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IAAR-Shanghai/xVerify-14B-Ia
xVerify-14B-Ia is a text generation model from IAAR-Shanghai. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as cc-by-nc-nd-4.0.
<h1 align="center" 🔍 xVerify-14B-Ia </h1
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From the Hugging Face model README
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.
Suitable for various objective question evaluation scenarios including math problems, multiple-choice questions, classification tasks, and short-answer questions.
Effectively processes answers with extensive reasoning steps to extract the final answer, regardless of complexity.
Primarily handles Chinese and English responses while remaining compatible with other languages.
To use xVerify for answer verification, you can follow the implementation provided in the official GitHub repository. Below is an example of single-sample evaluation:
from src.xVerify.model import Model
from src.xVerify.eval import Evaluator
# initialization
model_name = 'xVerify-14B-Ia'
model_path = 'IAAR-Shanghai/xVerify-14B-Ia'
inference_mode = 'local' # or 'api'
model = Model(
model_name=model_name,
model_path_or_url=model_path,
inference_mode=inference_mode
)
evaluator = Evaluator(model=model)
# input evaluation information
question = "In which year did Fayaz A. Malik receive the Young Scientist of the Year from the Council of Scientific and Industrial Research?"
llm_output = "The year Fayaz A. Malik received the Young Scientist of the Year award from the Council of Scientific and Industrial Research was 2001.
The answer is 2001."
correct_answer = "2009"
# evaluation
result = evaluator.single_evaluate(
question=question,
llm_output=llm_output,
correct_answer=correct_answer
)
print(result) # Output: Incorrect
@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},
}