BI-DIRECTIONAL ATTENTION FLOW FOR MACHINE COMPREHENSION
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Updated
Mar 25, 2019 - Python
BI-DIRECTIONAL ATTENTION FLOW FOR MACHINE COMPREHENSION
A PyTorch implementation of Neural Ranker-Reader model for Machine Reading Comprehension
Cooking Recipe MRC using PEFT techniques
Решение, занимающее 28/184 место в отборочном контесте ONTI "AI" на датасете MuSeRC.
Self Question-answering: Aspect-based Sentiment Analysis by Role Flipped Machine Reading Comprehension
KorSQuAD-pl provides transfer learning codes about korean dataset KorQuAD and english dataset SQuAD for extractive question answering. KorSQuAD-pl implemented through pytorch lightning.
Machine Comprehension on Squad Dataset using Match-LSTM + Ans-Ptr Network
This is a simple platform for labeling answers to questions in an article.
CS Bachelor Thesis. Open Domain Question Answering System that tries to answer general topic questions fetching from wikipedia.
Fine-tuning Question Answering models on German with the GermanQuAD dataset
The official implementation for ACL 2021 "Challenges in Information Seeking QA: Unanswerable Questions and Paragraph Retrieval".
a new large-scale challenging dataset for CLRC (Cross-Lingual Reading Comprehension)
Source Code for "Teaching Machine Comprehension with Compositional Explanations" (Findings of EMNLP 2020)
MRC question and answer approach using NLP and machine learning techniques
Endeavour to make full use of hierarchical information to extract span from product reviews for user questions
Building a machine reading comprehension system using pretrained model bert.
A solutions for https://onti2020.ai-academy.ru by @otter18
[JCSCE-2021] ViMRC - VLSP 2021: Improving Retrospective Reader for Vietnamese Machine Reading Comprehension
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