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AAAI Spring Symposia 2024: Stanford, CA, USA
- Ron P. A. Petrick, Christopher W. Geib:
Proceedings of the AAAI 2024 Spring Symposium Series, Stanford, CA, USA, March 25-27, 2024. AAAI Press 2024
Bi-directionality in Human-AI Collaborative Systems
- Cecilia O. Alm:
Centering Humans in Artificial Intelligence. 2-3 - Olivier Bartheye, Laurent Chaudron:
The Arithmetic of Machine Decision : How to Find the Symmetries of Complete Chaos. 4-11 - Ellen J. Bass, Steven Weber:
Toward Risk Frameworks for Autonomous Systems that Take Societal Safety-related Benefits into Account. 12-13 - Beth Cardier:
Communicating Unnamable Risks: Aligning Open World Situation Models Using Strategies from Creative Writing. 14-21 - Wanyi Chen, Mary L. Cummings:
Subjectivity in Unsupervised Machine Learning Model Selection. 22-29 - Yaliang Chuang, Poyang David Huang:
Learning Subjective Knowledge with Designer-Like Thinking and Interactive Machine Teaching. 30-34 - Boris Galitsky:
Shaped-Charge Architecture for Neuro-Symbolic Systems. 35-42 - Ted Goranson:
Perception-Dominant Control Types for Human/Machine Systems. 43-44 - Shih-Hong Huang, Ting-Hao (Kenneth) Huang:
On Replacing Humans with Large Language Models in Voice-Based Human-in-the-Loop Systems. 45-49 - Simon Kapiamba, Hesham Fouad, Ira S. Moskowitz:
Responsible Integration of Large Language Models (LLMs) in Navy Operational Plan Generation. 50-53 - Thuy Ngoc Nguyen, Chase McDonald, Cleotilde Gonzalez:
Credit Assignment: Challenges and Opportunities in Developing Human-like Learning Agents. 54-57 - Stephen Russell, Fabio Montes Suros, Ashwin Kumar:
Exploiting Machine Learning Bias: Predicting Medical Denials. 58-63 - Geoffrey W. Rutledge, Alexander Sivura:
A Generative AI-Based Virtual Physician Assistant. 64-65 - Diyi Yang:
Human-AI Interaction in the Age of Large Language Models. 66-67 - Ming Yin:
Accounting for Human Engagement Behavior to Enhance AI-Assisted Decision Making. 68-70
Empowering Machine Learning and Large Language Models with Domain and Commonsense Knowledge
- Nils Beutling, Maja Spahic-Bogdanovic:
Personalised Course Recommender: Linking Learning Objectives and Career Goals through Competencies. 72-81 - Stefan Dernbach, Khushbu Agarwal, Alejandro Zuniga, Michael Henry, Sutanay Choudhury:
GLaM: Fine-Tuning Large Language Models for Domain Knowledge Graph Alignment via Neighborhood Partitioning and Generative Subgraph Encoding. 82-89 - Charles Dickens, Connor Pryor, Lise Getoor:
Modeling Patterns for Neural-Symbolic Reasoning Using Energy-based Models. 90-99 - Florian Geissler, Karsten Roscher, Mario Trapp:
Concept-Guided LLM Agents for Human-AI Safety Codesign. 100-104 - Sadaf Ghaffari, Nikhil Krishnaswamy:
Exploring Failure Cases in Multimodal Reasoning About Physical Dynamics. 105-114 - Filippos Gouidis, Katerina Papantoniou, Konstantinos E. Papoutsakis, Theodore Patkos, Antonis A. Argyros, Dimitris Plexousakis:
Fusing Domain-Specific Content from Large Language Models into Knowledge Graphs for Enhanced Zero Shot Object State Classification. 115-124 - Nicholas Harvel, Felipe Bivort Haiek, Anupriya Ankolekar, David Brunner:
Can LLMs Answer Investment Banking Questions? Using Domain-Tuned Functions to Improve LLM Performance on Knowledge-Intensive Analytical Tasks. 125-133 - Jia Huang, Peng Jiang, Alvika Gautam, Srikanth Saripalli:
GPT-4V Takes the Wheel: Promises and Challenges for Pedestrian Behavior Prediction. 134-142 - Milan Kostic, Hans Friedrich Witschel, Knut Hinkelmann, Maja Spahic-Bogdanovic:
