declare-lab/TEAM
Our EMNLP 2022 paper on MCQA
This project helps natural language processing researchers evaluate multi-choice question answering (MCQA) models. It takes pre-processed datasets for MCQA tasks and outputs model accuracy scores and predictions for analysis. The primary users are academic or industry researchers working on advanced NLP models.
No commits in the last 6 months.
Use this if you are an NLP researcher benchmarking different approaches to multi-choice question answering tasks, especially those exploring binary classification methods.
Not ideal if you are looking for a plug-and-play solution for general text classification or an application-level tool for end-users.
Stars
23
Forks
3
Language
Python
License
MIT
Category
Last pushed
Jan 15, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/declare-lab/TEAM"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
cdqa-suite/cdQA
⛔ [NOT MAINTAINED] An End-To-End Closed Domain Question Answering System.
AMontgomerie/question_generator
An NLP system for generating reading comprehension questions
KristiyanVachev/Leaf-Question-Generation
Easy to use and understand multiple-choice question generation algorithm using T5 Transformers.
robinniesert/kaggle-google-quest
Google QUEST Q&A Labeling Kaggle Competition 6th Place Solution
cooelf/AwesomeMRC
IJCAI 2021 Tutorial & code for Retrospective Reader for Machine Reading Comprehension (AAAI 2021)