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20242026
most citedR1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

7 citations · 11 across the 14 of their papers we have counts for

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8 papers · 1 filter

cs.CL2026

ClawGym II: Exploring Black-Box RL on Agent Harness

Huatong Song, Fei Bai, Ming Yang +17

Agent harnesses have substantially improved performance on long-horizon tasks by coordinating agent interactions with the environment. However, reinforcement learning through compl…

cs.CL2026

Evo-Bench: Can Language Models Improve Agent Harness?

Lisheng Huang, Chen Yang, Hao Zhou +6

Large Language Models (LLMs) have driven rapid progress in autonomous agents, yet standard evaluations remain confined to static task solving. An emerging frontier is harness evolu…

cs.CL2026

ClawGym: A Scalable Framework for Building Effective Claw Agents

Fei Bai, Huatong Song, Shuang Sun +11

Claw-style environments support multi-step workflows over local files, tools, and persistent workspace states. However, scalable development around these environments remains const…

cs.CL2026

BeyondSWE: Can Current Code Agent Survive Beyond Single-Repo Bug Fixing?

Guoxin Chen, Fanzhe Meng, Jiale Zhao +12

Current code-agent benchmarks primarily evaluate localized issue resolution within a single target repository, leaving under-tested many software engineering tasks that require ext…

cs.CL2026

Computer Environments Elicit General Agentic Intelligence in LLMs

Daixuan Cheng, Shaohan Huang, Yuxian Gu +6

Agentic intelligence in large language models (LLMs) requires not only model intrinsic capabilities but also interactions with external environments. Equipping LLMs with computers…

cs.CL2025★ 2 cited

R1-Searcher++: Incentivizing the Dynamic Knowledge Acquisition of LLMs via Reinforcement Learning

Huatong Song, Jinhao Jiang, Wenqing Tian +7

Large Language Models (LLMs) are powerful but prone to hallucinations due to static knowledge. Retrieval-Augmented Generation (RAG) helps by injecting external information, but cur…

cs.CL2025

SimpleDeepSearcher: Deep Information Seeking via Web-Powered Reasoning Trajectory Synthesis

Shuang Sun, Huatong Song, Yuhao Wang +10

Retrieval-augmented generation (RAG) systems have advanced large language models (LLMs) in complex deep search scenarios requiring multi-step reasoning and iterative information re…

cs.CL2024

YuLan-Mini: An Open Data-efficient Language Model

Yiwen Hu, Huatong Song, Jia Deng +8

Effective pre-training of large language models (LLMs) has been challenging due to the immense resource demands and the complexity of the technical processes involved. This paper p…