Papers by Jiahong Zhao

2 papers
Reinforced Efficient Reasoning via Semantically Diverse Exploration (2026.acl-long)

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Challenge: Existing methods for reinforcement learning with verifiable rewards suffer from limited exploration diversity and inefficient reasoning.
Approach: They propose a method that rewards concise and correct reasoning while penalizing unnecessarily long reasoning chains.
Outcome: Extensive experiments on Qwen and Llama models validate the effectiveness and efficiency of ROSE.
FLAIR: Steering LLM Mathematical Problem Solving based on A Fuzzy-Logic-AssIsted Reasoner (2026.acl-long)

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Challenge: Existing approaches to mathematical reasoning rely on static heuristics or pre-determined reasoning strategies.
Approach: They propose an adaptive framework that integrates fuzzy theory into LLM-based mathematical reasoning.
Outcome: The proposed framework outperforms state-of-the-art models while offering effective and interpretable diagnostics of intermediate problem-solving states.

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