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‎README.md‎

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[![Hugging Face](https://img.shields.io/badge/HF_Paper-2601.11655-FFD21E?style=for-the-badge&logo=huggingface&logoColor=000)](https://huggingface.co/papers/2601.11655)
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[![Tables](https://img.shields.io/badge/TABLES-Statistics-blue?style=for-the-badge&logo=databricks)](https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/tables/)
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[![Contributors](https://img.shields.io/github/contributors/DeepSoftwareAnalytics/Awesome-Issue-Resolution?style=for-the-badge&color=green&logo=github)](https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution/graphs/contributors)
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![Papers Count](https://img.shields.io/badge/papers-284-green?style=for-the-badge&logo=googlescholar&logoColor=white)
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![Papers Count](https://img.shields.io/badge/papers-286-green?style=for-the-badge&logo=googlescholar&logoColor=white)
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[**📖 Documentation Website**](https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/) | [**📄 Full Paper**](https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/paper/) | [**📋 Tables & Resources**](https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/tables/)
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## 📖 Abstract
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Based on a systematic review of **284 papers and online resources**, this survey establishes a holistic theoretical framework for Issue Resolution in software engineering. We examine how **Large Language Models (LLMs)** are transforming the automation of GitHub issue resolution. Beyond the theoretical analysis, we have curated a comprehensive collection of datasets and model training resources, which are continuously synchronized with our GitHub repository and project documentation website.
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Based on a systematic review of **286 papers and online resources**, this survey establishes a holistic theoretical framework for Issue Resolution in software engineering. We examine how **Large Language Models (LLMs)** are transforming the automation of GitHub issue resolution. Beyond the theoretical analysis, we have curated a comprehensive collection of datasets and model training resources, which are continuously synchronized with our GitHub repository and project documentation website.
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## 📰 News
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- **LLVM-Bench**: LLVM-Bench: Benchmarking and Advancing Large Language Models for LLVM Compiler Issue Resolution [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.00700)
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- **MM-IssueLoc**: MM-IssueLoc: A Controlled Benchmark for Evaluating Visual Evidence in Multimodal Repository-Level Issue Localization [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.15205) [![GitHub](https://img.shields.io/badge/GitHub-code-181717?logo=github&logoColor=white)](https://github.com/Jasaxion/MM-IssueLoc-Bench)
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- **STAIR**: Reusing Past Repairs Through Hierarchical Trajectory Abstraction for Coding Agents [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.29658)
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- **SWE-Pruner Pro**: SWE-Pruner Pro: The Coder LLM Already Knows What to Prune [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.18213) [![GitHub](https://img.shields.io/badge/GitHub-code-181717?logo=github&logoColor=white)](https://github.com/Ayanami1314/swe-pruner-pro)
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- **SWE-Review**: SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.06065) [![GitHub](https://img.shields.io/badge/GitHub-code-181717?logo=github&logoColor=white)](https://github.com/SWE-Lego/SWE-Review) [![HuggingFace](https://img.shields.io/badge/HuggingFace-model-FFD21E?logo=huggingface&logoColor=black)](https://huggingface.co/collections/SWE-Lego/swe-review)
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<!-- END_RECENT_PAPERS -->
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## 📚 Complete Paper List
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> **Total: 284 works** across 14 categories
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> **Total: 286 works** across 14 categories
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### 📊 Evaluation Datasets
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*Individual autonomous agents for issue resolution*
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- `(2026-07)` **SWE-Pruner Pro**: SWE-Pruner Pro: The Coder LLM Already Knows What to Prune [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.18213) [![GitHub](https://img.shields.io/badge/GitHub-repo-24292F?logo=github&logoColor=white)](https://github.com/Ayanami1314/swe-pruner-pro)
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- `(2026-05)` **EvoRepair**: EvoRepair: Enhancing Vulnerability Repair Agents Through Experience-Based Self-Evolution [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2605.30105)
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- `(2026-05)` **EviACT**: EviACT: An Evidence-to-Action Framework for Agentic Program Repair [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2605.27238)
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- `(2026-05)` **ContraFix**: ContraFix: Skill-Enhanced Contrastive Runtime Analysis for Vulnerability Repair [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2605.17450) [![Website](https://img.shields.io/badge/Website-paper-5B9BD5?logo=googlechrome&logoColor=white)](https://figshare.com/s/f173c78e44bca88ebaea?file=66112583)
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- `(2026-03)` **DAIRA**: Dynamic analysis enhances issue resolution [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2603.22048) [![Website](https://img.shields.io/badge/Website-paper-5B9BD5?logo=googlechrome&logoColor=white)](https://anonymous.4open.science/r/DAIRA-80AC/README.md)
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- `(2026-02)` **Closing the Loop**: Closing the Loop: Universal Repository Representation with RPG-Encoder [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2602.02084) [![Website](https://img.shields.io/badge/Website-paper-5B9BD5?logo=googlechrome&logoColor=white)](https://ayanami2003.github.io/RPG-Encoder/) [![GitHub](https://img.shields.io/badge/GitHub-repo-24292F?logo=github&logoColor=white)](https://github.com/microsoft/RPG-ZeroRepo)
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- `(2026-01)` **SWE-Tester**: SWE-Tester: Training Open-Source LLMs for Issue Reproduction in Real-World Repositories [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2601.13713)
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- `(2026-01)` **SWE-Pruner**: SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2601.16746) [![GitHub](https://img.shields.io/badge/GitHub-repo-24292F?logo=github&logoColor=white)](https://github.com/Ayanami1314/swe-pruner)
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- `(2025-12)` **GraphLocator**: GraphLocator: Graph-guided Causal Reasoning for Issue Localization [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2512.22469)
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- `(2025-11)` **InfCode**: InfCode: Adversarial Iterative Refinement of Tests and Patches for Reliable Software Issue Resolution [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2511.16004)
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- `(2025-10)` **BugPilot**: BugPilot: Complex Bug Generation for Efficient Learning of SWE Skills [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2510.19898)
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*Models trained via supervised learning*
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- `(2026-08)` **SWE-Prime**: SWE-Prime: Fewer Trajectories, Better Performance [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2608.27449)
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- `(2026-07)` **SWE-Pruner Pro**: SWE-Pruner Pro: The Coder LLM Already Knows What to Prune [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.18213) [![GitHub](https://img.shields.io/badge/GitHub-repo-24292F?logo=github&logoColor=white)](https://github.com/Ayanami1314/swe-pruner-pro)
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- `(2026-06)` **Open-SWE-Traces**: Open-SWE-Traces: Advancing Dual-Mode Multilingual Distillation for Software Engineering Agents [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2606.16038) [![HuggingFace](https://img.shields.io/badge/HuggingFace-dataset-ff7e21?logo=huggingface&logoColor=white)](https://huggingface.co/collections/nvidia/open-swe-traces)
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- `(2026-05)` **From Patches to Trajectories**: From Patches to Trajectories: Privileged Process Supervision for Software-Engineering Agents [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2605.21996)
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- `(2026-04)` **SWE-AGILE**: SWE-AGILE: A Software Agent Framework for Efficiently Managing Dynamic Reasoning Context [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2604.11716) [![GitHub](https://img.shields.io/badge/GitHub-repo-24292F?logo=github&logoColor=white)](https://github.com/KDEGroup/SWE-AGILE) [![HuggingFace](https://img.shields.io/badge/HuggingFace-dataset-ff7e21?logo=huggingface&logoColor=white)](https://huggingface.co/KDEGroup)
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- `(2026-02)` **Scale-SWE**: Immersion in the GitHub Universe: Scaling Coding Agents to Mastery [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2602.09892) [![GitHub](https://img.shields.io/badge/GitHub-repo-24292F?logo=github&logoColor=white)](https://github.com/AweAI-Team/ScaleSWE) [![HuggingFace](https://img.shields.io/badge/HuggingFace-dataset-ff7e21?logo=huggingface&logoColor=white)](https://huggingface.co/collections/AweAI-Team/scale-swe)
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- `(2026-01)` **SWE-Lego**: SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue Resolving [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2601.01426)
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- `(2026-01)` **SWE-Replay**: SWE-Replay: Efficient Test-Time Scaling for Software Engineering Agents [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2601.22129)
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- `(2026-01)` **SWE-Pruner**: SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2601.16746) [![GitHub](https://img.shields.io/badge/GitHub-repo-24292F?logo=github&logoColor=white)](https://github.com/Ayanami1314/swe-pruner)
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- `(2025-12)` **SWE-Compressor**: Context as a Tool: Context Management for Long-Horizon SWE-Agents [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2512.22087)
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- `(2025-09)` **Devstral**: Devstral: Fine-tuning Language Models for Coding Agent Applications [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2509.25193)
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- `(2025-06)` **MCTS-Refined CoT**: MCTS-Refined CoT: High-Quality Fine-Tuning Data for LLM-Based Repository Issue Resolution [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2506.12728)

