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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 76–100 of 555 papers

TitleStatusHype
Coreference Resolution as Query-based Span PredictionCode1
A Unified MRC Framework for Named Entity RecognitionCode1
Interactive Language Learning by Question AnsweringCode1
MS MARCO: A Human Generated MAchine Reading COmprehension DatasetCode1
Interpretable Traces, Unexpected Outcomes: Investigating the Disconnect in Trace-Based Knowledge Distillation—0
Understanding LLMs' Cross-Lingual Context Retrieval: How Good It Is And Where It Comes FromCode0
Investigating Recent Large Language Models for Vietnamese Machine Reading Comprehension—0
MRCEval: A Comprehensive, Challenging and Accessible Machine Reading Comprehension BenchmarkCode0
Pay Attention to Real World Perturbations! Natural Robustness Evaluation in Machine Reading Comprehension—0
RoleMRC: A Fine-Grained Composite Benchmark for Role-Playing and Instruction-FollowingCode0
RoBIn: A Transformer-Based Model For Risk Of Bias Inference With Machine Reading ComprehensionCode0
Visualizing attention zones in machine reading comprehension models—0
Increasing the Difficulty of Automatically Generated Questions via Reinforcement Learning with Synthetic Preference—0
Towards Building a Robust Knowledge Intensive Question Answering Model with Large Language Models—0
Investigating a Benchmark for Training-set free Evaluation of Linguistic Capabilities in Machine Reading Comprehension—0
Enhancing Robustness of Retrieval-Augmented Language Models with In-Context Learning—0
SNFinLLM: Systematic and Nuanced Financial Domain Adaptation of Chinese Large Language Models—0
Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset ConstructionCode0
Recent Advances in Multi-Choice Machine Reading Comprehension: A Survey on Methods and Datasets—0
Evaluation of Instruction-Following Ability for Large Language Models on Story-Ending Generation—0
Comparison of Open-Source and Proprietary LLMs for Machine Reading Comprehension: A Practical Analysis for Industrial Applications—0
2DP-2MRC: 2-Dimensional Pointer-based Machine Reading Comprehension Method for Multimodal Moment Retrieval—0
Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training—0
Can GPT Redefine Medical Understanding? Evaluating GPT on Biomedical Machine Reading Comprehension—0
QLSC: A Query Latent Semantic Calibrator for Robust Extractive Question Answering—0
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