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 151200 of 1760 papers

TitleStatusHype
A Trigger-Sense Memory Flow Framework for Joint Entity and Relation ExtractionCode1
WebSRC: A Dataset for Web-Based Structural Reading ComprehensionCode1
ComQA:Compositional Question Answering via Hierarchical Graph Neural NetworksCode1
TSQA: Tabular Scenario Based Question AnsweringCode1
AraELECTRA: Pre-Training Text Discriminators for Arabic Language UnderstandingCode1
ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive LearningCode1
Optimizing Deeper Transformers on Small DatasetsCode1
ECONET: Effective Continual Pretraining of Language Models for Event Temporal ReasoningCode1
Dialogue Graph Modeling for Conversational Machine ReadingCode1
Reasoning in Dialog: Improving Response Generation by Context Reading ComprehensionCode1
ParsiNLU: A Suite of Language Understanding Challenges for PersianCode1
CTRLsum: Towards Generic Controllable Text SummarizationCode1
Context-Aware Answer Extraction in Question AnsweringCode1
RussianSuperGLUE: A Russian Language Understanding Evaluation BenchmarkCode1
mT5: A massively multilingual pre-trained text-to-text transformerCode1
RECONSIDER: Re-Ranking using Span-Focused Cross-Attention for Open Domain Question AnsweringCode1
Open-Domain Question Answering Goes Conversational via Question RewritingCode1
MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension MetricsCode1
PolicyQA: A Reading Comprehension Dataset for Privacy PoliciesCode1
Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement LearningCode1
Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine ReadingCode1
Inquisitive Question Generation for High Level Text ComprehensionCode1
Biomedical named entity recognition using BERT in the machine reading comprehension frameworkCode1
LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical ReasoningCode1
DocVQA: A Dataset for VQA on Document ImagesCode1
Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation ExtractionCode1
Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine ReadingCode1
ReCO: A Large Scale Chinese Reading Comprehension Dataset on OpinionCode1
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language ProcessingCode1
EMT: Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine ReadingCode1
Adversarial Training for Commonsense InferenceCode1
Recurrent Chunking Mechanisms for Long-Text Machine Reading ComprehensionCode1
Machine Reading Comprehension: The Role of Contextualized Language Models and BeyondCode1
Document Modeling with Graph Attention Networks for Multi-grained Machine Reading ComprehensionCode1
A Dataset for Statutory Reasoning in Tax Law Entailment and Question AnsweringCode1
A Self-Training Method for Machine Reading Comprehension with Soft Evidence ExtractionCode1
FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive SummarizationCode1
Teaching Machine Comprehension with Compositional ExplanationsCode1
Clinical Reading Comprehension: A Thorough Analysis of the emrQA DatasetCode1
STARC: Structured Annotations for Reading ComprehensionCode1
Benchmarking Robustness of Machine Reading Comprehension ModelsCode1
Logic-Guided Data Augmentation and Regularization for Consistent Question AnsweringCode1
From Machine Reading Comprehension to Dialogue State Tracking: Bridging the GapCode1
Molweni: A Challenge Multiparty Dialogues-based Machine Reading Comprehension Dataset with Discourse StructureCode1
What do Models Learn from Question Answering Datasets?Code1
A Sentence Cloze Dataset for Chinese Machine Reading ComprehensionCode1
Evaluating Models' Local Decision Boundaries via Contrast SetsCode1
TREC CAsT 2019: The Conversational Assistance Track OverviewCode1
Incorporating BERT into Neural Machine TranslationCode1
ReClor: A Reading Comprehension Dataset Requiring Logical ReasoningCode1
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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