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 361–370 of 555 papers

TitleStatusHype
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approaches—0
A Constituent-Centric Neural Architecture for Reading Comprehension—0
Adaptations of ROUGE and BLEU to Better Evaluate Machine Reading Comprehension Task—0
Adaptive Bi-directional Attention: Exploring Multi-Granularity Representations for Machine Reading Comprehension—0
A Data-centric Framework for Improving Domain-specific Machine Reading Comprehension Datasets—0
Addressing Semantic Drift in Generative Question Answering with Auxiliary Extraction—0
A Deep Cascade Model for Multi-Document Reading Comprehension—0
Adversarial Domain Adaptation for Machine Reading Comprehension—0
Adversarial reading networks for machine comprehension—0
Adversarial Training for Machine Reading Comprehension with Virtual Embeddings—0
Show:102550
← PrevPage 37 of 56Next →

No leaderboard results yet.