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
ComQA:Compositional Question Answering via Hierarchical Graph Neural NetworksCode1
Context-faithful Prompting for Large Language ModelsCode1
A Multi-turn Machine Reading Comprehension Framework with Rethink Mechanism for Emotion-Cause Pair ExtractionCode1
Coreference Resolution as Query-based Span PredictionCode1
Document Modeling with Graph Attention Networks for Multi-grained Machine Reading ComprehensionCode1
DUMA: Reading Comprehension with Transposition ThinkingCode1
ESTER: A Machine Reading Comprehension Dataset for Event Semantic Relation ReasoningCode1
Connecting Attributions and QA Model Behavior on Realistic CounterfactualsCode1
A Unified MRC Framework for Named Entity RecognitionCode1
ARES: A Reading Comprehension Ensembling Service—0
Show:102550
← PrevPage 8 of 56Next →

No leaderboard results yet.