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 301–350 of 1760 papers

TitleStatusHype
A New Entity Extraction Method Based on Machine Reading Comprehension—0
An evaluation of syntactic simplification rules for people with autism—0
Automated Scoring of a Summary-Writing Task Designed to Measure Reading Comprehension—0
Adversarial Training for Machine Reading Comprehension with Virtual Embeddings—0
Controlling Risk of Web Question Answering—0
Automated Pyramid Scoring of Summaries using Distributional Semantics—0
A Neural Comprehensive Ranker (NCR) for Open-Domain Question Answering—0
Automated Graph Generation at Sentence Level for Reading Comprehension Based on Conceptual Graphs—0
An End-to-End Dialogue State Tracking System with Machine Reading Comprehension and Wide & Deep Classification—0
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approaches—0
Conversational Answer Generation and Factuality for Reading Comprehension Question-Answering—0
Auto FAQ Generation—0
AutoFAIR : Automatic Data FAIRification via Machine Reading—0
A Unified Abstractive Model for Generating Question-Answer Pairs—0
An Empirical Analysis of Multiple-Turn Reasoning Strategies in Reading Comprehension Tasks—0
Adversarial reading networks for machine comprehension—0
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension—0
Augmenting Image Question Answering Dataset by Exploiting Image Captions—0
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Datasets and Metrics—0
Audio-Oriented Multimodal Machine Comprehension: Task, Dataset and Model—0
Atypical Prosodic Structure as an Indicator of Reading Level and Text Difficulty—0
An Effective Multi-Stage Approach For Question Answering—0
A3Net: Adversarial-and-Attention Network for Machine Reading Comprehension—0
GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level—0
Conversational Machine Comprehension: a Literature Review—0
A Two-Stage Approach for Generating Unbiased Estimates of Text Complexity—0
An Attentive Sequence Model for Adverse Drug Event Extraction from Biomedical Text—0
2M-BELEBELE: Highly Multilingual Speech and American Sign Language Comprehension Dataset—0
An Annotation Scheme of A Large-scale Multi-party Dialogues Dataset for Discourse Parsing and Machine Comprehension—0
Attention-Guided Answer Distillation for Machine Reading Comprehension—0
Adversarial Domain Adaptation for Machine Reading Comprehension—0
Attention for Implicit Discourse Relation Recognition—0
Attention-Based Convolutional Neural Network for Machine Comprehension—0
An Annotated Corpus of Picture Stories Retold by Language Learners—0
Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes—0
Attendre: Wait To Attend By Retrieval With Evicted Queries in Memory-Based Transformers for Long Context Processing—0
An Annotated Corpus for Machine Reading of Instructions in Wet Lab Protocols—0
Adversarial Augmentation Policy Search for Domain and Cross-Lingual Generalization in Reading Comprehension—0
Attacks against Abstractive Text Summarization Models through Lead Bias and Influence Functions—0
An Analysis of Prerequisite Skills for Reading Comprehension—0
Analyzing Zero-shot Cross-lingual Transfer in Supervised NLP Tasks—0
A Tagging Approach to Identify Complex Constituents for Text Simplification—0
Advances in Multi-turn Dialogue Comprehension: A Survey—0
SAT3D: Image-driven Semantic Attribute Transfer in 3D—0
A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset—0
A Survey on Neural Machine Reading Comprehension—0
Analyzing Wrap-Up Effects through an Information-Theoretic Lens—0
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehension—0
A Survey on Machine Reading Comprehension: Tasks, Evaluation Metrics and Benchmark Datasets—0
Advances in Multi-turn Dialogue Comprehension: A Survey—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Rational Reasoner / IDOLTest80.6—Unverified
2AMR-LE-EnsembleTest80—Unverified
3MERIt(MERIt-deberta-v2-xxlarge )Test79.3—Unverified
4MERIt-deberta-v2-xxlarge deberta.v2.xxlarge.path.override_True.norm_1.1.0.w2.A100.cp200.s42Test79.3—Unverified
5Knowledge modelTest79.2—Unverified
6DeBERTa-v2-xxlarge-AMR-LE-ContrapositionTest77.2—Unverified
7LReasoner ensembleTest76.1—Unverified
8ELECTRA and ALBERTTest71—Unverified
9WWZTest69.7—Unverified
10xlnet-large-uncased [extended data]Test69.3—Unverified
#ModelMetricClaimedVerifiedStatus
1ALBERT (Ensemble)Accuracy91.4—Unverified
2Megatron-BERT (ensemble)Accuracy90.9—Unverified
3ALBERTxxlarge+DUMA(ensemble)Accuracy89.8—Unverified
4Megatron-BERTAccuracy89.5—Unverified
5XLNetAccuracy (Middle)88.6—Unverified
6DeBERTalargeAccuracy86.8—Unverified
7B10-10-10Accuracy85.7—Unverified
8RoBERTaAccuracy83.2—Unverified
9Orca 2-13BAccuracy82.87—Unverified
10Orca 2-7BAccuracy80.79—Unverified
#ModelMetricClaimedVerifiedStatus
1Golden TransformerAverage F10.94—Unverified
2MT5 LargeAverage F10.84—Unverified
3ruRoberta-large finetuneAverage F10.83—Unverified
4ruT5-large-finetuneAverage F10.82—Unverified
5Human BenchmarkAverage F10.81—Unverified
6ruT5-base-finetuneAverage F10.77—Unverified
7ruBert-large finetuneAverage F10.76—Unverified
8ruBert-base finetuneAverage F10.74—Unverified
9RuGPT3XL few-shotAverage F10.74—Unverified
10RuGPT3LargeAverage F10.73—Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-LargeOverall: F164.4—Unverified
2BERT-LargeOverall: F162.7—Unverified
3BiDAFOverall: F128.5—Unverified
#ModelMetricClaimedVerifiedStatus
1BERTMSE0.05—Unverified
#ModelMetricClaimedVerifiedStatus
1BERT pretrained on MIMIC-IIIAnswer F163.55—Unverified