Datasets:
Update README.md
Browse files
README.md
CHANGED
@@ -39,4 +39,29 @@ dataset_info:
|
|
39 |
num_examples: 660
|
40 |
download_size: 3913633
|
41 |
dataset_size: 11007786
|
42 |
-
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
39 |
num_examples: 660
|
40 |
download_size: 3913633
|
41 |
dataset_size: 11007786
|
42 |
+
---
|
43 |
+
|
44 |
+
# LOC-BENCH: A Benchmark for Code Localization
|
45 |
+
|
46 |
+
<!-- Provide a quick summary of the dataset. -->
|
47 |
+
|
48 |
+
LOC-BENCH is a dataset specifically designed for evaluating code localization methods in software repositories.
|
49 |
+
LOC-BENCH provides a diverse set of issues, including bug reports, feature requests, security vulnerabilities, and performance optimizations.
|
50 |
+
|
51 |
+
## 🔧 How to Use
|
52 |
+
You can easily load LOC-BENCH using Hugging Face's datasets library:
|
53 |
+
```
|
54 |
+
from datasets import load_dataset
|
55 |
+
|
56 |
+
dataset = load_dataset("czlll/Loc-Bench")
|
57 |
+
```
|
58 |
+
## 📄 Citation
|
59 |
+
If you use LOC-BENCH in your research, please cite our paper:
|
60 |
+
```
|
61 |
+
@article{chen2025locagent,
|
62 |
+
title={LocAgent: Graph-Guided LLM Agents for Code Localization},
|
63 |
+
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},
|
64 |
+
journal={arXiv preprint arXiv:2503.09089},
|
65 |
+
year={2025}
|
66 |
+
}
|
67 |
+
```
|