Tag: Reasoning
All the articles with the tag "Reasoning".
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SEAL: Steerable Reasoning Calibration of Large Language Models for Free
Published: at 06:16 PM
87.52 🤔SEAL, a training-free method, calibrates the reasoning process of Large Language Models by steering latent representations to reduce redundant thoughts, achieving up to 14.1% accuracy improvement and 50.4% token reduction across diverse benchmarks.
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AM-Thinking-v1: Advancing the Frontier of Reasoning at 32B Scale
Published: at 11:20 PM 87.46 🤔AM-Thinking-v1 是一个32B参数的密集语言模型，通过精心设计的监督微调和强化学习后训练框架，在数学推理和代码生成任务上实现了与大型MoE模型媲美的性能，展示了中型规模模型在推理能力与部署效率之间的平衡潜力。
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Scaling Reasoning can Improve Factuality in Large Language Models
Published: at 11:09 AM 87.44 🤔本文通过从先进模型中提取并用知识图谱增强推理轨迹，微调Qwen2.5系列模型，并在复杂开放域问答任务中验证了测试时计算扩展（并行采样和预算强制）可提升事实准确性2-8%，尤其对小型模型效果显著。
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Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents
Published: at 11:24 AM 87.43 🤔本文提出Pre-Act方法，通过多步骤规划和详细推理提升LLM代理性能，并通过微调小型模型（如Llama 3.1 70B）在Almita数据集上实现比GPT-4高69.5%的行动准确率和28%的目标完成率。
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CoThink: Token-Efficient Reasoning via Instruct Models Guiding Reasoning Models
Published: at 11:15 AM 87.39 🤔CoThink 提出了一种双阶段推理框架，通过指令模型生成解决方案大纲指导推理模型完成解答，在保持准确率的同时平均减少 22.3% 的令牌生成量，提升了大型语言模型的推理效率。