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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 1–50 of 555 papers

TitleStatusHype
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
Multi-Grained Query-Guided Set Prediction Network for Grounded Multimodal Named Entity RecognitionCode1
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
Transfer Learning Enhanced Single-choice Decision for Multi-choice Question Answering—0
Enhancing Pre-Trained Generative Language Models with Question Attended Span Extraction on Machine Reading Comprehension—0
From Multiple-Choice to Extractive QA: A Case Study for English and ArabicCode0
PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering—0
emrQA-msquad: A Medical Dataset Structured with the SQuAD V2.0 Framework, Enriched with emrQA Medical Information—0
Interpreting Themes from Educational StoriesCode0
The Death of Feature Engineering? BERT with Linguistic Features on SQuAD 2.0—0
ArabicaQA: A Comprehensive Dataset for Arabic Question AnsweringCode1
ChroniclingAmericaQA: A Large-scale Question Answering Dataset based on Historical American Newspaper PagesCode1
WangchanLion and WangchanX MRC EvalCode0
MRC-based Nested Medical NER with Co-prediction and Adaptive Pre-training—0
QASE Enhanced PLMs: Improved Control in Text Generation for MRC—0
VlogQA: Task, Dataset, and Baseline Models for Vietnamese Spoken-Based Machine Reading ComprehensionCode0
Majority or Minority: Data Imbalance Learning Method for Named Entity Recognition—0
Towards Efficient Methods in Medical Question Answering using Knowledge Graph EmbeddingsCode0
Generative Large Language Models Are All-purpose Text Analytics Engines: Text-to-text Learning Is All Your Need—0
Towards Robust Text Retrieval with Progressive LearningCode0
Sharing, Teaching and Aligning: Knowledgeable Transfer Learning for Cross-Lingual Machine Reading Comprehension—0
Mirror: A Universal Framework for Various Information Extraction TasksCode1
MPrompt: Exploring Multi-level Prompt Tuning for Machine Reading ComprehensionCode1
Multi-grained Evidence Inference for Multi-choice Reading Comprehension—0
Guiding LLM to Fool Itself: Automatically Manipulating Machine Reading Comprehension Shortcut TriggersCode0
Explaining Interactions Between Text SpansCode0
Instructive Dialogue Summarization with Query AggregationsCode0
Hierarchical Evaluation Framework: Best Practices for Human Evaluation—0
Named Entity Recognition via Machine Reading Comprehension: A Multi-Task Learning ApproachCode0
Benchmarks for Pirá 2.0, a Reading Comprehension Dataset about the Ocean, the Brazilian Coast, and Climate Change—0
Multi-turn Dialogue Comprehension from a Topic-aware Perspective—0
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