Update README.md

README.md

@@ -41,3 +41,46 @@ configs:
   - split: test
     path: data/test-*
 ---
+
+# LOC-BENCH: A Benchmark for Code Localization
+
+<!-- Provide a quick summary of the dataset. -->
+LOC-BENCH is a dataset specifically designed for evaluating code localization methods in software repositories. 
+LOC-BENCH provides a diverse set of issues, including bug reports, feature requests, security vulnerabilities, and performance optimizations.
+
+To reproduce the results reported in the [paper](https://arxiv.org/abs/2503.09089), please refer to [`czlll/Loc-Bench_V0`](https://huggingface.co/datasets/czlll/Loc-Bench_V0).
+
+Loc-Bench is a refined benchmark for evaluating code localization methods.
+Compared to the V0, it improves data quality by filtering out examples that do not involve any function-level code modifications.
+We recommend using this dataset for a more accurate and reliable evaluation of code localization performance.
+
+The table below shows the distribution of categories in the dataset.
+
+| category | count |
+|:---------|:---------|
+| Bug Report  | 242  |
+| Feature Request  | 150  |
+| Performance Issue  | 139  |
+| Security Vulnerability  | 29  |
+
+
+Code: https://github.com/gersteinlab/LocAgent
+
+## 🔧 How to Use
+You can easily load LOC-BENCH using Hugging Face's datasets library:
+```
+from datasets import load_dataset
+
+dataset = load_dataset("czlll/Loc-Bench_V1", split="test")
+
+```
+## 📄 Citation
+If you use LOC-BENCH in your research, please cite our paper:
+```
+@article{chen2025locagent,
+title={LocAgent: Graph-Guided LLM Agents for Code Localization},
+author={Chen, Zhaoling and Tang,Xiangru and Deng,Gangda and Wu,Fang and Wu,Jialong and Jiang,Zhiwei and Prasanna,Viktor and Cohan,Arman and Wang,Xingyao},
+journal={arXiv preprint arXiv:2503.09089},
+year={2025}
+}
+```