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 12761300 of 1760 papers

TitleStatusHype
A Survey on Machine Reading Comprehension Systems0
A Survey on Machine Reading Comprehension: Tasks, Evaluation Metrics and Benchmark Datasets0
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehension0
A Survey on Neural Machine Reading Comprehension0
A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset0
A Tagging Approach to Identify Complex Constituents for Text Simplification0
Attacks against Abstractive Text Summarization Models through Lead Bias and Influence Functions0
Attendre: Wait To Attend By Retrieval With Evicted Queries in Memory-Based Transformers for Long Context Processing0
Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes0
Attention-Based Convolutional Neural Network for Machine Comprehension0
Attention for Implicit Discourse Relation Recognition0
Attention-Guided Answer Distillation for Machine Reading Comprehension0
A Two-Stage Approach for Generating Unbiased Estimates of Text Complexity0
Atypical Prosodic Structure as an Indicator of Reading Level and Text Difficulty0
Audio-Oriented Multimodal Machine Comprehension: Task, Dataset and Model0
Augmenting Image Question Answering Dataset by Exploiting Image Captions0
A Unified Abstractive Model for Generating Question-Answer Pairs0
AutoFAIR : Automatic Data FAIRification via Machine Reading0
Auto FAQ Generation0
Automated Graph Generation at Sentence Level for Reading Comprehension Based on Conceptual Graphs0
Automated Pyramid Scoring of Summaries using Distributional Semantics0
Automated Scoring of a Summary-Writing Task Designed to Measure Reading Comprehension0
Automatically Predicting Sentence Translation Difficulty0
Automatic Classification of the Complexity of Nonfiction Texts in Portuguese for Early School Years0
Automatic Entity State Annotation using the VerbNet Semantic Parser0
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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