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CoworkEnv synthesizes executable environments for coworker-agent training

huggingface.co by Zhongwei Xie et al. Editor score 8/10

CoworkEnv generates and validates workflow environments for SFT and RL; on Claw-Eval, SFT raises Qwen3-VL-8B-Instruct's mean score from 46.6 to 64.1, with a 31.9-point gain on multi-turn tasks. It offers a measurable approach to building training data for tool-using agents.

What

CoworkEnv synthesizes executable training environments for AI coworkers that must use tools, communicate across turns, and respond to changing workspace state.

Method

Teacher executions produce demonstrations for supervised fine-tuning, while student interactions supply rollouts and rewards for reinforcement learning.

Why it matters

The framework offers a way to generate and validate training experience for long-horizon agents; the excerpt reports improved Qwen3-VL-8B-Instruct scores after SFT.

Read on huggingface.co → Code · 3 stars

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