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 301325 of 1760 papers

TitleStatusHype
Adversarial Training for Machine Reading Comprehension with Virtual Embeddings0
Composing RNNs and FSTs for Small Data: Recovering Missing Characters in Old Hawaiian Text0
Automated Pyramid Scoring of Summaries using Distributional Semantics0
A Neural Comprehensive Ranker (NCR) for Open-Domain Question Answering0
Automated Graph Generation at Sentence Level for Reading Comprehension Based on Conceptual Graphs0
An End-to-End Dialogue State Tracking System with Machine Reading Comprehension and Wide & Deep Classification0
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approaches0
Composing RNNs and FSTs for Small Data: Recovering Missing Characters in Old Hawaiian Text0
Auto FAQ Generation0
AutoFAIR : Automatic Data FAIRification via Machine Reading0
A Unified Abstractive Model for Generating Question-Answer Pairs0
An Empirical Analysis of Multiple-Turn Reasoning Strategies in Reading Comprehension Tasks0
Adversarial reading networks for machine comprehension0
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension0
Augmenting Image Question Answering Dataset by Exploiting Image Captions0
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Datasets and Metrics0
Audio-Oriented Multimodal Machine Comprehension: Task, Dataset and Model0
Atypical Prosodic Structure as an Indicator of Reading Level and Text Difficulty0
An Effective Multi-Stage Approach For Question Answering0
A3Net: Adversarial-and-Attention Network for Machine Reading Comprehension0
GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level0
Comprehending Knowledge Graphs with Large Language Models for Recommender Systems0
A Two-Stage Approach for Generating Unbiased Estimates of Text Complexity0
An Attentive Sequence Model for Adverse Drug Event Extraction from Biomedical Text0
2M-BELEBELE: Highly Multilingual Speech and American Sign Language Comprehension Dataset0
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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