---
inference: false
language:
- en
- zh
tags:
- instruction-finetuning
task_categories:
- text-generation
base_model:
- meta-llama/Llama-3.2-3B-Instruct
license: cc-by-nc-nd-4.0
---

<h1 align="center">
🔍 xVerify-3B-Ia
</h1>

<p align="center">
  <div style="display: flex; justify-content: center; gap: 10px;">
    <a href="https://github.com/IAAR-Shanghai/xVerify">
      <img src="https://img.shields.io/badge/GitHub-Repository-blue?logo=github" alt="GitHub"/>
    </a>
    <a href="https://huggingface.co/IAAR-Shanghai/xVerify-3B-Ia">
      <img src="https://img.shields.io/badge/🤗%20Hugging%20Face-xVerify--3B--Ia-yellow" alt="Hugging Face"/>
    </a>
  </div>
</p>


xVerify is an evaluation tool fine-tuned from a pre-trained large language model, designed specifically for objective questions with a single correct answer. It accurately extracts the final answer from lengthy reasoning processes and efficiently identifies equivalence across different forms of expressions.

---

## ✨ Key Features

### 📊 Broad Applicability
Suitable for various objective question evaluation scenarios including math problems, multiple-choice questions, classification tasks, and short-answer questions.

### ⛓️ Handles Long Reasoning Chains
Effectively processes answers with extensive reasoning steps to extract the final answer, regardless of complexity.

### 🌐 Multilingual Support
Primarily handles Chinese and English responses while remaining compatible with other languages.

### 🔄 Powerful Equivalence Judgment
- ✓ Recognizes basic transformations like letter case changes and Greek letter conversions
- ✓ Identifies equivalent mathematical expressions across formats (LaTeX, fractions, scientific notation)
- ✓ Determines semantic equivalence in natural language answers
- ✓ Matches multiple-choice responses by content rather than just option identifiers

---


## 📚 Citation

```bibtex
@article{xVerify,
      title={xVerify: Efficient Answer Verifier for Reasoning Model Evaluations}, 
      author={Ding Chen and Qingchen Yu and Pengyuan Wang and Wentao Zhang and Bo Tang and Feiyu Xiong and Xinchi Li and Minchuan Yang and Zhiyu Li},
      journal={arXiv preprint arXiv:2504.10481},
      year={2025},
}
```