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ORCIDAAAI 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, Debashis Sahoo:
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, Han Kyul Kim:
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, Cassidy R. Sugimoto, Thema Monroe-White:
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, 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:
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, 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:
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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