docs: update papers

Author: NoraNotDora

README.md

@@ -12,7 +12,7 @@
 [![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)
 [![Tables](https://img.shields.io/badge/TABLES-Statistics-blue?style=for-the-badge&logo=databricks)](https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/tables/)
 [![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)
-![Papers Count](https://img.shields.io/badge/papers-178-green?style=for-the-badge&logo=googlescholar&logoColor=white)
+![Papers Count](https://img.shields.io/badge/papers-181-green?style=for-the-badge&logo=googlescholar&logoColor=white)
 
 [**📖 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/)
 
@@ -32,7 +32,7 @@
 
 ## 📖 Abstract
 
-Based on a systematic review of **178 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. 
+Based on a systematic review of **181 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. 
 
 <!-- START EXPLORE -->
 **🔍 Explore This Survey:**
@@ -67,7 +67,7 @@ Based on a systematic review of **178 papers and online resources**, this survey
 ## 📚 Complete Paper List
 
 
-> **Total: 178 works** across 14 categories
+> **Total: 181 works** across 14 categories
 
 
 ### 📊 Evaluation Datasets
@@ -118,6 +118,7 @@ Based on a systematic review of **178 papers and online resources**, this survey
 - **RepoForge**: RepoForge: Training a SOTA Fast-thinking SWE Agent with an End-to-End Data Curation Pipeline Synergizing SFT and RL at Scale (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2508.01550)
 - **SWE-Mirror**: SWE-Mirror: Scaling Issue-Resolving Datasets by Mirroring Issues Across Repositories (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2509.08724)
 - **SWE-Lego**: SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue Resolving (2026) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2601.01426)
+- **SWE-Universe**: SWE-Universe: Scale Real-World Verifiable Environments to Millions (2026) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://www.arxiv.org/abs/2602.02361)
 
 ### 🤖 Single-Agent Systems
 
@@ -211,6 +212,7 @@ Based on a systematic review of **178 papers and online resources**, this survey
 - **InfCode**: InfCode: Adversarial Iterative Refinement of Tests and Patches for Reliable Software Issue Resolution (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2511.16004)
 - **GraphLocator**: GraphLocator: Graph-guided Causal Reasoning for Issue Localization (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2512.22469)
 - **SWE-Tester**: SWE-Tester: Training Open-Source LLMs for Issue Reproduction in Real-World Repositories (2026) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2601.13713)
+- **Closing the Loop**: Closing the Loop: Universal Repository Representation with RPG-Encoder (2026) [![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)
 
 ### 🧠 Memory-Enhanced Methods
 
@@ -311,6 +313,7 @@ Based on a systematic review of **178 papers and online resources**, this survey
 - **SWE-MERA**: SWE-MERA: A Dynamic Benchmark for Agenticly Evaluating Large Language Models on Software Engineering Tasks (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2507.11059)
 - **RepoForge**: RepoForge: Training a SOTA Fast-thinking SWE Agent with an End-to-End Data Curation Pipeline Synergizing SFT and RL at Scale (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2508.01550)
 - **Multi-Docker-Eval**: Multi-Docker-Eval: A `Shovel of the Gold Rush' Benchmark on Automatic Environment Building for Software Engineering (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2512.06915)
+- **DockSmith**: DockSmith: Scaling Reliable Coding Environments via an Agentic Docker Builder (2026) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2602.00592) [![HuggingFace](https://img.shields.io/badge/HuggingFace-dataset-ff7e21?logo=huggingface&logoColor=white)](https://huggingface.co/collections/8sj7df9k8m5x8/docksmith)
 
