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 701750 of 1760 papers

TitleStatusHype
OpenQA: Hybrid QA System Relying on Structured Knowledge Base as well as Non-structured Data0
Multi-Row, Multi-Span Distant Supervision For Table+Text Question0
Roof-Transformer: Divided and Joined Understanding with Knowledge Enhancement0
Native Chinese Reader: A Dataset Towards Native-Level Chinese Machine Reading Comprehension0
A Puzzle-Based Dataset for Natural Language InferenceCode0
From Good to Best: Two-Stage Training for Cross-lingual Machine Reading Comprehension0
Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-sentence Dependency GraphCode0
TunBERT: Pretrained Contextualized Text Representation for Tunisian Dialect0
Towards Interpretable and Reliable Reading Comprehension: A Pipeline Model with Unanswerability Prediction0
Automatic Mining of Salient Events from Multiple Documents0
Understanding Attention in Machine Reading Comprehension0
ViQuAE, a Dataset for Knowledge-based Visual Question Answering about Named EntitiesCode0
ViQA-COVID: COVID-19 Machine Reading Comprehension Dataset for Vietnamese0
Context-Paraphrase Enhanced Commonsense Question Answering0
Structural Characterization for Dialogue Disentanglement0
Retrieval-guided Counterfactual Generation for QA0
Unsupervised Open-Domain Question Answering with Higher Answerability0
How Well Do Multi-hop Reading Comprehension Models Understand Date Information?0
On the Robustness of Reading Comprehension Models to Entity Renaming0
MRCLens: an MRC Dataset Bias Detection Toolkit0
EveMRC: A Two-stage Evidence Modeling For Multi-choice Machine Reading Comprehension0
Models can use keywords to answer questions that human cannot0
One General Teacher for Multi-Data Multi-Task: A New Knowledge Distillation Framework for Discourse Relation Analysis0
What Makes Machine Reading Comprehension Questions Difficult? Investigating Variation in Passage Sources and Question Types0
Calibration of Machine Reading Systems at Scale0
Question Generation for Reading Comprehension Assessment by Modeling How and What to Ask0
A Graph Fusion Approach to Cross-Lingual Machine Reading Comprehension0
Slot Filling for Biomedical Information Extraction0
Pre-trained Transformer-Based Approach for Arabic Question Answering : A Comparative Study0
IBERT: Idiom Cloze-style reading comprehension with Attention0
Discourse Comprehension: A Question Answering Framework to Represent Sentence ConnectionsCode0
Automatic Entity State Annotation using the VerbNet Semantic Parser0
Locke’s Holiday: Belief Bias in Machine Reading0
Machine Reading Comprehension as Data Augmentation: A Case Study on Implicit Event Argument Extraction0
Resolving Implicit References in Instructional Texts0
Can Question Generation Debias Question Answering Models? A Case Study on Question–Context Lexical Overlap0
What If Sentence-hood is Hard to Define: A Case Study in Chinese Reading Comprehension0
Evaluating a How-to Tip Machine Comprehension Model with QA Examples collected from a Community QA Site0
ESTER: A Machine Reading Comprehension Dataset for Reasoning about Event Semantic Relations0
Have You Seen That Number? Investigating Extrapolation in Question Answering Models0
Enhancing Multiple-choice Machine Reading Comprehension by Punishing Illogical Interpretations0
Self Question-answering: Aspect-based Sentiment Analysis by Role Flipped Machine Reading ComprehensionCode0
The Global Banking Standards QA Dataset (GBS-QA)0
Less Is More: Domain Adaptation with Lottery Ticket for Reading ComprehensionCode0
Learning Representations for Zero-Shot Retrieval over Structured Data0
A Framework for Learning Assessment through Multimodal Analysis of Reading Behaviour and Language Comprehension0
Challenges in Procedural Multimodal Machine Comprehension:A Novel Way To Benchmark0
ListReader: Extracting List-form Answers for Opinion Questions0
A Unified Abstractive Model for Generating Question-Answer Pairs0
Cooperative Semi-Supervised Transfer Learning of Machine Reading Comprehension0
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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