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 61–70 of 555 papers

TitleStatusHype
ArabicaQA: A Comprehensive Dataset for Arabic Question AnsweringCode1
Recurrent Chunking Mechanisms for Long-Text Machine Reading ComprehensionCode1
ECONET: Effective Continual Pretraining of Language Models for Event Temporal ReasoningCode1
A Self-Training Method for Machine Reading Comprehension with Soft Evidence ExtractionCode1
A Sentence Cloze Dataset for Chinese Machine Reading ComprehensionCode1
A Unified MRC Framework for Named Entity RecognitionCode1
Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation ExtractionCode1
Asking Questions the Human Way: Scalable Question-Answer Generation from Text CorpusCode1
Biomedical named entity recognition using BERT in the machine reading comprehension frameworkCode1
JaQuAD: Japanese Question Answering Dataset for Machine Reading ComprehensionCode1
Show:102550
← PrevPage 7 of 56Next →

No leaderboard results yet.