LLMs in Automated Essay Evaluation: A Case Study. 143-147 - Emanuele Laurenzi, Adrian Mathys, Andreas Martin:
An LLM-Aided Enterprise Knowledge Graph (EKG) Engineering Process. 148-156 - Pei-Ying Lin, Erick Chandra, Jane Yung-jen Hsu:
ASMR: Aggregated Semantic Matching Retrieval Unleashing Commonsense Ability of LLM through Open-Ended Question Answering. 157-166 - Carsten Maletzki
, Eric Rietzke, Ralph Bergmann:
Empowering Large Language Models in Hybrid Intelligence Systems through Data-Centric Process Models. 167-174 - Andreas Martin, Charuta Pande, Sandro Schwander, Ademola J. Ajuwon, Christoph Pimmer:
Domain-specific Embeddings for Question-Answering Systems: FAQs for Health Coaching. 175-179 - Andreas Martin, Charuta Pande, Hans Friedrich Witschel, Judith Mathez:
ChEdBot: Designing a Domain-Specific Conversational Agent in a Simulational Learning Environment Using LLMs. 180-187 - Andreas Martin, Hans Friedrich Witschel, Maximilian Mandl, Mona Stockhecke:
Semantic Verification in Large Language Model-based Retrieval Augmented Generation. 188-192 - Orfeas Menis-Mastromichalakis, Edmund Dervakos, Alexandros Chortaras, Giorgos Stamou:
Rule-Based Explanations of Machine Learning Classifiers Using Knowledge Graphs. 193-202 - Ankur Padia, Francis Ferraro, Tim Finin:
Enhancing Knowledge Graph Consistency through Open Large Language Models: A Case Study. 203-208 - Kristina Radivojevic, Nicholas Clark, Paul R. Brenner:
LLMs Among Us: Generative AI Participating in Digital Discourse. 209-218 - Kanak Raj, Kaushik Roy, Vamshi Bonagiri, Priyanshul Govil, Krishnaprasad Thirunarayan, Raxit Goswami, Manas Gaur:
K-PERM: Personalized Response Generation Using Dynamic Knowledge Retrieval and Persona-Adaptive Queries. 219-226 - Kaushik Roy, Alessandro Oltramari, Yuxin Zi, Chathurangi Shyalika, Vignesh Narayanan, Amit P. Sheth:
Causal Event Graph-Guided Language-based Spatiotemporal Question Answering. 227-233 - Sakhinana Sagar Srinivas, Geethan Sannidhi, Venkataramana Runkana:
Multi-Modal Instruction-Tuning Small-Scale Language-and-Vision Assistant for Semiconductor Electron Micrograph Analysis. 234-242 - Jaelle Scheuerman, Dina M. Acklin:
A Framework for Enhancing Behavioral Science Research with Human-Guided Language Models. 243-247 - Ben Schuering, Thomas Schmid:
What Can Computers Do Now? Dreyfus Revisited for the Third Wave of Artificial Intelligence. 248-252 - Lucas L. Snijder, Quirine T. S. Smit, Maaike H. T. de Boer:
Advancing Ontology Alignment in the Labor Market: Combining Large Language Models with Domain Knowledge. 253-262 - Neset Özkan Tan, Niket Tandon, David Wadden, Oyvind Tafjord, Mark Gahegan, Michael Witbrock:
Faithful Reasoning over Scientific Claims. 263-272 - Christopher Toukmaji, Allison Tee:
Retrieval-Augmented Generation and LLM Agents for Biomimicry Design Solutions. 273-278 - Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Amit P. Sheth:
Exploring Alternative Approaches to Language Modeling for Learning from Data and Knowledge. 279-286
Federated Learning on the Edge
- Sree Bhargavi Balija, Amitash Nanda
Building Communication Efficient Asynchronous Peer-to-Peer Federated LLMs with Blockchain. 288-292 - Nathalie Baracaldo:
Is Federated Learning Still Alive in the Foundation Model Era? 293 - Yiran Chen:
Advancing Federated Learning by Addressing Data and System Heterogeneity. 294 - Mark J. Gerken:
Operational Environments at the Extreme Tactical Edge. 295 - Seyyedali Hosseinalipour:
Confluence of Random Walks, Interacting Particle Systems, and Distributed Machine Learning: Federated Learning through Crawling over Networks. 296 - Anurata Prabha Hridi, Rajeev Sahay, Seyyedali Hosseinalipour, Bita Akram:
Revolutionizing AI-Assisted Education with Federated Learning: A Pathway to Distributed, Privacy-Preserving, and Debiased Learning Ecosystems. 297-303 - Jithin Jagannath:
Framework for Federated Learning and Edge Deployment of Real-Time Reinforcement Learning Decision Engine on Software Defined Radio. 304 - Hana Khamfroush:
Resource-aware Federated Data Analytics in Edge-Enabled IoT Systems. 305 - Sanmi Koyejo:
Towards Fault-Tolerant Federated and Distributed Machine Learning. 306 - Scott Kuzdeba:
Federated Learning of Things - Expanding the Heterogeneity in Federated Learning. 307 - Aritra Mitra:
Towards Robust Multi-Agent Reinforcement Learning. 308 - Jose Sanchez-Viloria, Dimitris Stripelis, Panos P. Markopoulos, George Sklivanitis, Dimitris A. Pados:
Adaptive Federated Learning for Automatic Modulation Classification Under Class and Noise Imbalance. 309 - Ashish Shenoy, Sid Wang, Pierce Chuang, John Nguyen:
Now It Sounds Like You: Learning Personalized Vocabulary On Device. 310-315 - Nojan Sheybani, Farinaz Koushanfar:
You Can Have Your Cake and Eat It Too: Ensuring Practical Robustness and Privacy in Federated Learning. 316 - Nicholas Soures, Vedant Karia, Dhireesha Kudithipudi:
Advancing Neuro-Inspired Lifelong Learning for Edge with Co-Design. 317 - Mehreen Tahir, Muhammad Intizar Ali:
Multi-Criterion Client Selection for Efficient Federated Learning. 318-322 - Elahe Vedadi, Joshua V. Dillon, Philip Andrew Mansfield, Karan Singhal, Arash Afkanpour, Warren Richard Morningstar:
Federated Variational Inference: Towards Improved Personalization and Generalization. 323-327 - Lun Wang:
Reconciling Privacy and Byzantine-robustness in Federated Learning. 328
Impact of GenAI on Social and Individual Well-being
- Christina Alexandris:
GenAI and Socially Responsible AI in Natural Language Processing Applications: A Linguistic Perspective. 330-337 - Soki Arai, Yuki Yamamoto, Yuji Nozaki, Haruka Matsukura, Maki Sakamoto:
A Dataset for Estimating Participant Inspiration in Meetings toward AI-Based Meeting Support System to Improve Worker Wellbeing. 338-339 - Oliver Bendel:
How Can Generative AI Enhance the Well-being of Blind? 340-347 - Sara Darwish, Alison Bragaw-Butler, Paul Marcelli, Kaylee Gassner:
Diversity, Equity, and Inclusion, and the Deployment of Artificial Intelligence Within the Department of Defense. 348-353 - Stefanie Hauske, Oliver Bendel:
How Can GenAI Foster Well-being in Self-regulated Learning? 354-361 - Kazuhiro Ito, Junko Hayashi, Shoko Wakamiya, Masae Manabe, Yasushi Watanabe, Masataka Nakayama, Yukiko Uchida, Eiji Aramaki:
Engineering Approach to Explore Language Reflecting Well-Being. 362-364 - Takashi Kido, Keiki Takadama:
The Challenges for GenAI in Social and Individual Well-Being. 365-367 - Iko Nakari, Keiki Takadama:
Sleep Stage Estimation by Introduction of Sleep Domain Knowledge to AI: Towards Personalized Sleep Counseling System with GenAI. 368-373 - Yuto Nakashima:
Personalized Image Generation Through Swiping. 374-375 - Michelle Nie:
Artificial Intelligence: The Biggest Threat to Democracy Today? 376-379 - Mark Nuppnau, Khalid Kattan, Robert G. Reynolds:
Cultural Algorithm Guided Policy Gradient with Parameter Exploration. 380-386 - Yukio Ohsawa, Tomohide Maekawa, Hiroki Yamaguchi, Hiro Yoshida, Kaira Sekiguchi:
Collect and Connect Data Leaves to Feature Concepts: Interactive Graph Generation Toward Wellbeing. 387-388 - Yukio Ohsawa, Sae Kondo, Yi Sun, Kaira Sekiguchi:
Generating a Map of Well-being Regions Using Multi-scale Moving Direction Entropy on Mobile Sensors. 389-390 - Yohn Jairo Parra Bautista, Carlos Theran, Richard A. Aló:
Ethical Considerations of Generative AI: A Survey Exploring the Role of Decision Makers in the Loop. 391-398 - Helen Qin:
Generative AI Applications in Helping Children with Speech Language Issues. 399-400 - Zhonghao Shi, Ellen Landrum, Amy O'Connell, Mina J. Kian, Leticia Pinto-Alva, Kaleen Shrestha, Xiaoyuan Zhu, Maja J. Mataric:
How Can Large Language Models Enable Better Socially Assistive Human-Robot Interaction: A Brief Survey. 401-404 - Daiki Shintani, Iko Nakari, Satomi Washizaki, Keiki Takadama:
NREM3 Sleep Stage Estimation Based on Accelerometer by Body Movement Count and Biological Rhythms. 405-411 - Andy Skumanich
Modes of Tracking Mal-Info in Social Media with AI/ML Tools to Help Mitigate Harmful GenAI for Improved Societal Well Being. 412-417 - Hiroshi Sogabe, Masayuki Numao:
Toward Application to General Conversation Detection of Dementia Tendency from Conversation Based on Linguistic and Time Features of Speech. 418-425 - Melanie Swan, Takashi Kido, Eric Roland, Renato P. dos Santos:
AI Health Agents: Pathway2vec, ReflectE, Category Theory, and Longevity. 426-433 - Keiki Takadama:
What Is a Correct Output by Generative AI From the Viewpoint of Well-Being? - Perspective From Sleep Stage Estimation -. 434-439 - Faye-Marie Vassel, Evan Shieh
The Psychosocial Impacts of Generative AI Harms. 440-447 - Kevin Vo:
AI-Assisted Talk: A Narrative Review on the New Social and Conversational Landscape. 448-449 - Kevin Vo:
Social Smarts with Tech Sparks: Harnessing LLMs for Youth Socioemotional Growth. 450-451 - Jin Yamanaka, Takashi Kido:
Evaluating Large Language Models with RAG Capability: A Perspective from Robot Behavior Planning and Execution. 452-456 - Mingzhe Yang:
Fair Machine Guidance to Enhance Fair Decision Making. 457-458 - Sharon Chee Yin Ho, Arisa Ema, Tanja Tajmel:
The Impacts of Text-to-Image Generative AI on Creative Professionals According to Prospective Generative AI Researchers: Insights from Japan. 459-463 - Takahiro Yonekawa, Hiroko Yamano, Ichiro Sakata:
An Analysis Method for the Impact of GenAI Code Suggestions on Software Engineers' Thought Processes. 464-465
Increasing Diversity in AI Education and Research
- Sambit Bhattacharya, Bogdan D. Czejdo, Rebecca Zulli, Adrienne Smith:
Enhancing AI Education at an MSI: A Design-Based Research Approach. 467-472 - Yu Chen, Gabriel Granco, Yunfei Hou, Heather Macias, Frank A. Gomez:
AI for Social Good Education at Hispanic Serving Institutions. 473 - Ryan Evans, Neelu Sinha:
Bridging the Gap: Diversity Initiatives in AI Education. 474-477 - Derek Jacoby, Saiph Savage, Yvonne Coady:
Remote Possibilities: Where There Is a WIL, Is There a Way? AI Education for Remote Learners in a New Era of Work-Integrated-Learning. 478-485 - Devang Jayachandran, Pranit Maldikar, Tyler S. Love, Jeremy J. Blum:
Leveraging Generative Artificial Intelligence to Broaden Participation in Computer Science. 486-492 - Mary Lou Maher, Sri Yash Tadimalla:
Increasing Diversity in Lifelong AI Education: Workshop Report. 493-500 - Swati Mehrotra, Neelu Sinha:
A Human-Centric Approach towards Equity and Inclusion in AI Education. 501-507 - Brian Plancher, Sebastian Büttrich, Jeremy Ellis, Neena Goveas, Laila D. Kazimierski, Jesús Alfonso López Sotelo, Milan Lukic, Diego Mendez
