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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

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Showing 51–60 of 555 papers

TitleStatusHype
DUMA: Reading Comprehension with Transposition ThinkingCode1
Cooperative Self-training of Machine Reading ComprehensionCode1
Context-faithful Prompting for Large Language ModelsCode1
LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical ReasoningCode1
Coreference Resolution as Query-based Span PredictionCode1
Modeling Hierarchical Reasoning Chains by Linking Discourse Units and Key Phrases for Reading ComprehensionCode1
Molweni: A Challenge Multiparty Dialogues-based Machine Reading Comprehension Dataset with Discourse StructureCode1
MPrompt: Exploring Multi-level Prompt Tuning for Machine Reading ComprehensionCode1
ECONET: Effective Continual Pretraining of Language Models for Event Temporal ReasoningCode1
Connecting Attributions and QA Model Behavior on Realistic CounterfactualsCode1
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