新闻
Before They Can Solve: Predicting Post-Training Coding-Agent Performance from Base Models
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers developed methods to predict how well base coding models will perform after post-training as agents, without running expensive training.
- 为何重要
- ML engineers selecting which base models to fine-tune for coding tasks need early signals before committing compute to post-training.
- 注意
- Methods rely on having successful post-trained trajectories and verifiers available; results shown on ten model pairs, generalization unclear.
- agent
- agentic
- prompt
- post-train
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