhythmsDaiki Shintani, Iko Nakari, Satomi Washizaki, Keiki Takadama. 405-411 [doi]
• Modes of Tracking Mal-Info in Social Media with AI/ML Tools to Help Mitigate Harmful GenAI for Improved Societal Well BeingAndy Skumanich, Han Kyul Kim. 412-417 [doi]
• Toward Application to General Conversation Detection of Dementia Tendency from Conversation Based on Linguistic and Time Features of SpeechHiroshi Sogabe, Masayuki Numao. 418-425 [doi]
• AI Health Agents: Pathway2vec, ReflectE, Category Theory, and LongevityMelanie Swan, Takashi Kido, Eric Roland, Renato P. Dos Santos. 426-433 [doi]
• What Is a Correct Output by Generative AI From the Viewpoint of Well-Being? - Perspective From Sleep Stage Estimation -Keiki Takadama. 434-439 [doi]
• The Psychosocial Impacts of Generative AI HarmsFaye-Marie Vassel, Evan Shieh, Cassidy R. Sugimoto, Thema Monroe-White. 440-447 [doi]
• AI-Assisted Talk: A Narrative Review on the New Social and Conversational LandscapeKevin Vo. 448-449 [doi]
• Social Smarts with Tech Sparks: Harnessing LLMs for Youth Socioemotional GrowthKevin Vo. 450-451 [doi]
• Evaluating Large Language Models with RAG Capability: A Perspective from Robot Behavior Planning and ExecutionJin Yamanaka, Takashi Kido. 452-456 [doi]
• Fair Machine Guidance to Enhance Fair Decision MakingMingzhe Yang. 457-458 [doi]
• The Impacts of Text-to-Image Generative AI on Creative Professionals According to Prospective Generative AI Researchers: Insights from JapanSharon Chee Yin Ho, Arisa Ema, Tanja Tajmel. 459-463 [doi]
• An Analysis Method for the Impact of GenAI Code Suggestions on Software Engineers' Thought ProcessesTakahiro Yonekawa, Hiroko Yamano, Ichiro Sakata. 464-465 [doi]
• Enhancing AI Education at an MSI: A Design-Based Research ApproachSambit Bhattacharya, Bogdan D. Czejdo, Rebecca Zulli, Adrienne Smith. 467-472 [doi]
• AI for Social Good Education at Hispanic Serving InstitutionsYu Chen, Gabriel Granco, Yunfei Hou, Heather Macias, Frank A. Gomez. 473 [doi]
• Bridging the Gap: Diversity Initiatives in AI EducationRyan Evans, Neelu Sinha. 474-477 [doi]
• Remote Possibilities: Where There Is a WIL, Is There a Way? AI Education for Remote Learners in a New Era of Work-Integrated-LearningDerek Jacoby, Saiph Savage, Yvonne Coady. 478-485 [doi]
• Leveraging Generative Artificial Intelligence to Broaden Participation in Computer ScienceDevang Jayachandran, Pranit Maldikar, Tyler S. Love, Jeremy J. Blum. 486-492 [doi]
• Increasing Diversity in Lifelong AI Education: Workshop ReportMary Lou Maher, Sri Yash Tadimalla. 493-500 [doi]
• A Human-Centric Approach towards Equity and Inclusion in AI EducationSwati Mehrotra, Neelu Sinha. 501-507 [doi]
• TinyML4D: Scaling Embedded Machine Learning Education in the Developing WorldBrian Plancher, Sebastian Büttrich, Jeremy Ellis, Neena Goveas, Laila D. Kazimierski, Jesús Alfonso López Sotelo, Milan Lukic, Diego Mendez 0001, Rosdiadee Nordin, Andrés Oliva Trevisan, Massimo Pavan, Manuel Roveri, Marcus Rüb, Jackline Tum, Marian Verhelst, Salah Abdeljabar, Segun Adebayo, Thomas Amberg, Halleluyah Aworinde, José Bagur, Gregg Barrett, Nabil Benamar, Bharat S. Chaudhari, Ronald Criollo, David Cuartielles, José A. Ferreira Filho, Solomon Gizaw, Evgeni Gousev, Alessandro Grande, Shawn Hymel, Peter Ing, Prashant Manandhar, Pietro Manzoni, Boris Murmann, Eric Pan, Rytis Paskauskas, Ermanno Pietrosemoli, Tales C. Pimenta, Marcelo Rovai, Marco Zennaro, Vijay Janapa Reddi. 508-515 [doi]
• Inclusion Ethics in AI: Use Cases in African FashionChristelle Scharff, James Brusseau, Krishna Mohan Bathula, Kaleemunnisa Fnu, Samyak Rakesh Meshram, Om Gaikhe. 516-521 [doi]
