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

Authors: Liliana Hotsko, Yinxi Li, Yuntian Deng, Pengyu Nie.

Trains a hypernetwork to generate repository-specific LoRA adapters from source code and update them as commits arrive.

ArXiv initial submission: 2026-06-04.

[Original paper](https://arxiv.org/abs/2606.06492) · [Reading-list entry](https://programasweights.com/reading-list/papers/2606.06492/)
[Preprint BibTeX](https://programasweights.com/reading-list/papers/2606.06492/citation.bib) · [Preprint CSL-JSON](https://programasweights.com/reading-list/papers/2606.06492/citation.csl.json) · [JSON record](https://programasweights.com/reading-list/papers/2606.06492/record.json)

**Contribution:** Code2LoRA-Static maps a repository snapshot to an adapter. Code2LoRA-Evo updates a GRU state with each code diff and generates the adapter from that state.

**Program form:** Generated LoRA matrices for a frozen code language model.

**Conditioning:** A repository snapshot; the evolution variant also receives successive commit diffs.

**Execution:** The code model uses the generated adapter without adding repository context tokens to each request.

**Relationship to PAW:** Code2LoRA and PAW train models to generate reusable weights. Code2LoRA puts repository knowledge into adapters; PAW compiles function specifications into neural programs with a compiler–interpreter interface.

**Limitations:** The paper evaluates Python test-assertion completion with Qwen2.5-Coder-1.5B.

Related terms: Code2LoRA, repository-conditioned adapters, commit-streaming adapters, hypernetworks, weight-space programming.

## Approaches

- [Generated weights and adapters](https://programasweights.com/reading-list/guides/compilation/#generated-adapters): Generate model weights from a task description, examples, or context.

Reading-list version 1.3.0; updated 2026-11-14.


## 中文简介

训练超网络，根据代码仓库生成 LoRA 适配器，并随新的提交更新适配器。

[中文阅读清单](https://programasweights.com/zh/reading-list/)