Persistent Cross-Attempt State Optimization for Repository-Level Code Generation
Large language models (LLMs) have achieved substantial progress in repository-level code generation. However, solving the same repository-level task often requires multiple attempts, while existing methods still optimize each attempt in isolation and do not preserve or reuse task-specific state across attempts. In this paper, we propose LiveCoder, a novel framework for repository-level code generation based on cross-attempt knowledge optimization. LiveCoder maintains persistent task-specific state from prior attempts to guide subsequent generation. This state includes success knowledge, which captures reusable signals from previously strong repositories, failure knowledge, which records u...
| Authors | Ruwei Pan, Jiangshuai Wang, Qisheng Zhang et al. |
|---|---|
| Primary category | cs.SE |
| Published | 4 April 2026 |
| Last updated at source | 4 April 2026 |
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