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pith:2026:2WCQIODVOQ3UAT4MDGJNCVZ2MV
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ClawGym: A Scalable Framework for Building Effective Claw Agents

Bryan Dai, Chuan Hao, Daixuan Cheng, Fei Bai, Feng Chang, Huatong Song, Jian Yang, Ji-Rong Wen, Ran Tao, Renyuan Li, Shuang Sun, Wayne Xin Zhao, Yike Yang, Yuan Wei

ClawGym provides a complete framework for synthesizing data, training, and evaluating Claw-style personal agents.

arxiv:2604.26904 v3 · 2026-04-29 · cs.CL · cs.AI · cs.LG

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Claims

C1strongest claim

ClawGym supports the full lifecycle of Claw-style personal agent development by constructing ClawGym-SynData (13.5K filtered tasks), training ClawGym-Agents via SFT on black-box rollouts plus lightweight RL, and providing ClawGym-Bench (200 instances) for reliable evaluation.

C2weakest assumption

The persona-driven synthetic tasks and hybrid verification mechanisms produce training data and evaluations that transfer to real-world Claw-style environments with persistent local state and external tools.

C3one line summary

ClawGym supplies a 13.5K-task synthetic dataset, SFT-plus-RL trained agents, and a 200-instance benchmark to support the full lifecycle of Claw-style personal agent development.

Receipt and verification
First computed 2026-05-20T00:03:12.926681Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

d5850438757437404f8c1992d1573a6545bbb77c146c5d7b54e43bb8297bfbc1

Aliases

arxiv: 2604.26904 · arxiv_version: 2604.26904v3 · doi: 10.48550/arxiv.2604.26904 · pith_short_12: 2WCQIODVOQ3U · pith_short_16: 2WCQIODVOQ3UAT4M · pith_short_8: 2WCQIODV
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/2WCQIODVOQ3UAT4MDGJNCVZ2MV \
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# expect: d5850438757437404f8c1992d1573a6545bbb77c146c5d7b54e43bb8297bfbc1
Canonical record JSON
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