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LLM Agent
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2026
05-11
EN
MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems
05-11
中
MASPO:面向 LLM 多智能体系统的联合提示词优化
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
04-13
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
04-12
EN
Voyager: An Open-Ended Embodied Agent with Large Language Models — Deep Technical Review
04-12
中
Voyager:一个能在 Minecraft 中持续成长的 LLM 具身智能体 —— 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
03-23
EN
MiRA: A Subgoal-driven Framework for Improving Long-Horizon LLM Agents — Technical Review
03-16
EN
MetaGPT: When LLM Agents Form a Software Company — Multi-Agent Collaboration Done Right
03-09
EN
AutoGen: Microsoft's Framework for Building Multi-Agent Conversations That Actually Work
03-09
EN
Generative Agents: 25 AI Characters Living in a Simulated Town — Believable Human Behavior from LLMs
03-06
EN
SWE-agent: Turning LLMs Into Autonomous Software Engineers That Fix Real GitHub Issues
02-23
EN
Self-Refine: Teaching LLMs to Critique and Improve Their Own Output — No Extra Training Needed
02-20
EN
Reflexion: LLM Agents That Learn from Failure Through Verbal Self-Reflection
02-18
EN
GLM-5 Technical Review: From Vibe Coding to Agentic Engineering
02-16
EN
Tree of Thoughts: Deliberate Problem Solving with Large Language Models — Technical Review
02-09
EN
ReAct Technical Review: From Reasoning Ability to Executable Reasoning