About

Most current question answering datasets frame the task as reading comprehension where the question is about a paragraph or document and the answer often is a span in the document. The Machine Reading group at UCL also provides an overview of reading comprehension tasks.

Benchmarks

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Subtasks

Datasets

Latest papers with code

ExpMRC: Explainability Evaluation for Machine Reading Comprehension

10 May 2021ymcui/ExpMRC

Achieving human-level performance on some of Machine Reading Comprehension (MRC) datasets is no longer challenging with the help of powerful Pre-trained Language Models (PLMs).

MACHINE READING COMPREHENSION MULTI-CHOICE MRC SPAN-EXTRACTION MRC

8
10 May 2021

REPT: Bridging Language Models and Machine Reading Comprehensionvia Retrieval-Based Pre-training

10 May 2021SparkJiao/retrieval-based-mrc-pretraining

Pre-trained Language Models (PLMs) have achieved great success on Machine Reading Comprehension (MRC) over the past few years.

MACHINE READING COMPREHENSION

0
10 May 2021

Lawformer: A Pre-trained Language Model for Chinese Legal Long Documents

9 May 2021thunlp/LegalPLMs

Legal artificial intelligence (LegalAI) aims to benefit legal systems with the technology of artificial intelligence, especially natural language processing (NLP).

LANGUAGE MODELLING QUESTION ANSWERING READING COMPREHENSION

2
09 May 2021

MRCBert: A Machine Reading ComprehensionApproach for Unsupervised Summarization

1 May 2021saurabhhssaurabh/reviews_summarization

We demonstrated our results on reviews of a product from the Electronics category in the Amazon Reviews dataset.

DECISION MAKING MACHINE READING COMPREHENSION TRANSFER LEARNING

0
01 May 2021

NT5?! Training T5 to Perform Numerical Reasoning

15 Apr 2021lesterpjy/numeric-t5

Numerical reasoning over text (NRoT) presents unique challenges that are not well addressed by existing pre-training objectives.

READING COMPREHENSION

6
15 Apr 2021

Evaluating Explanations for Reading Comprehension with Realistic Counterfactuals

9 Apr 2021xiye17/EvalQAExpl

Token-level attributions have been extensively studied to explain model predictions for a wide range of classification tasks in NLP (e. g., sentiment analysis), but such explanation techniques are less explored for machine reading comprehension (RC) tasks.

MACHINE READING COMPREHENSION SENTIMENT ANALYSIS

8
09 Apr 2021

ReCAM@IITK at SemEval-2021 Task 4: BERT and ALBERT based Ensemble for Abstract Word Prediction

4 Apr 2021amittal151/SemEval-2021-Task4_models

We fine-tuned the pre-trained masked language models namely BERT and ALBERT and used an Ensemble of these as our submitted system on Subtask 1 (ReCAM-Imperceptibility) and Subtask 2 (ReCAM-Nonspecificity).

LANGUAGE MODELLING READING COMPREHENSION

0
04 Apr 2021

XRJL-HKUST at SemEval-2021 Task 4: WordNet-Enhanced Dual Multi-head Co-Attention for Reading Comprehension of Abstract Meaning

30 Mar 2021zzshou/RCAM

This paper presents our submitted system to SemEval 2021 Task 4: Reading Comprehension of Abstract Meaning.

LANGUAGE MODELLING READING COMPREHENSION

5
30 Mar 2021

Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet Extraction

13 Mar 2021NKU-IIPLab/BMRC

Aspect sentiment triplet extraction (ASTE), which aims to identify aspects from review sentences along with their corresponding opinion expressions and sentiments, is an emerging task in fine-grained opinion mining.

ASPECT SENTIMENT TRIPLET EXTRACTION MACHINE READING COMPREHENSION OPINION MINING

7
13 Mar 2021

AnswerQuest: A System for Generating Question-Answer Items from Multi-Paragraph Documents

5 Mar 2021roemmele/answerquest

One strategy for facilitating reading comprehension is to present information in a question-and-answer format.

QUESTION ANSWERING QUESTION GENERATION READING COMPREHENSION

7
05 Mar 2021