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.
This model was presented in the paper xVerify: Efficient Answer Verifier for Reasoning Model Evaluations.
✨ 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
🚀 Usage
For detailed instructions on environment setup, model deployment (via vLLM), and evaluation using the VAR dataset, please refer to the official GitHub repository.
📚 Citation
@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},
}