Claw AI Lab: An Autonomous Multi-Agent Research Team

Fuente: arXiv
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Main Authors: Wu, Fan, Chen, Cheng, Tan, Zhenshan, Zhang, Taiyu, Xu, Xinzhen, Qian, Yanyu, Gao, Dingcheng, Zhu, Lanyun, Zhu, Qi, Tan, Yi, Ji, Deyi, Lin, Guosheng, Chen, Tianrun, Ye, Deheng, Liu, Fayao
Format: Preprint
Published: 2026
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author Wu, Fan
Chen, Cheng
Tan, Zhenshan
Zhang, Taiyu
Xu, Xinzhen
Qian, Yanyu
Gao, Dingcheng
Zhu, Lanyun
Zhu, Qi
Tan, Yi
Ji, Deyi
Lin, Guosheng
Chen, Tianrun
Ye, Deheng
Liu, Fayao
author_facet Wu, Fan
Chen, Cheng
Tan, Zhenshan
Zhang, Taiyu
Xu, Xinzhen
Qian, Yanyu
Gao, Dingcheng
Zhu, Lanyun
Zhu, Qi
Tan, Yi
Ji, Deyi
Lin, Guosheng
Chen, Tianrun
Ye, Deheng
Liu, Fayao
contents We present Claw AI Lab, a lab-native autonomous research platform that advances automated research from a hidden prompt-to-paper pipeline into an interactive AI laboratory. Rather than centering the system around a single agent or a fixed serial workflow, we allow users to instantiate a full research team from one prompt, with customizable roles, collaborative workflows, real-time monitoring, artifact inspection, and rollback/resume control through a unified dashboard. The platform also supports distinct research modes for exploration, multi-agent discussion, and reproduction, making autonomous research substantially more steerable and laboratory-like in practice. A key practical contribution of Claw AI Lab lies in its Claw-Code Harness, which connects local codebases, datasets, and checkpoints to runnable experiments and feeds execution artifacts back into the research loop. As a result, the harness improves not only execution integration, but also experimental completion and result integrity: experiments are easier to inspect, iterate on, and faithfully transfer into final papers, reducing common failure modes such as partial runs and malformed result reporting. In our internal evaluation on five AI research case studies, using AutoResearchClaw as the baseline, Claw AI Lab is consistently preferred by AI expert judges on idea novelty, experiment completeness, and paper presentation quality. We view Claw AI Lab as an early step toward a new paradigm: autonomous research as usable, interactive, and reliability-aware scientific infrastructure.
format Preprint
id arxiv_https___arxiv_org_abs_2605_22662
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Claw AI Lab: An Autonomous Multi-Agent Research Team
Wu, Fan
Chen, Cheng
Tan, Zhenshan
Zhang, Taiyu
Xu, Xinzhen
Qian, Yanyu
Gao, Dingcheng
Zhu, Lanyun
Zhu, Qi
Tan, Yi
Ji, Deyi
Lin, Guosheng
Chen, Tianrun
Ye, Deheng
Liu, Fayao
Artificial Intelligence
We present Claw AI Lab, a lab-native autonomous research platform that advances automated research from a hidden prompt-to-paper pipeline into an interactive AI laboratory. Rather than centering the system around a single agent or a fixed serial workflow, we allow users to instantiate a full research team from one prompt, with customizable roles, collaborative workflows, real-time monitoring, artifact inspection, and rollback/resume control through a unified dashboard. The platform also supports distinct research modes for exploration, multi-agent discussion, and reproduction, making autonomous research substantially more steerable and laboratory-like in practice. A key practical contribution of Claw AI Lab lies in its Claw-Code Harness, which connects local codebases, datasets, and checkpoints to runnable experiments and feeds execution artifacts back into the research loop. As a result, the harness improves not only execution integration, but also experimental completion and result integrity: experiments are easier to inspect, iterate on, and faithfully transfer into final papers, reducing common failure modes such as partial runs and malformed result reporting. In our internal evaluation on five AI research case studies, using AutoResearchClaw as the baseline, Claw AI Lab is consistently preferred by AI expert judges on idea novelty, experiment completeness, and paper presentation quality. We view Claw AI Lab as an early step toward a new paradigm: autonomous research as usable, interactive, and reliability-aware scientific infrastructure.
title Claw AI Lab: An Autonomous Multi-Agent Research Team
topic Artificial Intelligence
url https://arxiv.org/abs/2605.22662