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Collections including paper arXiv:2501.11425

AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning

Paper • 2402.15506 • Published Feb 23, 2024 • 18
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent

Paper • 2404.03648 • Published Apr 4, 2024 • 30
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts

Paper • 2405.19893 • Published May 30, 2024 • 33
Parrot: Efficient Serving of LLM-based Applications with Semantic Variable

Paper • 2405.19888 • Published May 30, 2024 • 7

Agent Workflow Memory

Paper • 2409.07429 • Published Sep 11, 2024 • 31
Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

Paper • 2501.11425 • Published Jan 20 • 109
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22 • 154

To Read collection

interesting papers to read

Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Paper • 2503.24290 • Published Mar 31 • 62
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119
START: Self-taught Reasoner with Tools

Paper • 2503.04625 • Published Mar 6 • 113
DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Paper • 2503.14476 • Published Mar 18 • 141

LLM-Reasoning (training)

LLM reasoning papers, with RL and long COT. (Post)Training of LLM is involved.

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Paper • 2501.12948 • Published Jan 22 • 423
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach

Paper • 2502.05171 • Published Feb 7 • 150
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though

Paper • 2501.04682 • Published Jan 8 • 99
rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Paper • 2501.04519 • Published Jan 8 • 285

Agent Laboratory: Using LLM Agents as Research Assistants

Paper • 2501.04227 • Published Jan 8 • 94
Search-o1: Agentic Search-Enhanced Large Reasoning Models

Paper • 2501.05366 • Published Jan 9 • 102
Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

Paper • 2501.11425 • Published Jan 20 • 109
Learn-by-interact: A Data-Centric Framework for Self-Adaptive Agents in Realistic Environments

Paper • 2501.10893 • Published Jan 18 • 26

Latest Agent paper

GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

Paper • 2508.06471 • Published Aug 8 • 189
Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

Paper • 2501.11425 • Published Jan 20 • 109
Agent Laboratory: Using LLM Agents as Research Assistants

Paper • 2501.04227 • Published Jan 8 • 94
Agent KB: Leveraging Cross-Domain Experience for Agentic Problem Solving

Paper • 2507.06229 • Published Jul 8 • 75

Interesting Papers

Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

Paper • 2501.11425 • Published Jan 20 • 109
Agent Laboratory: Using LLM Agents as Research Assistants

Paper • 2501.04227 • Published Jan 8 • 94
System Prompt Optimization with Meta-Learning

Paper • 2505.09666 • Published May 14 • 71
Visual Planning: Let's Think Only with Images

Paper • 2505.11409 • Published May 16 • 56

Evolving Deeper LLM Thinking

Paper • 2501.09891 • Published Jan 17 • 115
PaSa: An LLM Agent for Comprehensive Academic Paper Search

Paper • 2501.10120 • Published Jan 17 • 52
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong

Paper • 2501.09775 • Published Jan 16 • 33
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario

Paper • 2501.10132 • Published Jan 17 • 22

Papers exploring autonomous AI systems and frameworks for building intelligent agents that can perceive environment, plan actions and use tools.

Agent Laboratory: Using LLM Agents as Research Assistants

Paper • 2501.04227 • Published Jan 8 • 94
Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains

Paper • 2501.05707 • Published Jan 10 • 20
Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

Paper • 2501.11425 • Published Jan 20 • 109

rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Paper • 2501.04519 • Published Jan 8 • 285
URSA: Understanding and Verifying Chain-of-thought Reasoning in Multimodal Mathematics

Paper • 2501.04686 • Published Jan 8 • 53
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though

Paper • 2501.04682 • Published Jan 8 • 99
Agent Laboratory: Using LLM Agents as Research Assistants

Paper • 2501.04227 • Published Jan 8 • 94

AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning

Paper • 2402.15506 • Published Feb 23, 2024 • 18
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent

Paper • 2404.03648 • Published Apr 4, 2024 • 30
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts

Paper • 2405.19893 • Published May 30, 2024 • 33
Parrot: Efficient Serving of LLM-based Applications with Semantic Variable

Paper • 2405.19888 • Published May 30, 2024 • 7

Latest Agent paper

GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

Paper • 2508.06471 • Published Aug 8 • 189
Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

Paper • 2501.11425 • Published Jan 20 • 109
Agent Laboratory: Using LLM Agents as Research Assistants

Paper • 2501.04227 • Published Jan 8 • 94
Agent KB: Leveraging Cross-Domain Experience for Agentic Problem Solving

Paper • 2507.06229 • Published Jul 8 • 75

Agent Workflow Memory

Paper • 2409.07429 • Published Sep 11, 2024 • 31
Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

Paper • 2501.11425 • Published Jan 20 • 109
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22 • 154

Interesting Papers

Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

Paper • 2501.11425 • Published Jan 20 • 109
Agent Laboratory: Using LLM Agents as Research Assistants

Paper • 2501.04227 • Published Jan 8 • 94
System Prompt Optimization with Meta-Learning

Paper • 2505.09666 • Published May 14 • 71
Visual Planning: Let's Think Only with Images

Paper • 2505.11409 • Published May 16 • 56

To Read collection

interesting papers to read

Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Paper • 2503.24290 • Published Mar 31 • 62
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119
START: Self-taught Reasoner with Tools

Paper • 2503.04625 • Published Mar 6 • 113
DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Paper • 2503.14476 • Published Mar 18 • 141

Evolving Deeper LLM Thinking

Paper • 2501.09891 • Published Jan 17 • 115
PaSa: An LLM Agent for Comprehensive Academic Paper Search

Paper • 2501.10120 • Published Jan 17 • 52
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong

Paper • 2501.09775 • Published Jan 16 • 33
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario

Paper • 2501.10132 • Published Jan 17 • 22

LLM-Reasoning (training)

LLM reasoning papers, with RL and long COT. (Post)Training of LLM is involved.

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Paper • 2501.12948 • Published Jan 22 • 423
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach

Paper • 2502.05171 • Published Feb 7 • 150
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though

Paper • 2501.04682 • Published Jan 8 • 99
rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Paper • 2501.04519 • Published Jan 8 • 285

Papers exploring autonomous AI systems and frameworks for building intelligent agents that can perceive environment, plan actions and use tools.

Agent Laboratory: Using LLM Agents as Research Assistants

Paper • 2501.04227 • Published Jan 8 • 94
Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains

Paper • 2501.05707 • Published Jan 10 • 20
Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

Paper • 2501.11425 • Published Jan 20 • 109

Agent Laboratory: Using LLM Agents as Research Assistants

Paper • 2501.04227 • Published Jan 8 • 94
Search-o1: Agentic Search-Enhanced Large Reasoning Models

Paper • 2501.05366 • Published Jan 9 • 102
Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

Paper • 2501.11425 • Published Jan 20 • 109
Learn-by-interact: A Data-Centric Framework for Self-Adaptive Agents in Realistic Environments

Paper • 2501.10893 • Published Jan 18 • 26

rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Paper • 2501.04519 • Published Jan 8 • 285
URSA: Understanding and Verifying Chain-of-thought Reasoning in Multimodal Mathematics

Paper • 2501.04686 • Published Jan 8 • 53
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though

Paper • 2501.04682 • Published Jan 8 • 99
Agent Laboratory: Using LLM Agents as Research Assistants

Paper • 2501.04227 • Published Jan 8 • 94

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