most citedQwen3 Technical Report

111 citations · 130 across the 15 of their papers we have counts for

collaborators

18 papers

cs.CL2025

Nested Browser-Use Learning for Agentic Information Seeking

Baixuan Li, Jialong Wu, Wenbiao Yin +8

Information-seeking (IS) agents have achieved strong performance across a range of wide and deep search tasks, yet their tool use remains largely restricted to API-level snippet re…

cs.CL2025

AutoForge: Automated Environment Synthesis for Agentic Reinforcement Learning

Shihao Cai, Runnan Fang, Jialong Wu +10

Conducting reinforcement learning (RL) in simulated environments offers a cost-effective and highly scalable way to enhance language-based agents. However, previous work has been l…

cs.AI2025

EcomBench: Towards Holistic Evaluation of Foundation Agents in E-commerce

Rui Min, Zile Qiao, Ze Xu +18

Foundation agents have rapidly advanced in their ability to reason and interact with real environments, making the evaluation of their core capabilities increasingly important. Whi…

cs.AI2025

IterResearch: Rethinking Long-Horizon Agents with Interaction Scaling

Guoxin Chen, Zile Qiao, Xuanzhong Chen +13

Recent advances in deep-research agents have shown promise for autonomous knowledge construction through dynamic reasoning over external sources. However, existing approaches rely…

cs.CL2025

ParallelMuse: Agentic Parallel Thinking for Deep Information Seeking

Baixuan Li, Dingchu Zhang, Jialong Wu +9

Parallel thinking expands exploration breadth, complementing the deep exploration of information-seeking (IS) agents to further enhance problem-solving capability. However, convent…

cs.CL2025

WebLeaper: Empowering Efficiency and Efficacy in WebAgent via Enabling Info-Rich Seeking

Zhengwei Tao, Haiyang Shen, Baixuan Li +11

Large Language Model (LLM)-based agents have emerged as a transformative approach for open-ended problem solving, with information seeking (IS) being a core capability that enables…

cs.CL2025

Tongyi DeepResearch Technical Report

Tongyi DeepResearch Team, Baixuan Li, Bo Zhang +54

We present Tongyi DeepResearch, an agentic large language model, which is specifically designed for long-horizon, deep information-seeking research tasks. To incentivize autonomous…

cs.CL2025

WebResearcher: Unleashing unbounded reasoning capability in Long-Horizon Agents

Zile Qiao, Guoxin Chen, Xuanzhong Chen +13

Recent advances in deep-research systems have demonstrated the potential for AI agents to autonomously discover and synthesize knowledge from external sources. In this paper, we in…

cs.CL2025

Towards General Agentic Intelligence via Environment Scaling

Runnan Fang, Shihao Cai, Baixuan Li +13

Advanced agentic intelligence is a prerequisite for deploying Large Language Models in practical, real-world applications. Diverse real-world APIs demand precise, robust function-c…

cs.CL2025

Scaling Agents via Continual Pre-training

Liangcai Su, Zhen Zhang, Guangyu Li +19

Large language models (LLMs) have evolved into agentic systems capable of autonomous tool use and multi-step reasoning for complex problem-solving. However, post-training approache…

cs.CL2025

WebShaper: Agentically Data Synthesizing via Information-Seeking Formalization

Zhengwei Tao, Jialong Wu, Wenbiao Yin +10

The advent of Large Language Model (LLM)-powered agents has revolutionized artificial intelligence by enabling solutions to complex, open-ended tasks through web-based information-…

cs.CL2025★ 3 cited

WebSailor: Navigating Super-human Reasoning for Web Agent

Kuan Li, Zhongwang Zhang, Huifeng Yin +16

Transcending human cognitive limitations represents a critical frontier in LLM training. Proprietary agentic systems like DeepResearch have demonstrated superhuman capabilities on…

cs.CL2025★ 1 cited

EvolveSearch: An Iterative Self-Evolving Search Agent

Dingchu Zhang, Yida Zhao, Jialong Wu +8

The rapid advancement of large language models (LLMs) has transformed the landscape of agentic information seeking capabilities through the integration of tools such as search engi…

cs.CL2025★ 111 cited

Qwen3 Technical Report

An Yang, Anfeng Li, Baosong Yang +57

In this work, we present Qwen3, the latest version of the Qwen model family. Qwen3 comprises a series of large language models (LLMs) designed to advance performance, efficiency, a…

cs.CL2025

WebDancer: Towards Autonomous Information Seeking Agency

Jialong Wu, Baixuan Li, Runnan Fang +10

Addressing intricate real-world problems necessitates in-depth information seeking and multi-step reasoning. Recent progress in agentic systems, exemplified by Deep Research, under…

cs.CL2025★ 12 cited

Qwen2.5-1M Technical Report

An Yang, Bowen Yu, Chengyuan Li +25

We introduce Qwen2.5-1M, a series of models that extend the context length to 1 million tokens. Compared to the previous 128K version, the Qwen2.5-1M series have significantly enha…

cs.CL2025

OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking

Zekun Xi, Wenbiao Yin, Jizhan Fang +7

Machine writing with large language models often relies on retrieval-augmented generation. However, these approaches remain confined within the boundaries of the model's predefined…

cs.CL2025★ 3 cited

WebWalker: Benchmarking LLMs in Web Traversal

Jialong Wu, Wenbiao Yin, Yong Jiang +8

Retrieval-augmented generation (RAG) demonstrates remarkable performance across tasks in open-domain question-answering. However, traditional search engines may retrieve shallow co…