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 16511700 of 1760 papers

TitleStatusHype
The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and SuggestionsCode0
Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question AnsweringCode0
Analyzing Temporal Complex Events with Large Language Models? A Benchmark towards Temporal, Long Context UnderstandingCode0
Phrase-Indexed Question Answering: A New Challenge for Scalable Document ComprehensionCode0
Learning to Describe Phrases with Local and Global ContextsCode0
Picture What you ReadCode0
Semantically Equivalent Adversarial Rules for Debugging NLP modelsCode0
Which is the Effective Way for Gaokao: Information Retrieval or Neural Networks?Code0
Commonsense for Generative Multi-Hop Question Answering TasksCode0
Learning to Search in Long Documents Using Document StructureCode0
Comment Staytime Prediction with LLM-enhanced Comment UnderstandingCode0
Deep Manifold Learning for Reading Comprehension and Logical Reasoning Tasks with Polytuplet LossCode0
Porting an Open Information Extraction System from English to GermanCode0
Cognitive Graph for Multi-Hop Reading Comprehension at ScaleCode0
Which Shortcut Solution Do Question Answering Models Prefer to Learn?Code0
Semantics Altering Modifications for Evaluating Comprehension in Machine ReadingCode0
Less Is More: Domain Adaptation with Lottery Ticket for Reading ComprehensionCode0
DuoRC: Towards Complex Language Understanding with Paraphrased Reading ComprehensionCode0
Towards Efficient Methods in Medical Question Answering using Knowledge Graph EmbeddingsCode0
Semantics-aware BERT for Language UnderstandingCode0
Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-sentence Dependency GraphCode0
CNN for Text-Based Multiple Choice Question AnsweringCode0
The NarrativeQA Reading Comprehension ChallengeCode0
A Reading Comprehension Corpus for Machine Translation EvaluationCode0
Multilingual Multi-Aspect Explainability Analyses on Machine Reading Comprehension ModelsCode0
BERT-based distractor generation for Swedish reading comprehension questions using a small-scale datasetCode0
Lexical Generalization Improves with Larger Models and Longer TrainingCode0
CliCR: A Dataset of Clinical Case Reports for Machine Reading ComprehensionCode0
Chunk, Align, Select: A Simple Long-sequence Processing Method for TransformersCode0
Analyzing Research Trends in Inorganic Materials Literature Using NLPCode0
The relational processing limits of classic and contemporary neural network models of language processingCode0
The Shmoop Corpus: A Dataset of Stories with Loosely Aligned SummariesCode0
Dual Ask-Answer Network for Machine Reading ComprehensionCode0
Investigating Prior Knowledge for Challenging Chinese Machine Reading ComprehensionCode0
Abstract, Rationale, Stance: A Joint Model for Scientific Claim VerificationCode0
Lite Unified Modeling for Discriminative Reading ComprehensionCode0
Towards a Better Understanding Human Reading Comprehension with Brain SignalsCode0
LLM-as-a-Judge: Reassessing the Performance of LLMs in Extractive QACode0
LLMs are Biased Evaluators But Not Biased for Retrieval Augmented GenerationCode0
The Web as a Knowledge-base for Answering Complex QuestionsCode0
Locations of Characters in Narratives: Andersen and Persuasion DatasetsCode0
Be Consistent! Improving Procedural Text Comprehension using Label ConsistencyCode0
DTW at Qur’an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource DomainCode0
DTW at Qur'an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource DomainCode0
Sentence Pair Scoring: Towards Unified Framework for Text ComprehensionCode0
ViTextVQA: A Large-Scale Visual Question Answering Dataset for Evaluating Vietnamese Text Comprehension in ImagesCode0
DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over ParagraphsCode0
LogiQA 2.0—An Improved Dataset for Logical Reasoning in Natural Language UnderstandingCode0
DREAM: A Challenge Dataset and Models for Dialogue-Based Reading ComprehensionCode0
Understanding LLMs' Cross-Lingual Context Retrieval: How Good It Is And Where It Comes FromCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Rational Reasoner / IDOLTest80.6Unverified
2AMR-LE-EnsembleTest80Unverified
3MERIt-deberta-v2-xxlarge deberta.v2.xxlarge.path.override_True.norm_1.1.0.w2.A100.cp200.s42Test79.3Unverified
4MERIt(MERIt-deberta-v2-xxlarge )Test79.3Unverified
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