#Reasoning

2026

• 05-15 EN

  Zero Sum SVD: A Global, Loss-Aware Rank Budget for LLM Compression

• 05-15 中

  Zero Sum SVD：用「损失零和」做全局奇异值预算分配的 LLM 压缩方法

• 05-12 EN

  DAPO: An Open-Source LLM Reinforcement Learning System at Scale

• 05-12 中

  DAPO：大规模开源 LLM 强化学习系统

• 05-01 EN

  Low-Rank Optimization Trajectories for LLM RLVR Acceleration: A Technical Review of NExt

• 04-27 EN

  Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond — Technical Review

• 04-22 EN

  SAGE: Training-Free Semantic Evidence Composition for Edge-Cloud Inference Under Hard Uplink Budgets

• 04-19 EN

  SpecGuard: Verification-Aware Speculative Decoding for Efficient Multi-Step Reasoning

• 04-19 中

  SpecGuard：用于多步推理的验证感知推测解码

• 04-13 EN

  Toolformer: Language Models Can Teach Themselves to Use Tools — Deep Technical Review

• 04-13 中

  Toolformer：让语言模型自己学会“什么时候调用工具”——深度阅读笔记

• 04-11 EN

  Language Agent Tree Search (LATS): Unifying Reasoning, Acting, and Planning in Language Models — Deep Technical Review

• 04-11 中

  LATS（Language Agent Tree Search）：把推理、行动、规划统一到同一个语言模型代理框架里 — 深度阅读笔记

• 03-30 EN

  Chain-of-Thought Prompting Elicits Reasoning in LLMs — In-Depth Technical Review

• 02-20 EN

  DeepSeekMath: How 120B Tokens of Math Data and GRPO Rival GPT-4 on Competition Problems

• 02-16 EN

  Tree of Thoughts: Deliberate Problem Solving with Large Language Models — Technical Review