SOTAVerified

Reading Comprehension

Most current question answering datasets frame the task as reading comprehension where the question is about a paragraph or document and the answer often is a span in the document.

Some specific tasks of reading comprehension include multi-modal machine reading comprehension and textual machine reading comprehension, among others. In the literature, machine reading comprehension can be divide into four categories: cloze style, multiple choice, span prediction, and free-form answer. Read more about each category here.

Benchmark datasets used for testing a model's reading comprehension abilities include MovieQA, ReCoRD, and RACE, among others.

The Machine Reading group at UCL also provides an overview of reading comprehension tasks.

Figure source: A Survey on Machine Reading Comprehension: Tasks, Evaluation Metrics and Benchmark Datasets

Papers

Showing 51100 of 1760 papers

TitleStatusHype
Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet ExtractionCode1
ExpMRC: Explainability Evaluation for Machine Reading ComprehensionCode1
Adversarial Training for Commonsense InferenceCode1
FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language ModelsCode1
Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine ReadingCode1
Biomedical named entity recognition using BERT in the machine reading comprehension frameworkCode1
Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State TrackingCode1
From LSAT: The Progress and Challenges of Complex ReasoningCode1
Break, Perturb, Build: Automatic Perturbation of Reasoning Paths Through Question DecompositionCode1
Break It Down: A Question Understanding BenchmarkCode1
ELASTIC: Numerical Reasoning with Adaptive Symbolic CompilerCode1
ECONET: Effective Continual Pretraining of Language Models for Event Temporal ReasoningCode1
A Dataset for Statutory Reasoning in Tax Law Entailment and Question AnsweringCode1
Densely Connected Attention Propagation for Reading ComprehensionCode1
Asking Questions the Human Way: Scalable Question-Answer Generation from Text CorpusCode1
A Self-Training Method for Machine Reading Comprehension with Soft Evidence ExtractionCode1
A Trigger-Sense Memory Flow Framework for Joint Entity and Relation ExtractionCode1
Dependency Parsing as MRC-based Span-Span PredictionCode1
EMT: Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine ReadingCode1
CreoleVal: Multilingual Multitask Benchmarks for CreolesCode1
ArabicaQA: A Comprehensive Dataset for Arabic Question AnsweringCode1
Cooperative Self-training of Machine Reading ComprehensionCode1
CTRLsum: Towards Generic Controllable Text SummarizationCode1
AllenNLP: A Deep Semantic Natural Language Processing PlatformCode1
Context-Aware Answer Extraction in Question AnsweringCode1
Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical ReasoningCode1
AraELECTRA: Pre-Training Text Discriminators for Arabic Language UnderstandingCode1
Coreference Resolution as Query-based Span PredictionCode1
Multi-Grained Query-Guided Set Prediction Network for Grounded Multimodal Named Entity RecognitionCode1
A Robustly Optimized BMRC for Aspect Sentiment Triplet ExtractionCode1
A Sentence Cloze Dataset for Chinese Machine Reading ComprehensionCode1
Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation ExtractionCode1
Context-faithful Prompting for Large Language ModelsCode1
Debate Helps Supervise Unreliable ExpertsCode1
A Multi-turn Machine Reading Comprehension Framework with Rethink Mechanism for Emotion-Cause Pair ExtractionCode1
AC-EVAL: Evaluating Ancient Chinese Language Understanding in Large Language ModelsCode1
LatestEval: Addressing Data Contamination in Language Model Evaluation through Dynamic and Time-Sensitive Test ConstructionCode1
DeRIS: Decoupling Perception and Cognition for Enhanced Referring Image Segmentation through Loopback SynergyCode1
A Unified MRC Framework for Named Entity RecognitionCode1
Automated Scoring for Reading Comprehension via In-context BERT TuningCode1
A Large Cross-Modal Video Retrieval Dataset with Reading ComprehensionCode1
DocTrack: A Visually-Rich Document Dataset Really Aligned with Human Eye Movement for Machine ReadingCode1
Analyzing Multi-Task Learning for Abstractive Text SummarizationCode1
DocVQA: A Dataset for VQA on Document ImagesCode1
EntQA: Entity Linking as Question AnsweringCode1
ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive LearningCode1
CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about NegationCode1
Benchmarking: Past, Present and FutureCode1
BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment AnalysisCode1
ConditionalQA: A Complex Reading Comprehension Dataset with Conditional AnswersCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Rational Reasoner / IDOLTest80.6Unverified
2AMR-LE-EnsembleTest80Unverified
3MERIt(MERIt-deberta-v2-xxlarge )Test79.3Unverified
4MERIt-deberta-v2-xxlarge deberta.v2.xxlarge.path.override_True.norm_1.1.0.w2.A100.cp200.s42Test79.3Unverified
5Knowledge modelTest79.2Unverified
6DeBERTa-v2-xxlarge-AMR-LE-ContrapositionTest77.2Unverified
7LReasoner ensembleTest76.1Unverified
8ELECTRA and ALBERTTest71Unverified
9WWZTest69.7Unverified
10xlnet-large-uncased [extended data]Test69.3Unverified
#ModelMetricClaimedVerifiedStatus
1ALBERT (Ensemble)Accuracy91.4Unverified
2Megatron-BERT (ensemble)Accuracy90.9Unverified
3ALBERTxxlarge+DUMA(ensemble)Accuracy89.8Unverified
4Megatron-BERTAccuracy89.5Unverified
5XLNetAccuracy (Middle)88.6Unverified
6DeBERTalargeAccuracy86.8Unverified
7B10-10-10Accuracy85.7Unverified
8RoBERTaAccuracy83.2Unverified
9Orca 2-13BAccuracy82.87Unverified
10Orca 2-7BAccuracy80.79Unverified
#ModelMetricClaimedVerifiedStatus
1Golden TransformerAverage F10.94Unverified
2MT5 LargeAverage F10.84Unverified
3ruRoberta-large finetuneAverage F10.83Unverified
4ruT5-large-finetuneAverage F10.82Unverified
5Human BenchmarkAverage F10.81Unverified
6ruT5-base-finetuneAverage F10.77Unverified
7ruBert-large finetuneAverage F10.76Unverified
8ruBert-base finetuneAverage F10.74Unverified
9RuGPT3XL few-shotAverage F10.74Unverified
10RuGPT3LargeAverage F10.73Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-LargeOverall: F164.4Unverified
2BERT-LargeOverall: F162.7Unverified
3BiDAFOverall: F128.5Unverified
#ModelMetricClaimedVerifiedStatus
1BERTMSE0.05Unverified
#ModelMetricClaimedVerifiedStatus
1BERT pretrained on MIMIC-IIIAnswer F163.55Unverified