Verified workflow training gives language models reusable procedural skills

SkillGym converts human-written agent instructions into checked training tasks, enabling models to retain workflows even when the original skills are withheld.

Chinese Tech
Zhilong Ge · Yuting Shao · Yutao Yang · Yuxuan Cai · Jie Zhou · Kai Chen · +3 more

East China Normal University · Shanghai AI Laboratory

Research Digest··2 min read
Ge et al.

The authors developed SkillGym, a pipeline that turns written agent skills—step-by-step workflows normally supplied at inference time—into concrete tasks with code-based outcome checkers.

Why this paper

From Shanghai AI Laboratory and East China Normal University · Part of Skill Selection for Agents, now 14 papers

In one line

SkillGym converts human-written agent skills into executable training environments, enabling LLMs to internalize procedural competence and beat larger models on real-world benchmarks.

What we could check

  • ·No code link found
  • ·No weights link found
  • ·No dataset link found
  • ·No compute details found
  • ·No stated limitations found
  • ·No benchmark numbers found

Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.

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