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 71–80 of 555 papers

TitleStatusHype
FinBERT-MRC: financial named entity recognition using BERT under the machine reading comprehension paradigmCode1
From Machine Reading Comprehension to Dialogue State Tracking: Bridging the GapCode1
A Multi-turn Machine Reading Comprehension Framework with Rethink Mechanism for Emotion-Cause Pair ExtractionCode1
Biomedical named entity recognition using BERT in the machine reading comprehension frameworkCode1
ChroniclingAmericaQA: A Large-scale Question Answering Dataset based on Historical American Newspaper PagesCode1
Interactive Machine Comprehension with Dynamic Knowledge GraphsCode1
ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin InformationCode1
KELM: Knowledge Enhanced Pre-Trained Language Representations with Message Passing on Hierarchical Relational GraphsCode1
Multitask Pre-training of Modular Prompt for Chinese Few-Shot LearningCode1
Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading ComprehensionCode0
Show:102550
← PrevPage 8 of 56Next →

No leaderboard results yet.