TinyML4D: Scaling Embedded Machine Learning Education in the Developing World. 508-515 - Christelle Scharff, James Brusseau, Krishna Mohan Bathula, Kaleemunnisa Fnu, Samyak Rakesh Meshram, Om Gaikhe:
Inclusion Ethics in AI: Use Cases in African Fashion. 516-521 - Neelu Sinha, Rama Madhavarao, Robert Freeman, Irene Oujo, Janet Boyd:
AI Literacy for Hispanic-Serving Institution (HSI) Students. 522-527 - Sri Yash Tadimalla, Mary Lou Maher:
Implications of Identity in AI: Creators, Creations, and Consequences. 528-535 - Kathleen Timmerman, Judy Goldsmith, Brent Harrison, Zongming Fei:
Designing Inclusive AI Certifications. 536-543
Symposium on Human-Like Learning
- Brendan Conway-Smith, Robert L. West:
Toward Autonomy: Metacognitive Learning for Enhanced AI Performance. 545-546 - Yinuo Du, Baptiste Prébot, Cleotilde Gonzalez:
Turing-like Experiment in a Cyber Defense Game. 547-550 - Kenneth D. Forbus:
Analogy as the Swiss Army Knife of Human-like Learning. 551-552 - Matt Jones, Tyler R. Scott, Michael C. Mozer:
Human-like Learning in Temporally Structured Environments. 553 - Steven Jones, Peter Lindes:
Toward Human-Like Representation Learning for Cognitive Architectures. 554-555 - Peter Lindes, Steven Jones:
Modeling Human-Like Acquisition of Language and Concepts. 556-558 - Maya Malaviya, Ilia Sucholutsky, Thomas L. Griffiths:
Pushing the Limits of Learning from Limited Data. 559-561 - Maya Malaviya, Mark K. Ho:
Teaching Functions with Gaussian Process Regression. 562-564 - Sheikh Mannan, Vivekanand Pandey Vimal, Paul DiZio, Nikhil Krishnaswamy:
Embodying Human-Like Modes of Balance Control Through Human-In-the-Loop Dyadic Learning. 565-569 - Shiwali Mohan, John E. Laird:
Learning Fast and Slow: A Redux of Levels of Learning in General Autonomous Intelligent Agents. 570-571 - Kanad Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh:
Learning Decision-Making Functions Given Cardinal and Ordinal Consensus Data. 572 - Viraj Parimi, Sungkweon Hong, Brian Williams:
Task-driven Risk-bounded Hierarchical Reinforcement Learning Based on Iterative Refinement. 573-575 - Edward Pogossian:
A Model of Cognizing Supporting the Origination of Cognizing in Nature. 576-578 - Ming Qian, Chuiqing Kong:
Exploring the Gap: The Challenge of Achieving Human-like Generalization for Concept-based Translation Instruction Using Large Language Models. 579-581 - Irina Rabkina:
Human-Like Learning of Social Reasoning via Analogy. 582 - Christopher B. Rauch
Algorithmic Decision-Making in Difficult Scenarios. 583-585 - Sina Rismanchian, Shayan Doroudi, Yasaman Razeghi:
Turtle-like Geometry Learning: How Humans and Machines Differ in Learning Turtle Geometry. 586-587 - Jesse Roberts
Do Large Language Models Learn to Human-Like Learn? 588-591 - Jonathan C. H. Tong, Yung-Fong Hsu, Churn-Jung Liau:
An Exploring Study on Building Affective Artificial Intelligence by Neural-Symbolic Computing (Extended Abstract). 592-593 - Daniel Weitekamp III:
Decomposed Inductive Procedure Learning: Learning Academic Tasks with Human-Like Data Efficiency. 594 - Yangyang Yu, Haohang Li, Zhi Chen, Yuechen Jiang, Yang Li, Denghui Zhang, Rong Liu, Jordan W. Suchow, Khaldoun Khashanah:
FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design. 595-597 - Bonan Zhao, Natalia Vélez, Thomas L. Griffiths:
Comparing Human Behavior to an Optimal Policy for Innovation. 598-599 - Bonan Zhao, Christopher G. Lucas, Neil R. Bramley:
Constructing Deep Concepts through Shallow Search. 600-602
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