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
Automatic Evaluation vs. User Preference in Neural Textual QuestionAnswering over COVID-19 Scientific Literature0
Automatic Entity State Annotation using the VerbNet Semantic Parser0
A New Semantic Lexicon and Similarity Measure in Bangla0
Affective Common Sense Knowledge Acquisition for Sentiment Analysis0
A Constituent-Centric Neural Architecture for Reading Comprehension0
App-Aware Response Synthesis for User Reviews0
Recent Advances in Multi-Choice Machine Reading Comprehension: A Survey on Methods and Datasets0
Data Augmentation for Biomedical Factoid Question Answering0
DADgraph: A Discourse-aware Dialogue Graph Neural Network for Multiparty Dialogue Machine Reading Comprehension0
Automatic Classification of the Complexity of Nonfiction Texts in Portuguese for Early School Years0
CWIG3G2 - Complex Word Identification Task across Three Text Genres and Two User Groups0
Cut to the Chase: A Context Zoom-in Network for Reading Comprehension0
Automatically Predicting Sentence Translation Difficulty0
A New Entity Extraction Method Based on Machine Reading Comprehension0
CuentosIE: can a chatbot about "tales with a message" help to teach emotional intelligence?0
CSS: Combining Self-training and Self-supervised Learning for Few-shot Dialogue State Tracking0
CSReader at SemEval-2018 Task 11: Multiple Choice Question Answering as Textual Entailment0
Automated Scoring of a Summary-Writing Task Designed to Measure Reading Comprehension0
An evaluation of syntactic simplification rules for people with autism0
Adversarial Training for Machine Reading Comprehension with Virtual Embeddings0
Crowd-sourcing annotation of complex NLU tasks: A case study of argumentative content annotation0
Cross-Task Knowledge Transfer for Query-Based Text Summarization0
Cross-lingual Machine Reading Comprehension with Language Branch Knowledge Distillation0
Automated Pyramid Scoring of Summaries using Distributional Semantics0
A Neural Comprehensive Ranker (NCR) for Open-Domain Question Answering0
Cross-lingual and Cross-domain Evaluation of Machine Reading Comprehension with Squad and CALOR-Quest Corpora0
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
Creating Interactive Macaronic Interfaces for Language Learning0
CPRM: A LLM-based Continual Pre-training Framework for Relevance Modeling in Commercial Search0
Auto FAQ Generation0
Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning0
AutoFAIR : Automatic Data FAIRification via Machine Reading0
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training0
Correcting the Misuse: A Method for the Chinese Idiom Cloze Test0
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
Cooperative Semi-Supervised Transfer Learning of Machine Reading Comprehension0
Cooperative Self-training of Machine Reading Comprehension0
Augmenting Image Question Answering Dataset by Exploiting Image Captions0
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension0
Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions0
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
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Datasets and Metrics0
A3Net: Adversarial-and-Attention Network for Machine Reading Comprehension0
Conversational Machine Comprehension: a Literature Review0
Show:102550
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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