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<!DOCTYPE html>
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<title>IPEval: A Bilingual Intellectual Property Agency Consultation Evaluation Benchmark for Large Language Models</title>
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<h1 class="title is-1 publication-title">IPEval: A Bilingual Intellectual Property Agency Consultation Evaluation Benchmark for Large Language Models</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://Qiyao-Wang.github.io">Qiyao Wang</a><sup>1</sup>,</span>
<span class="author-block">
Jianguo Huang<sup>1</sup>,</span>
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Shule Lu<sup>1</sup>,</span>
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<span class="author-block">
Yuan Lin<sup>1*</sup>,</span>
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<span class="author-block">
Kan Xu<sup>1</sup>,</span>
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<span class="author-block">
Liang Yang<sup>1</sup>,</span>
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<span class="author-block">
Hongfei Lin<sup>1</sup>,</span>
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<span class="author-block"><sup>1</sup>Dalian University of Technology</span>
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<h2 class="title is-3">Abstract</h2>
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<p>
IPEval is a pioneering bilingual Intellectual Property (IP) agency consultation evaluation benchmark, meticulously crafted to assess the competencies of Large Language Models (LLMs) in the intricate domain of intellectual property. This benchmark is the first of its kind, encompassing a diverse spectrum of 2,657 multiple-choice questions that are intricately divided across four major capability dimensions: creation, application, protection, and management.
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<pre><code>@article{wang2024ipeval,
title={IPEval: A Bilingual Intellectual Property Agency Consultation Evaluation Benchmark for Large Language Models},
author={Wang, Qiyao and Huang, Jianguo and Lu, Shule and Lin, Yuan and Xu, Kan and Yang, Liang and Lin, Hongfei},
journal={arXiv preprint arXiv:2406.12386},
year={2024}
}</code></pre>
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