Papers by Jaechang Kim

2 papers
Semantic Exploration with Adaptive Gating for Efficient Problem Solving with Language Models (2025.acl-long)

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Challenge: Existing methods for multi-step reasoning suffer from inefficiency and redundancy . existing methods neglect the diversity of task difficulties leading to extensive searches even for easy tasks .
Approach: They propose a method that explores reasoning paths with a gating mechanism that decides whether to conduct a tree search based on the confidence level of answers from a previous simple reasoning method.
Outcome: The proposed method significantly improves accuracy by 4.3% on average while requiring only 31% of computational costs.
Bridging the Gap between Expert and Language Models: Concept-guided Chess Commentary Generation and Evaluation (2025.naacl-long)

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Challenge: Experimental results show that expert models generate accurate, informative and fluent commentary, but are prone to hallucinations due to their limited decision-making capabilities.
Approach: They propose a concept-guided chess commentary generation and a GPT-based Chess Commentary Evaluation to bridge this gap between expert models and large language models.
Outcome: The proposed model is accurate, informative, and fluent.

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