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README.md

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-license: apache-2.0
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+# CompRealVul_LLVM Dataset
+
+[![Hugging Face](https://img.shields.io/badge/🤗%20View%20on-HuggingFace-blue)](https://huggingface.co/datasets/compAgent/CompRealVul_LLVM)
+
+## Dataset Summary
+
+**CompRealVul_LLVM** is the LLVM IR (Intermediate Representation) version of the [CompRealVul](https://huggingface.co/datasets/compAgent/CompRealVul) dataset. This version is designed specifically for **training and evaluating machine learning models** on the task of **binary vulnerability detection** in a setting that closely mimics how models are used in practice — operating on the compiled representation of code rather than raw source code.
+
+Each function in this dataset was compiled from C code to LLVM IR, enabling robust training of models on semantically rich, architecture-independent binary representations.
+
+This dataset supports research aligned with the methodology described in our paper, where the goal is to predict vulnerabilities directly from **compiled IR representations** rather than from source code.
+
+## Key Features
+
+- ✅ **LLVM IR representation** of each function (field: `llvm_ir_function`)
+- ✅ Includes **train**, **validation**, and **test** splits
+- ✅ Vulnerability labels (`label`) for supervised learning
+- ✅ Metadata about original source (`dataset`, `file`, `fun_name`)
+- ✅ Structured as **Parquet** files for fast loading and processing
+
+## Dataset Structure
+
+Each record contains:
+
+- `dataset`: Original dataset source of the function (e.g., Juliet, NVD)
+- `file`: File path of the source from which the function was extracted
+- `fun_name`: Name of the function in the source code
+- `llvm_ir_function`: LLVM IR string representing the function
+- `label`: Binary label indicating vulnerability (`1` for vulnerable, `0` for non-vulnerable)
+- `split`: Dataset split (`train`, `validation`, `test`)
+
+## Format
+
+This dataset is provided in [Apache Parquet](https://parquet.apache.org/) format under the `default` configuration. It follows the [Croissant schema](https://mlcommons.org/croissant/) and includes three predefined splits.
+
+## Usage
+
+You can load and explore the dataset using the 🤗 `datasets` library:
+
+```python
+from datasets import load_dataset
+
+# Load a specific split
+train_ds = load_dataset("compAgent/CompRealVul_LLVM", split="train")
+print(train_ds[0])
+```
+
+## Example
+```json
+{
+  "dataset": "Juliet",
+  "file": "CWE121/s01.c",
+  "fun_name": "bad_function",
+  "llvm_ir_function": "define dso_local i32 @bad_function() #0 { ... }",
+  "label": "1",
+  "split": "train"
+}
+```
+
+## License
+This dataset is released under the Apache 2.0 License.
+
+## Citation
+```cite
+@misc{comprealvul_llvm,
+  author       = {comp agent},
+  title        = {CompRealVul_LLVM: A Dataset of Vulnerable and Non-Vulnerable Functions in LLVM IR},
+  howpublished = {\url{https://huggingface.co/datasets/compAgent/CompRealVul_LLVM}},
+  year         = {2025}
+}
+```