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Over-Defense in Coding Agents Begins at Silent Forks

Hanjun Luo, Xuecheng Liu, Xiucheng Zhang, Zhuoning Xu, Yingbin Jin, Yankai Chen · Oct 18, 2026

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 45% Moderate protocol signal Freshness: Hot Status: Fallback
Automatic Metrics Long Horizon Coding
  • Language models behind coding agents are post-trained with outcome rewards, and recent methods concentrate credit on the turns that decide the outcome.
  • On a test set of unseen repositories, it lowers a 4B model's disproportionate behavior from 70.3% to 58.9%, against 67.7% for DPO at randomly chosen turns, establishing behavioral divergence as a learning signal for how agents act beyond…
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