3 papers
cs.AI2025
GIFARC: Synthetic Dataset for Leveraging Human-Intuitive Analogies to Elevate AI Reasoning
Woochang Sim, Hyunseok Ryu, Kyungmin Choi +2
The Abstraction and Reasoning Corpus (ARC) poses a stringent test of general AI capabilities, requiring solvers to infer abstract patterns from only a handful of examples. Despite…
cs.CL2024
Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus
Seungpil Lee, Woochang Sim, Donghyeon Shin +6
The existing methods for evaluating the inference abilities of Large Language Models (LLMs) have been predominantly results-centric, making it challenging to assess the inference p…
cs.AI2024
Enhancing Analogical Reasoning in the Abstraction and Reasoning Corpus via Model-Based RL
Jihwan Lee, Woochang Sim, Sejin Kim +1
This paper demonstrates that model-based reinforcement learning (model-based RL) is a suitable approach for the task of analogical reasoning. We hypothesize that model-based RL can…