AdaReasoner: Adaptive Reasoning Enables More Flexible Thinking in Large Language Models

• URL: http://arxiv.org/abs/2505.17312v3
• Date: Fri, 27 Jun 2025 19:19:38 GMT
• Title: AdaReasoner: Adaptive Reasoning Enables More Flexible Thinking in Large Language Models
• Authors: Xiangqi Wang, Yue Huang, Yanbo Wang, Xiaonan Luo, Kehan Guo, Yujun Zhou, Xiangliang Zhang,
• Abstract summary: AdaReasoner is an LLM-agnostic plugin designed for any LLM to automate adaptive reasoning configurations.<n>AdaReasoner is trained using a reinforcement learning (RL) framework, combining a factorized action space with a targeted exploration strategy.<n>It consistently outperforms standard baselines, preserves out-of-distribution robustness, and yield gains on knowledge-intensive tasks through tailored prompts.
• Score: 32.51746551988431
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: LLMs often need effective configurations, like temperature and reasoning steps, to handle tasks requiring sophisticated reasoning and problem-solving, ranging from joke generation to mathematical reasoning. Existing prompting approaches usually adopt general-purpose, fixed configurations that work 'well enough' across tasks but seldom achieve task-specific optimality. To address this gap, we introduce AdaReasoner, an LLM-agnostic plugin designed for any LLM to automate adaptive reasoning configurations for tasks requiring different types of thinking. AdaReasoner is trained using a reinforcement learning (RL) framework, combining a factorized action space with a targeted exploration strategy, along with a pretrained reward model to optimize the policy model for reasoning configurations with only a few-shot guide. AdaReasoner is backed by theoretical guarantees and experiments of fast convergence and a sublinear policy gap. Across six different LLMs and a variety of reasoning tasks, it consistently outperforms standard baselines, preserves out-of-distribution robustness, and yield gains on knowledge-intensive tasks through tailored prompts.

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