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Session 1: Foundations and Challenges in AI Theory of Mind
Session 1: Foundations and Challenges in AI Theory of Mind
Towards Properly Implementing Theory of Mind in Artificial Intelligence: An Account of Four Frequent Misconceptions
Large Language Models Show No Coherence Across Different Theory of Mind Tasks: Evidence From GPT-4o
The Turing Game
Session 2: Enhancing AI’s Social and Affective Understanding
Session 2: Enhancing AI’s Social and Affective Understanding
Rank-O-ToM: Unlocking Emotional Nuance Ranking to Enhance Affective Theory-of-Mind
MAPS - A Metacognitive Architecture for Improved Social Learning
Bi-Directional Mental Model Reconciliation for Human-Robot Interaction with Large Language Models
Session 3: Theory of Mind for Decision-Making and Narrative Understanding
Session 3: Theory of Mind for Decision-Making and Narrative Understanding
Bayesian Inverse Reinforcement Learning Approach for Policy Summarization
Detective ToM: A Theory of Mind Framework for Analysis of Surprising Yet Coherent Crime Mysteries
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