4 papers
Learning to Theorize the World from Observation
Doojin Baek, Gyubin Lee, Junyeob Baek +2
What does it mean to understand the world? Contemporary world models often operationalize understanding as accurate future prediction in latent or observation space. Developmental…
Discrete JEPA: Learning Discrete Token Representations without Reconstruction
Junyeob Baek, Hosung Lee, Christopher Hoang +2
The cornerstone of cognitive intelligence lies in extracting hidden patterns from observations and leveraging these principles to systematically predict future outcomes. However, c…
Addressing and Visualizing Misalignments in Human Task-Solving Trajectories
Sejin Kim, Hosung Lee, Sundong Kim
Understanding misalignments in human task-solving trajectories is crucial for enhancing AI models trained to closely mimic human reasoning. This study categorizes such misalignment…
ARCLE: The Abstraction and Reasoning Corpus Learning Environment for Reinforcement Learning
Hosung Lee, Sejin Kim, Seungpil Lee +4
This paper introduces ARCLE, an environment designed to facilitate reinforcement learning research on the Abstraction and Reasoning Corpus (ARC). Addressing this inductive reasonin…