English(EN) TAC-CoT: Tool-Empowered Implicit Chain-of-Thought via Interleaving Explicit Tokens

新的TAC-CoT框架通过工具使用提高了LLM代理的效率

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-04 05:00

研究人员推出了一种名为TAC-CoT的新型框架，旨在增强大型语言模型（LLM）代理的能力。该系统将隐式思维链（CoT）推理与显式工具使用相结合，使代理能够更有效地执行复杂任务。通过用紧凑的潜在段替换详细的中间推理步骤，并将文本标记仅保留用于工具调用、观察和最终答案，TAC-CoT显著降低了计算开销。实验表明，TAC-CoT在数学和问答基准测试中提高了准确性，同时大幅减少了模型前向传播次数，并在各种场景中提高了工具使用质量。 AI

影响通过优化工具使用，提高了LLM代理在复杂推理任务中的效率和准确性。

排序理由该集群包含一篇详细介绍LLM代理新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Juseon Do, Sangmin Bae, Jeesu Jung, Hwanjun Song · 2026-11-04 05:00

TAC-CoT：通过交错显式令牌实现的工具赋能隐式思维链

arXiv:2611.01926v1 Announce Type: new Abstract: LLM-based agentic systems are increasingly combined with CoT reasoning to solve tasks that require accurate reasoning, external knowledge, and multi-step deliberation. Yet, explicit CoT incurs substantial generation overhead, while …

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报道来源 [1]

TAC-CoT：通过交错显式令牌实现的工具赋能隐式思维链

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