Awesome Deep Research Agent

We maintain a curated collection of papers exploring the path towards Deep Research (DR) Agents, focusing on formulating core concepts and mapping the research landscape.

⌛️ We’re continuously compiling and updating cutting‑edge insights. Feel free to suggest any related work you find valuable!

Build a digital assistant on your screen. Generated by DALL-E-3.

🔥 WELCOME CONTRIBUTE!

🔥 This project is actively maintained, and we welcome your contributions. If you have any suggestions, such as missing papers or information, please feel free to open an issue or submit a pull request.

📰 News

• [2025.09.03] 📄 Updated version of our paper "Deep Research Agents: A Systematic Examination And Roadmap" is now available on ArXiv with expanded analysis and refined research directions!
• [2025.06.18] 🚀 Our comprehensive survey "Deep Research Agents: A Systematic Examination And Roadmap" is officially released on ArXiv - providing systematic insights into the current state and future of deepresearch agents!

🏗️ Our Works Towards DR Agents

✨✨✨ Deep Research Agents: A Systematic Examination And Roadmap

📚 Awesome Papers

Table of Contents

1. Search Engine Integration
2. Tool Use
3. Architecture & Workflow
   • Static Workflow
   • Dynamic Single‑Agent Workflow
   • Dynamic Multi‑Agent Workflow
4. Tuning Methods
5. Industrial Applications
6. Benchmarks for DR Agents

Search Engine Integration

📊 Search Engine · API vs Browser Comparison

Tool Use 

📊 Tool Use Capabilities Comparison

Architecture & Workflow

Static Workflow

• AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning
• Agent Laboratory: Using LLM Agents as Research Assistants
• CoSearchAgent: A Lightweight Collaborative Search Agent with Large Language Models
• AgentRxiv: Towards Collaborative Autonomous Research
• The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
• Nouswise

Dynamic Single‑Agent Workflow

• OpenResearcher: Unleashing AI for Accelerated Scientific Research
• Search‑o1: Agentic Search‑Enhanced Large Reasoning Models
• Agentic Reasoning: Reasoning LLMs with Tools for the Deep Research
• Agent‑R1: Training Powerful LLM Agents with End‑to‑End Reinforcement Learning
• R1‑Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
• Search‑R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
• DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real‑world Environments
• WebThinker: Empowering Large Reasoning Models with Deep Research Capability
• Open AI Deep Research
• Google Gemini Deep Research
• Grok Deep Search
• Perplexity Deep Research
• ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning
• Synthetic Data Generation & Multi-Step RL for Reasoning & Tool Use
• H2O.ai Deep Research
• SimpleDeepSearcher: Deep Information Seeking via Web-Powered Reasoning Trajectory Synthesis
• WebDancer: Towards Autonomous Information Seeking Agency
• Synthetic Data Generation & Multi‑Step RL for Reasoning & Tool Use
• SimpleDeepSearcher: Deep Information Seeking via Web‑Powered Reasoning Trajectory Synthesis
• Suna AI
• Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self‑Evolution
• AgenticSeek
• AutoGLM Rumination
• O-agents
• WebDancer
• WebSailor
• WebShaper
• Kimi-Researcher
• Deep Researcher with Test-Time Diffusion
• WebWatcher
• Chat-Agent
• Cognitive Kernel-Pro
• Tool-Star
• MiroRL
• Memento

Dynamic Multi‑Agent Workflow

• Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models
• AutoAgent: A Fully-Automated and Zero-Code Framework for LLM Agents
• OpenManus
• Manus
• OWL
• PANGU DEEPDIVER: ADAPTIVE SEARCH INTENSITY SCALING VIA OPEN-WEB REINFORCEMENT LEARNING
• H2O.ai Deep Research
• Copilot Researche
• Genspark Super Agent
• DeerFlow
• MMAC-Copilot
• Agent KB
• Towards an AI co-scientist
• WebWalker
• AWorld
• Atom-Searcher

Tuning Methods

📊 Tuning Methods Comparison

Benchmarks for DR Agents

📊 QA Benchmarks (Hotpot / 2Wiki / NQ / TQ / GPQA)

📊 GAIA (Test and Val) Benchmarks

📄 Citation

If you find this work helpful, please cite our paper:

@article{huang2025deep,
  title={Deep Research Agents: A Systematic Examination And Roadmap},
  author={Huang, Yuxuan and Chen, Yihang and Zhang, Haozheng and Li, Kang and Fang, Meng and Yang, Linyi and Li, Xiaoguang and Shang, Lifeng and Xu, Songcen and Hao, Jianye and others},
  journal={arXiv preprint arXiv:2506.18096},
  year={2025}
}

<!-- ## Relevant Survey

• A Survey of Generative Search and Recommendation in the Era of Large Language Models (Apr.2024)

• When Search Engine Services meet Large Language Models: Visions and Challenges (June.2024)

• Large Language Models for Information Retrieval: A Survey (Sep.2024)

Benchmark

• SWE-bench: Can Language Models Resolve Real-World GitHub Issues? (Oct.2023)

• GAIA: a benchmark for General AI Assistants (Nov.2023)

• Learning to Ask: When LLM Agents Meet Unclear Instruction (Aug.2024)

• MLGym: A New Framework and Benchmark for Advancing AI Research Agents (Feb. 2025)
  GitHub Repo

• Retrieval Models Aren't Tool-Savvy: Benchmarking Tool Retrieval for Large Language Models (Mar.2025)

Close Source Research Agent

• **Google Gemini Deep Research (Dec.2024)

• **Open AI Deep Research (Feb.2025)

• **Perplexity Deep Research (Feb.2025)

• **Grok Deep Search (March. 2025)

Deep Research Agent (final):

Deep Research Agent

• Agentic Reasoning: Reasoning LLMs with Tools for the Deep Research (Feb.2025)

• AgentRxiv: Towards Collaborative Autonomous Research (Mar.2025)

• Agent-R1: Training Powerful LLM Agents with End-to-End Reinforcement Learning (Mar.2025)

Retrieval/Search Augmented Agent Framework

• Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models (Jul.2024)

• OPEN-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models (Oct.2024)

• Chain-of-Retrieval Augmented Generation (Jan.2025)

• Search-o1: Agentic Search-Enhanced Large Reasoning Models (Jan.2025)

• FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research (Feb.2025)**

• DeepRAG: Thinking to Retrieval Step by Step for Large Language Models (Feb.2025)**

• Toward Agentic AI: Generative Information Retrieval Inspired Intelligent Communications and Networking (Feb.2025)

Toolcall Agent Framework

• Agent S: An Open Agentic Framework that Uses Computers Like a Human (Oct.2024)**

• Open AI Operator (Jan.2025)

• AutoAgent: A Fully-Automated and Zero-Code Framework for LLM Agents (Feb. 2025)**

• Agent S2: An Open, Modular, and Scalable Framework for Computer Use Agents (Mar.2025)

• OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation (Mar.2025)

• OpenManus (Mar. 2025)

• START: Self-taught Reasoner with Tools (Mar.2025)

Reinforcement Learning

• DeepRetrieval: Powerful Query Generation for Information Retrieval with Reinforcement Learning (Feb.2025)

• ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning (Mar.2025)**

• R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning (Mar.2025)**

• Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning (Mar.2025)**

• Agent-R1: Training Powerful LLM Agents with End-to-End Reinforcement Learning (Mar.2025)** -- >