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README.md

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[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://github.com/IINemo/lm-polygraph/blob/master/LICENSE.md)
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![Python 3.11](https://img.shields.io/badge/python-3.11-blue.svg)
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[![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97-Benchmark-yellow)](https://huggingface.co/LM-Polygraph)
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<a href="https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00737/128713/Benchmarking-Uncertainty-Quantification-Methods" target="_blank"><img src=https://img.shields.io/badge/TACL-2025-blue.svg></a>
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<a href="https://arxiv.org/pdf/2406.15627" target="_blank"><img src=https://img.shields.io/badge/arXiv-b5212f.svg></a>
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# LM-Polygraph: Uncertainty estimation for LLMs
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<table align="left">
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<tr>
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<td valign="middle">
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<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/605a2d14768f56df182c99e2/uHMVA4vBitbtP7l1K2wIg.png"
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alt="LM-Polygraph logo"
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width="110"
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style="margin-right: 0px;">
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</td>
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<td valign="middle">
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<h1 style="margin: 0; line-height: 1.1;">
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LM-Polygraph: Uncertainty estimation for LLMs
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</h1>
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</td>
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</tr>
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</table>
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<br clear="all"/>
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<p align="left">
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<a href="https://github.com/IINemo/lm-polygraph/blob/master/LICENSE.md">
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<img src="https://img.shields.io/badge/License-MIT-green.svg" alt="License: MIT"/>
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</a>
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<img src="https://img.shields.io/badge/python-3.11-blue.svg" alt="Python 3.11"/>
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<a href="https://huggingface.co/LM-Polygraph">
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<img src="https://img.shields.io/badge/%F0%9F%A4%97-Benchmark-yellow" alt="Hugging Face Benchmark"/>
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</a>
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<a href="https://2023.emnlp.org/" target="_blank" rel="noopener noreferrer">
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<img
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src="https://img.shields.io/badge/EMNLP-2023-red?logo=bookstack&logoColor=white"
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alt="EMNLP 2023"
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/>
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</a>
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<a href="https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00737/128713/Benchmarking-Uncertainty-Quantification-Methods" target="_blank">
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<img src="https://img.shields.io/badge/TACL-2025-blue?logo=bookstack&logoColor=white" alt="TACL 2025"/>
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</a>
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<a href="https://sites.google.com/view/acl2025-uncertainty-for-llms/">
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<img src="https://img.shields.io/badge/ACL-2025-red?logo=googlescholar&logoColor=white" alt="Tutorial ACL 2025"/>
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</a>
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</p>
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[Installation](#installation) | [Basic usage](#basic_usage) | [Overview](#overview_of_methods) | [Benchmark](#benchmark) | [Demo application](#demo_web_application) | [Documentation](https://lm-polygraph.readthedocs.io/)
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## Cite
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**TACL-2025:**
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**TACL-2025 paper:**
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```
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@article{shelmanovvashurin2025,
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author = {Vashurin, Roman and Fadeeva, Ekaterina and Vazhentsev, Artem and Rvanova, Lyudmila and Vasilev, Daniil and Tsvigun, Akim and Petrakov, Sergey and Xing, Rui and Sadallah, Abdelrahman and Grishchenkov, Kirill and Panchenko, Alexander and Baldwin, Timothy and Nakov, Preslav and Panov, Maxim and Shelmanov, Artem},
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}
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```
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**ACL-2025 Tutorial:**
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```
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@inproceedings{shelmanov-etal-2025-uncertainty,
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title = "Uncertainty Quantification for Large Language Models",
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author = "Shelmanov, Artem and
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Panov, Maxim and
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Vashurin, Roman and
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Vazhentsev, Artem and
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Fadeeva, Ekaterina and
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Baldwin, Timothy",
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editor = "Arase, Yuki and
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Jurgens, David and
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Xia, Fei",
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booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 5: Tutorial Abstracts)",
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month = jul,
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year = "2025",
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address = "Vienna, Austria",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2025.acl-tutorials.3/",
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doi = "10.18653/v1/2025.acl-tutorials.3",
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pages = "3--4",
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ISBN = "979-8-89176-255-8"
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}
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```
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**EMNLP-2023 paper:**
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```
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@inproceedings{fadeeva-etal-2023-lm,

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