7 citations · 11 across the 14 of their papers we have counts for
5 papers · 2 filters
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…
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…
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…
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…
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…