 ### 🔬 Data Synthesis Methods
 

data/papers_data_collection.yaml

@@ -1,6 +1,3 @@
-# Data Collection
-# Auto-generated from taxonomy.tex and BibTeX file
-
 - short_name: SWE-rebench
   title: 'SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated
     Evaluation of Software Engineering Agents'
@@ -56,3 +53,13 @@
   venue: arXiv preprint arXiv:2512.06915 2025
   links:
     arxiv: https://arxiv.org/abs/2512.06915
+- short_name: DockSmith
+  title: 'DockSmith: Scaling Reliable Coding Environments via an Agentic Docker Builder'
+  authors: Jiaran Zhang, Luck Ma, Yanhao Li, Fanqi Wan, Di Qi, Xu Zhao, Jieyi Hou,
+    Zhe Xie, Mengqiang Ren, Xin Wu, Zhewei Huang, Liangyu Chen, Yingwei Ma, Qi Han,
+    Xiangyu Zhang
+  venue: arXiv preprint arXiv:2602.00592
+  year: '2026'
+  links:
+    arxiv: https://arxiv.org/abs/2602.00592
+    huggingface: https://huggingface.co/collections/8sj7df9k8m5x8/docksmith

data/papers_tool.yaml

@@ -300,3 +300,13 @@
   year: '2026'
   links:
     arxiv: https://arxiv.org/abs/2601.13713
+- short_name: Closing the Loop
+  title: 'Closing the Loop: Universal Repository Representation with RPG-Encoder'
+  authors: Jane Luo, Chengyu Yin, Xin Zhang, Qingtao Li, Steven Liu, Yiming Huang,
+    Jie Wu, Hao Liu, Yangyu Huang, Yu Kang, Fangkai Yang, Ying Xin, Scarlett Li
+  venue: arXiv preprint arXiv:2602.02084
+  year: '2026'
+  links:
+    arxiv: https://arxiv.org/abs/2602.02084
+    github: https://github.com/microsoft/RPG-ZeroRepo
+    website: https://ayanami2003.github.io/RPG-Encoder/

data/papers_training_datasets.yaml

@@ -1,6 +1,3 @@
-# Training Datasets
-# Auto-generated from taxonomy.tex and BibTeX file
-
 - short_name: SWE-bench-extra
   title: 'SWE-bench: Can Language Models Resolve Real-world Github Issues?'
   authors: Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei,
@@ -123,3 +120,12 @@
   venue: arXiv preprint arXiv:2601.01426 2026
   links:
     arxiv: https://arxiv.org/abs/2601.01426
+- short_name: SWE-Universe
+  title: 'SWE-Universe: Scale Real-World Verifiable Environments to Millions'
+  authors: Mouxiang Chen, Lei Zhang, Yunlong Feng, Xuwu Wang, Wenting Zhao, Ruisheng
+    Cao, Jiaxi Yang, Jiawei Chen, Mingze Li, Zeyao Ma, Hao Ge, Zongmeng Zhang, Zeyu
+    Cui, Dayiheng Liu, Jingren Zhou, Jianling Sun, Junyang Lin, Binyuan Hui
+  venue: arXiv preprint arXiv:2602.02361
+  year: '2026'
+  links:
+    arxiv: https://www.arxiv.org/abs/2602.02361

docs/about.md

@@ -2,7 +2,7 @@
 
 ## About This Project
 
-Based on a systematic review of 178 papers and online resources, this project establishes a holistic theoretical framework for Issue Resolution in software engineering. This website is designed to facilitate efficient literature retrieval and exploration.
+Based on a systematic review of 181 papers and online resources, this project establishes a holistic theoretical framework for Issue Resolution in software engineering. This website is designed to facilitate efficient literature retrieval and exploration.
 
 
 ---

docs/index.md

@@ -30,7 +30,7 @@
         <a href="https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution/graphs/contributors" target="_blank">
             <img src="https://img.shields.io/github/contributors/DeepSoftwareAnalytics/Awesome-Issue-Resolution?style=for-the-badge&color=green&logo=github" alt="Contributors">
         </a>
-        <img src="https://img.shields.io/badge/papers-178-green?style=for-the-badge&logo=googlescholar&logoColor=white" alt="Papers Count">
+        <img src="https://img.shields.io/badge/papers-181-green?style=for-the-badge&logo=googlescholar&logoColor=white" alt="Papers Count">
     </div>
 
     <!-- Interactive Exploration Badges -->
@@ -57,7 +57,7 @@
 
 <div class="abstract-content" markdown="1">
 
-Based on a systematic review of 178 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](https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution) and project documentation website. 
+Based on a systematic review of 181 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](https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution) and project documentation website. 
 