• AI Literacy for Hispanic-Serving Institution (HSI) StudentsNeelu Sinha, Rama Madhavarao, Robert Freeman, Irene Oujo, Janet Boyd. 522-527 [doi]
• Implications of Identity in AI: Creators, Creations, and ConsequencesSri Yash Tadimalla, Mary Lou Maher. 528-535 [doi]
• Designing Inclusive AI CertificationsKathleen Timmerman, Judy Goldsmith, Brent Harrison, Zongming Fei. 536-543 [doi]
• Toward Autonomy: Metacognitive Learning for Enhanced AI PerformanceBrendan Conway-Smith, Robert L. West. 545-546 [doi]
• Turing-like Experiment in a Cyber Defense GameYinuo Du, Baptiste Prébot, Cleotilde Gonzalez. 547-550 [doi]
• Analogy as the Swiss Army Knife of Human-like LearningKenneth D. Forbus. 551-552 [doi]
• Human-like Learning in Temporally Structured EnvironmentsMatt Jones 0001, Tyler R. Scott, Michael C. Mozer. 553 [doi]
• Toward Human-Like Representation Learning for Cognitive ArchitecturesSteven Jones, Peter Lindes. 554-555 [doi]
• Modeling Human-Like Acquisition of Language and ConceptsPeter Lindes, Steven Jones. 556-558 [doi]
• Pushing the Limits of Learning from Limited DataMaya Malaviya, Ilia Sucholutsky, Thomas L. Griffiths 0001. 559-561 [doi]
• Teaching Functions with Gaussian Process RegressionMaya Malaviya, Mark K. Ho. 562-564 [doi]
• Embodying Human-Like Modes of Balance Control Through Human-In-the-Loop Dyadic LearningSheikh Mannan, Vivekanand Pandey Vimal, Paul DiZio, Nikhil Krishnaswamy. 565-569 [doi]
• Learning Fast and Slow: A Redux of Levels of Learning in General Autonomous Intelligent AgentsShiwali Mohan, John E. Laird. 570-571 [doi]
• Learning Decision-Making Functions Given Cardinal and Ordinal Consensus DataKanad Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh. 572 [doi]
• Task-driven Risk-bounded Hierarchical Reinforcement Learning Based on Iterative RefinementViraj Parimi, Sungkweon Hong, Brian Williams 0001. 573-575 [doi]
• A Model of Cognizing Supporting the Origination of Cognizing in NatureEdward Pogossian. 576-578 [doi]
• Exploring the Gap: The Challenge of Achieving Human-like Generalization for Concept-based Translation Instruction Using Large Language ModelsMing Qian, Chuiqing Kong. 579-581 [doi]
• Human-Like Learning of Social Reasoning via AnalogyIrina Rabkina. 582 [doi]
• Algorithmic Decision-Making in Difficult ScenariosChristopher B. Rauch, Ursula Addison, Michael W. Floyd, Prateek Goel, Justin Karneeb, Ray Kulhanek, Othalia Larue, David H. Ménager, Mallika Mainali, Matthew Molineaux, Adam Pease, Anik Sen, J. T. Turner, Rosina Weber. 583-585 [doi]
• Turtle-like Geometry Learning: How Humans and Machines Differ in Learning Turtle GeometrySina Rismanchian, Shayan Doroudi, Yasaman Razeghi. 586-587 [doi]
• Do Large Language Models Learn to Human-Like Learn?Jesse Roberts. 588-591 [doi]
• An Exploring Study on Building Affective Artificial Intelligence by Neural-Symbolic Computing (Extended Abstract)Jonathan C. H. Tong, Yung-Fong Hsu, Churn-Jung Liau. 592-593 [doi]
• Decomposed Inductive Procedure Learning: Learning Academic Tasks with Human-Like Data EfficiencyDaniel Weitekamp III. 594 [doi]
• FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character DesignYangyang Yu, Haohang Li, Zhi Chen, Yuechen Jiang, Yang Li, Denghui Zhang, Rong Liu, Jordan W. Suchow, Khaldoun Khashanah. 595-597 [doi]
• Comparing Human Behavior to an Optimal Policy for InnovationBonan Zhao, Natalia Vélez, Thomas L. Griffiths 0001. 598-599 [doi]
• Constructing Deep Concepts through Shallow SearchBonan Zhao, Christopher G. Lucas, Neil R. Bramley. 600-602 [doi]