Update README.md

README.md

@@ -44,27 +44,28 @@ configs:
 
 # 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.
+LOC-BENCH is a dataset specifically designed to evaluate code localization methods in software repositories. LOC-BENCH provides diverse 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).
+Code: https://github.com/gersteinlab/LocAgent
 
-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.
+## 📊 Details
+[`Loc-Bench_V1`](https://huggingface.co/datasets/czlll/Loc-Bench_V1) is our official dataset for easy comparison with our approach.
 
 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  |
+<details>
+  <summary>Previous Versions</summary>
 
-
-Code: https://github.com/gersteinlab/LocAgent
+  - [`Loc-Bench_V0.1`](https://huggingface.co/datasets/czlll/Loc-Bench_V0.1): The dataset used in [the early version of our paper](https://arxiv.org/abs/2503.09089).
+  Some examples in this dataset do not involve function-level code modifications but instead focus on modifying classes.
+  V1 filters out 100 examples without function-level code modifications, creating a cleaner subset of the dataset.
+  - [`Loc-Bench_V0.2`](https://huggingface.co/datasets/czlll/Loc-Bench_V0.2): Filtering out examples that do not involve function-level code modifications and then supplementing the dataset to restore it to the original size of 660 examples.
+</details>
 
 ## 🔧 How to Use
 You can easily load LOC-BENCH using Hugging Face's datasets library:
@@ -74,6 +75,7 @@ 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:
 ```