DeepAgent: A General Reasoning Agent with Scalable Toolsets
A general reasoning agent with autonomous tool discovery, memory folding, and tool reinforcement learning across more than 16,000 tools.
Wenxiang Jiao 焦文祥
LLM Algorithm Expert / Xiaohongshu
Towards agents that reason deeply, learn from experience, and continually improve.
My research spans capability learning, deep reasoning, and self-evolving agents. I currently focus on tool and skill learning, agentic reinforcement learning, and harness engineering—how an agent’s runtime can support learning and self-improvement.
Research agenda
From learning to self-evolution.
01
Agents & Self-Evolution
How can agents learn from experience and improve themselves?
Tool & skill learning · Agentic RL · Harness Engineering 02Deep Reasoning
How can models reason more deeply and efficiently?
Multi-agent collaboration · Efficient reasoning · LLM psychology 03Capability Learning
How do language models acquire and update their capabilities?
Multilingual learning · Translation · Continual pretraining · SafetyA closer look
Selected work
Harness-R1: Learning to Edit Executable Runtime Harnesses from Agent Failure Trajectories
Learns to turn agent failure trajectories into executable runtime patches, using task reruns as reinforcement learning feedback.
Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate
Studies degeneration of thought in self-reflection and uses multi-agent debate to encourage divergent reasoning.
On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs
A systematic evaluation of LLM psychological portrayals across personality, relationships, motivation, and emotional abilities.
Citation and star counts checked .
Recently
Updates
Three papers accepted to NeurIPS 2026, namely MMSkills, Agent2World, and VisFactor. Congratulations!
Three papers accepted to ACL 2026 conference (2 main + 1 findings). Congratulations!
Two papers (REA-RL, DeepCompress) accepted to ICLR 2026. Congratulations!
Gave an invited talk at Agentic AI Summit 2026 titled Scalable and Personalizable AI Agents.
DeepAgent accepted to WWW 2026. Congratulations!
Background
Experience & education
Experience
- Sep 2025 — Present
Xiaohongshu
LLM Algorithm Expert
General agents, tool and skill learning, and self-improvement through Harness Engineering.
- Nov 2021 — Aug 2025
Tencent
Senior Researcher
Hunyuan, Aug 2024–Aug 2025: long-context understanding and complex instruction following.
AI Lab, Nov 2021–Aug 2024: multilingual models, translation, reasoning, and multi-agent collaboration.
Education
- Aug 2017 — Nov 2021
The Chinese University of Hong Kong
Ph.D. in Computer Science & Engineering
Advised by Prof. Irwin King and Prof. Michael R. Lyu.
- Aug 2015 — Jun 2017
Nanjing University
Master’s in Optical Engineering
- Sep 2011 — Jul 2015
Nanjing University
Bachelor’s in Information Engineering
Academic community
Recognition & service
Selected recognition
- 2024ICLR Oral Presentation
PsychoBench · Top 1.2%
- 2022Best Paper Award
Multilingual Representation Learning Workshop, EMNLP
- 20221st Place · WMT
Large-Scale African Languages Translation · Constrained track
Reviewing
Nature, Nature Machine Intelligence, NeurIPS, ICLR, ICML, ACL, and EMNLP.
Selected invited talks
Scalable and Personalizable AI Agents
Agentic AI Summit · Jan 2026
From Machine to Human-like Intelligence
CCMT tutorial · Oct 2023
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