1.**Introduction**
How to conduct adaptive bug fixing and generate patches with minimal modifications have seldom been investigated. To bridge this gap, we first introduce a novel task,
namely AdaPR (Adaptive Program Repair). We then propose a two-stage approach **AdaPatcher**(Adaptive Patch Generator) to enhance program repair while maintaining the consistency.
In the first stage, we utilize a Bug Locator with self-debug learning to accurately pinpoint bug locations. In the second stage, we train a Program Modifier to ensure consistency between the post-modified fixed code and the premodified buggy code. The Program Modifier is enhanced with a location-aware repair learning strategy to generate patches based on identified buggy lines, a hybrid training strategy for selective reference and an adaptive preference learning to prioritize fewer changes.
The code can be found in the link https://github.com/zhenlongDai/AdaPatcher.
2.**Citation**
```
@article{dai2025less,
title={Less is Mo…
