Function-Aware Fill-in-the-Middle: Mid-Training for Coding Agent Foundation Models
Image: Hugging Face Papers
TIGER-Lab proposes Function-Aware Fill-in-the-Middle (FIM) as a mid-training step for coding agent foundation models.
Standard FIM trains a model to fill a gap in code, but this work makes the model aware of the surrounding functions and their signatures.
The goal is stronger foundation models for coding agents — the systems that read a repo, plan changes and write pull requests.
For developers, better coding foundations mean agents that understand a codebase's structure instead of guessing from isolated snippets.
It reflects the shift from chat-based coding assistants toward autonomous agents that operate across whole repositories.
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