SOTAVerified

Machine Reading Comprehension

Machine Reading Comprehension is one of the key problems in Natural Language Understanding, where the task is to read and comprehend a given text passage, and then answer questions based on it.

Source: Making Neural Machine Reading Comprehension Faster

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 231–240 of 555 papers

TitleStatusHype
Native Chinese Reader: A Dataset Towards Native-Level Chinese Machine Reading Comprehension—0
From Good to Best: Two-Stage Training for Cross-lingual Machine Reading Comprehension—0
Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-sentence Dependency GraphCode0
Models can use keywords to answer questions that human cannot—0
A Graph Fusion Approach to Cross-Lingual Machine Reading Comprehension—0
EveMRC: A Two-stage Evidence Modeling For Multi-choice Machine Reading Comprehension—0
On the Robustness of Reading Comprehension Models to Entity Renaming—0
What Makes Machine Reading Comprehension Questions Difficult? Investigating Variation in Passage Sources and Question Types—0
Understanding Attention in Machine Reading Comprehension—0
MRCLens: an MRC Dataset Bias Detection Toolkit—0
Show:102550
← PrevPage 24 of 56Next →

No leaderboard results yet.