CLI-Universe: Towards Verifiable Task Synthesis Engine for Terminal Agents
A principled synthesis engine generates high-quality terminal-agent tasks through multi-dimensional capability taxonomy and evidence-guided research, creating a distilled dataset t…
Hugging Face · Daily Papers
·Zhanbo Hua, Yifan Yao
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·▲ 24 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Zhanbo Hua, Yifan Yao, Weihao Xie, Yongchi Zhao, Minghao Liu, Ruizhi Qiu
- 24 upvotes da comunidade
- Temas: LLM-based terminal agents, executable training data, synthesis engine, capability taxonomy, evidence-guided deep research, Dockerized environments
Resumo
Resumo original (em inglês), extraído do paper:
A principled synthesis engine generates high-quality terminal-agent tasks through multi-dimensional capability taxonomy and evidence-guided research, creating a distilled dataset that enables significant performance gains in LLM training.
