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#

multiple-choice-question-answering

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A large-scale (194k), Multiple-Choice Question Answering (MCQA) dataset designed to address realworld medical entrance exam questions.

  • UpdatedNov 28, 2022
  • Jupyter Notebook

Source code for our "MMM" paper at AAAI 2020

  • UpdatedMay 4, 2020
  • Python
ChengyuBERT

[COLING 2020] BERT-based Models for Chengyu

  • UpdatedDec 29, 2021
  • Python

ThinkBench is an LLM benchmarking tool focused on evaluating the effectiveness of chain-of-thought (CoT) prompting for answering multiple-choice questions.

  • UpdatedJul 1, 2024
  • Python

Hong Kong Polytechnic Unversity Master degree's Natural Language Processing (COMP5523) Course project

  • UpdatedMay 7, 2024
  • Jupyter Notebook

The web app is designed for generating multiple-choice questions from text input. Users can either type text directly or upload `.txt` files to create questions. The application also offers options to download the generated questions in PDF or Word format.

  • UpdatedAug 17, 2024
  • Python

NLP project on multiple choice question answering on the QASC dataset

  • UpdatedSep 25, 2024
  • Jupyter Notebook

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