Jul 2026
Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models
Beyond in-domain gains, mid-training mitigates the capability erosion that agentic post-training otherwise inflicts on non-agent coding and non-coding tool-use benchmarks (tau-bench, BFCL): although the mid-training corpus contains Python code only, the function-call inductive bias survives post-training and yields consistent gains.
Yubo Wang, Jiarong Liang, Yuxuan Zhang et al.
· arXiv.org · 1 citation