Author

Shaoqiu Zhang

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Preprint Aug 2026

SKT: Skill-Use Training at Scale via Verified Synthetic Data Generation

Experiments across diverse models, benchmarks, and agent harnesses show that supervised fine-tuning on SKT-generated trajectories consistently improves skill-use performance, establishing verified data synthesis as an effective and scalable approach for skill-use training.

Zelin Tan, Yi-Qun Zhang, Hao Li et al. · 2 citations

Preprint Jul 2026

SWE-Pruner Pro: The Coder LLM Already Knows What to Prune

SWE-Pruner Pro is proposed, which prunes tool outputs directly inside the agent, with a small head turns the agent's own internal representations into a keep-or-prune label for each line, with a length-aware embedding keyed to each tool output's line count.

Yuhang Wang, Yuling Shi, Shaoqiu Zhang et al. · 2 citations