 **🔍 Explore This Survey:**
 
@@ -128,6 +128,7 @@ This section covers the datasets used for evaluation and training, as well as me
 * **RepoForge**: RepoForge: Training a SOTA Fast-thinking SWE Agent with an End-to-End Data Curation Pipeline Synergizing SFT and RL at Scale (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2508.01550){: target="_blank" }
 * **SWE-Mirror**: SWE-Mirror: Scaling Issue-Resolving Datasets by Mirroring Issues Across Repositories (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2509.08724){: target="_blank" }
 * **SWE-Lego**: SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue Resolving (2026) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2601.01426){: target="_blank" }
+* **SWE-Universe**: SWE-Universe: Scale Real-World Verifiable Environments to Millions (2026) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://www.arxiv.org/abs/2602.02361){: target="_blank" }
 <!-- END PAPERS:training_datasets -->
 
 ### Data Collection
@@ -139,6 +140,7 @@ This section covers the datasets used for evaluation and training, as well as me
 * **SWE-MERA**: SWE-MERA: A Dynamic Benchmark for Agenticly Evaluating Large Language Models on Software Engineering Tasks (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2507.11059){: target="_blank" }
 * **RepoForge**: RepoForge: Training a SOTA Fast-thinking SWE Agent with an End-to-End Data Curation Pipeline Synergizing SFT and RL at Scale (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2508.01550){: target="_blank" }
 * **Multi-Docker-Eval**: Multi-Docker-Eval: A `Shovel of the Gold Rush' Benchmark on Automatic Environment Building for Software Engineering (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2512.06915){: target="_blank" }
+* **DockSmith**: DockSmith: Scaling Reliable Coding Environments via an Agentic Docker Builder (2026) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2602.00592){: target="_blank" } [![HuggingFace](https://img.shields.io/badge/HuggingFace-dataset-ff7e21?logo=huggingface&logoColor=white)](https://huggingface.co/collections/8sj7df9k8m5x8/docksmith){: target="_blank" }
 <!-- END PAPERS:data_collection -->
 
 ### Data Synthesis
@@ -251,6 +253,7 @@ This section covers both training-free and training-based methods for issue reso
 * **InfCode**: InfCode: Adversarial Iterative Refinement of Tests and Patches for Reliable Software Issue Resolution (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2511.16004){: target="_blank" }
 * **GraphLocator**: GraphLocator: Graph-guided Causal Reasoning for Issue Localization (2025) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2512.22469){: target="_blank" }
 * **SWE-Tester**: SWE-Tester: Training Open-Source LLMs for Issue Reproduction in Real-World Repositories (2026) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2601.13713){: target="_blank" }
+* **Closing the Loop**: Closing the Loop: Universal Repository Representation with RPG-Encoder (2026) [![arXiv](https://img.shields.io/badge/arXiv-paper-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2602.02084){: target="_blank" } [![Website](https://img.shields.io/badge/Website-paper-5B9BD5?logo=googlechrome&logoColor=white)](https://ayanami2003.github.io/RPG-Encoder/){: target="_blank" } [![GitHub](https://img.shields.io/badge/GitHub-repo-24292F?logo=github&logoColor=white)](https://github.com/microsoft/RPG-ZeroRepo){: target="_blank" }
 <!-- END PAPERS:tool -->
 
 #### Memory

site/about/index.html

@@ -704,7 +704,7 @@
 
 <h1 id="about">About<a class="headerlink" href="#about" title="Permanent link">&para;</a></h1>
 <h2 id="about-this-project">About This Project<a class="headerlink" href="#about-this-project" title="Permanent link">&para;</a></h2>
-<p>Based on a systematic review of 178 papers and online resources, this project establishes a holistic theoretical framework for Issue Resolution in software engineering. This website is designed to facilitate efficient literature retrieval and exploration.</p>
+<p>Based on a systematic review of 181 papers and online resources, this project establishes a holistic theoretical framework for Issue Resolution in software engineering. This website is designed to facilitate efficient literature retrieval and exploration.</p>
 <hr />
 <h2 id="key-features">Key Features<a class="headerlink" href="#key-features" title="Permanent link">&para;</a></h2>
 <ul>