Tag: Reasoning
All the articles with the tag "Reasoning".
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Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models
本文系统综述了基于强化学习的推理方法在多模态大语言模型(MLLMs)中的进展,分析了算法设计、奖励机制及应用,揭示了跨模态推理和奖励稀疏性等挑战,并提出了分层奖励和交互式RL等未来方向。
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Less is More: Enhancing Structured Multi-Agent Reasoning via Quality-Guided Distillation
本文提出了一种质量导向的多代理框架,通过提示诱导、检索增强合成和奖励过滤从少量标注数据中提炼高质量监督信号,提升LLMs在低资源结构化推理任务中的性能。
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Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models
本文首次系统调查了大型语言模型高效推理的进展,通过分类模型、输出和提示-based方法,探讨了减少"过度思考"现象的策略,以优化计算效率并保持推理能力。
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Agentic Reasoning and Tool Integration for LLMs via Reinforcement Learning
ARTIST, a novel framework unifying agentic reasoning, reinforcement learning, and tool integration, enables LLMs to autonomously orchestrate external tools within multi-turn reasoning, achieving up to 22% accuracy gains on complex math tasks and significant improvements in multi-turn function calling over baselines.
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Beyond the Last Answer: Your Reasoning Trace Uncovers More than You Think
本文提出了一种通过分割大型语言模型推理轨迹为子思维并从中间状态生成多条推理路径、最终以众数聚合答案的方法,显著提高了数学推理任务的准确性(最高提升13%),并揭示了答案一致性与正确性的相关性。