5 papers · 1 filter
Align While Search: Belief-Guided Exploratory Inference for World-Grounded Embodied Agents
Seohui Bae, Jeonghye Kim, Youngchul Sung +1
In this paper, we propose a test-time adaptive agent that performs exploratory inference through posterior-guided belief refinement without relying on gradient-based updates or add…
Computational Blueprints: Generating Isomorphic Mathematics Problems with Large Language Models
Jeong-Hoon Kim, Jinwoo Nam, Geunsik Jo
Personalized mathematics education is growing rapidly, creating a strong demand for large sets of similar practice problems. Yet existing studies on mathematics problem generation…
Penalizing Infeasible Actions and Reward Scaling in Reinforcement Learning with Offline Data
Jeonghye Kim, Yongjae Shin, Whiyoung Jung +5
Reinforcement learning with offline data suffers from Q-value extrapolation errors. To address this issue, we first demonstrate that linear extrapolation of the Q-function beyond t…
RAISE: Enhancing Scientific Reasoning in LLMs via Step-by-Step Retrieval
Minhae Oh, Jeonghye Kim, Nakyung Lee +3
Scientific reasoning requires not only long-chain reasoning processes, but also knowledge of domain-specific terminologies and adaptation to updated findings. To deal with these ch…
ReflAct: World-Grounded Decision Making in LLM Agents via Goal-State Reflection
Jeonghye Kim, Sojeong Rhee, Minbeom Kim +4
Recent advances in LLM agents have largely built on reasoning backbones like ReAct, which interleave thought and action in complex environments. However, ReAct often produces ungro…