‎app/data/papers_sft.yaml‎

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- short_name: SWE-Pruner Pro
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title: 'SWE-Pruner Pro: The Coder LLM Already Knows What to Prune'
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authors: Yuhang Wang, Yuling Shi, Shaoqiu Zhang, Jialiang Liang, Shilin He, Siyu
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Ye, Yuting Chen, Kai Cai, Xiaodong Gu
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year: '2026'
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venue: arXiv preprint arXiv:2607.18213
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month: 2026-07
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links:
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arxiv: https://arxiv.org/abs/2607.18213
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github: https://github.com/Ayanami1314/swe-pruner-pro
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- short_name: Open-SWE-Traces
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Engineering Agents'
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- short_name: SWE-Pruner
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title: 'SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents'
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authors: Yuhang Wang, Yuling Shi, Mo Yang, Rongrui Zhang, Shilin He, Heng Lian,
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Yuting Chen, Siyu Ye, Kai Cai, Xiaodong Gu
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year: '2026'
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venue: arXiv preprint arXiv:2601.16746
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month: 2026-01
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links:
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github: https://github.com/Ayanami1314/swe-pruner
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- short_name: SWE-Compressor
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title: 'Context as a Tool: Context Management for Long-Horizon SWE-Agents'
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authors: Shukai Liu, Jian Yang, Bo Jiang, Yizhi Li, Jinyang Guo, Xianglong Liu,

