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🔍 xVerify-1.5B-I

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 was introduced in the paper xVerify: Efficient Answer Verifier for Reasoning Model Evaluations.

The model accurately extracts the final answer from lengthy reasoning processes and efficiently identifies equivalence across different forms of expressions, helping to evaluate reasoning models that adopt slow-thinking strategies.

✨ 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

Basic Transformations: Recognizes letter case changes and Greek letter conversions.
Mathematical Expressions: Identifies equivalent expressions across formats like LaTeX, fractions, and scientific notation.
Semantic Equivalence: Determines if natural language answers align with the correct reference.
Advanced Multiple-Choice: Matches responses by content rather than just option identifiers.

📚 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},
}

Authors: Ding Chen, Qingchen Yu, Pengyuan Wang, Wentao Zhang, Bo Tang, Feiyu Xiong, Xinchi Li, Minchuan Yang, Zhiyu Li.