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Add papers related to Automated Program Repair #210

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12 changes: 11 additions & 1 deletion README.md
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Expand Up @@ -1993,14 +1993,24 @@ For each task, the first column contains non-neural methods (e.g. n-gram, TF-IDF

- "NL-Debugging: Exploiting Natural Language as an Intermediate Representation for Code Debugging" [2025-05] [[paper](https://arxiv.org/abs/2505.15356)]

- "Empirical Evaluation of Generalizable Automated Program Repair with Large Language Models" [2025-06] [[paper](https://arxiv.org/abs/2506.03283)]
- "The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models" [2025-05] [EASE, June 2025] [[paper](https://arxiv.org/abs/2505.02931)]

- "Adversarial Reasoning for Repair Based on Inferred Program Intent" [2025-05] [ISSTA 2025] [[paper](https://arxiv.org/abs/2505.13008)]

- "Empirical Evaluation of Generalizable Automated Program Repair with Large Language Models" [2025-06] [ICSE 2025] [[paper](https://arxiv.org/abs/2506.03283)]

- "Boosting Open-Source LLMs for Program Repair via Reasoning Transfer and LLM-Guided Reinforcement Learning" [2025-06] [[paper](https://arxiv.org/abs/2506.03921)]

- "EXPEREPAIR: Dual-Memory Enhanced LLM-based Repository-Level Program Repair" [2025-06] [[paper](https://arxiv.org/abs/2506.10484)]

- "SynFix: Dependency-Aware Program Repair via RelationGraph Analysis" [2025-07] [ACL 2025 Findings] [[paper](https://aclanthology.org/2025.findings-acl.252/)]

- "Agentic Program Repair from Test Failures at Scale: A Neuro-symbolic approach with static analysis and test execution feedback" [2025-07] [TSE, July 2025] [[paper](https://arxiv.org/abs/2507.18755)]

- "The Impact of Fine-tuning Large Language Models on Automated Program Repair" [2025-07] [ICSME 2025] [[paper](https://arxiv.org/abs/2507.19909)]

- "How Small is Enough? Empirical Evidence of Quantized Small Language Models for Automated Program Repair" [2025-08] [ESEM 2025] [[paper](https://arxiv.org/abs/2508.16499v1)]

### Code Similarity and Embedding (Clone Detection, Code Search)

- "Self-Supervised Contrastive Learning for Code Retrieval and Summarization via Semantic-Preserving Transformations" [2020-09] [SIGIR 2021] [[paper](https://arxiv.org/abs/2009.02731)]
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