‎app/data/papers_single_agent.yaml‎

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- short_name: SWE-Pruner Pro
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title: 'SWE-Pruner Pro: The Coder LLM Already Knows What to Prune'
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authors: Yuhang Wang, Yuling Shi, Shaoqiu Zhang, Jialiang Liang, Shilin He, Siyu
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Ye, Yuting Chen, Kai Cai, Xiaodong Gu
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year: '2026'
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venue: arXiv preprint arXiv:2607.18213
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month: 2026-07
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links:
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github: https://github.com/Ayanami1314/swe-pruner-pro
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- short_name: EvoRepair
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Self-Evolution'

‎app/data/papers_tool.yaml‎

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- short_name: SWE-Pruner
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title: 'SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents'
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authors: Yuhang Wang, Yuling Shi, Mo Yang, Rongrui Zhang, Shilin He, Heng Lian,
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Yuting Chen, Siyu Ye, Kai Cai, Xiaodong Gu
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year: '2026'
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venue: arXiv preprint arXiv:2601.16746
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github: https://github.com/Ayanami1314/swe-pruner
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- short_name: GraphLocator
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authors: Wei Liu, Chao Peng, Pengfei Gao, Aofan Liu, Wei Zhang, Haiyan Zhao, Zhi

‎app/docs/admin/data.json‎

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{
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"papers": [
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}
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},
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{
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"short_name": "SWE-Pruner Pro",
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"title": "SWE-Pruner Pro: The Coder LLM Already Knows What to Prune",
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"authors": "Yuhang Wang, Yuling Shi, Shaoqiu Zhang, Jialiang Liang, Shilin He, Siyu Ye, Yuting Chen, Kai Cai, Xiaodong Gu",
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"venue": "arXiv preprint arXiv:2607.18213",
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"month": "2026-07",
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"category": "sft,single_agent",
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"links": {
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"arxiv": "https://arxiv.org/abs/2607.18213",
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},
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{
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"id": 274,
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"short_name": "Rethinking Issue Resolution for AI/ML Systems",
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"huggingface": "https://huggingface.co/collections/8sj7df9k8m5x8/docksmith"
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}
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{
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"id": 288,
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"short_name": "SWE-Pruner",
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"title": "SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents",
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"authors": "Yuhang Wang, Yuling Shi, Mo Yang, Rongrui Zhang, Shilin He, Heng Lian, Yuting Chen, Siyu Ye, Kai Cai, Xiaodong Gu",
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"venue": "arXiv preprint arXiv:2601.16746",
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"month": "2026-01",
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"category": "sft,tool",
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"links": {
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"short_name": "daVinci-Dev",

‎app/docs/index.md‎

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<a href="https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution/graphs/contributors" target="_blank">
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<img src="https://img.shields.io/github/contributors/DeepSoftwareAnalytics/Awesome-Issue-Resolution?style=for-the-badge&color=green&logo=github" alt="Contributors">
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</a>
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<img src="https://img.shields.io/badge/papers-284-green?style=for-the-badge&logo=googlescholar&logoColor=white" alt="Papers Count">
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<img src="https://img.shields.io/badge/papers-286-green?style=for-the-badge&logo=googlescholar&logoColor=white" alt="Papers Count">
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</div>
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<!-- Interactive Exploration Badges -->

‎app/docs/news.md‎

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- **LLVM-Bench**: LLVM-Bench: Benchmarking and Advancing Large Language Models for LLVM Compiler Issue Resolution [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.00700)
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- **MM-IssueLoc**: MM-IssueLoc: A Controlled Benchmark for Evaluating Visual Evidence in Multimodal Repository-Level Issue Localization [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.15205) [![GitHub](https://img.shields.io/badge/GitHub-code-181717?logo=github&logoColor=white)](https://github.com/Jasaxion/MM-IssueLoc-Bench)
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- **STAIR**: Reusing Past Repairs Through Hierarchical Trajectory Abstraction for Coding Agents [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.29658)
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- **SWE-Pruner Pro**: SWE-Pruner Pro: The Coder LLM Already Knows What to Prune [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.18213) [![GitHub](https://img.shields.io/badge/GitHub-code-181717?logo=github&logoColor=white)](https://github.com/Ayanami1314/swe-pruner-pro)
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- **SWE-Review**: SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2607.06065) [![GitHub](https://img.shields.io/badge/GitHub-code-181717?logo=github&logoColor=white)](https://github.com/SWE-Lego/SWE-Review) [![HuggingFace](https://img.shields.io/badge/HuggingFace-model-FFD21E?logo=huggingface&logoColor=black)](https://huggingface.co/collections/SWE-Lego/swe-review)
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<!-- END_RECENT_PAPERS -->
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