Code2LoRA: Hypernetwork-Generated Adapters for Code Language Models under Software Evolution

Published
Source
arXiv
Paper number
327
Field
Software Engineering
arXiv ID
2606.06492

Key points

  • A hypernetwork generates repository-specific LoRA adapters to inject repository knowledge at inference time without token overhead.
  • It supports two modes, Code2LoRA-Static for static snapshots and Code2LoRA-Evo for evolving codebases.
  • Code2LoRA-Evo adapts to commit-level diffs with a GRU hidden state.
  • It introduces RepoPeftBench, a new benchmark built from 604 Python repositories.
  • It comes close to the repository-specific LoRA upper bound with 66.2 percent exact match on the static track and 60.3 percent exact match on the evolving track.

Paper links

External research summaries. These are not HDATF publications or measured product results.

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