A large-scale (194k), Multiple-Choice Question Answering (MCQA) dataset designed to address realworld medical entrance exam questions.
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Updated
Nov 28, 2022 - Jupyter Notebook
A large-scale (194k), Multiple-Choice Question Answering (MCQA) dataset designed to address realworld medical entrance exam questions.
Source code for our "MMM" paper at AAAI 2020
Repository for My HuggingFace Natural Language Processing Projects
[COLING 2020] BERT-based Models for Chengyu
Hong Kong Polytechnic Unversity Master degree's Natural Language Processing (COMP5523) Course project
ThinkBench is an LLM benchmarking tool focused on evaluating the effectiveness of chain-of-thought (CoT) prompting for answering multiple-choice questions.
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.
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