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 401450 of 1760 papers

TitleStatusHype
Context-Paraphrase Enhanced Commonsense Question Answering0
Contextualized Representations Using Textual Encyclopedic Knowledge0
Attention-Based Convolutional Neural Network for Machine Comprehension0
Contextual Recurrent Units for Cloze-style Reading Comprehension0
Continual Domain Adaptation for Machine Reading Comprehension0
Continual Machine Reading Comprehension via Uncertainty-aware Fixed Memory and Adversarial Domain Adaptation0
Continuous fluency tracking and the challenges of varying text complexity0
A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements0
Document-Level Multi-Aspect Sentiment Classification as Machine Comprehension0
Contrastive Perplexity for Controlled Generation: An Application in Detoxifying Large Language Models0
An Attentive Sequence Model for Adverse Drug Event Extraction from Biomedical Text0
Controlling Risk of Web Question Answering0
Conversational Answer Generation and Factuality for Reading Comprehension Question-Answering0
Conversational Machine Comprehension: a Literature Review0
Document-Level N-ary Relation Extraction with Multiscale Representation Learning0
An Effective Multi-Stage Approach For Question Answering0
Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions0
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning0
Cooperative Self-training of Machine Reading Comprehension0
Cooperative Semi-Supervised Transfer Learning of Machine Reading Comprehension0
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension0
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Datasets and Metrics0
A Unified Abstractive Model for Generating Question-Answer Pairs0
Combining Formal and Distributional Models of Temporal and Intensional Semantics0
Assessing Distractors in Multiple-Choice Tests0
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training0
Collecting high-quality adversarial data for machine reading comprehension tasks with humans and models in the loop0
Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning0
CPRM: A LLM-based Continual Pre-training Framework for Relevance Modeling in Commercial Search0
Creating Interactive Macaronic Interfaces for Language Learning0
Assessing Conformance of Manually Simplified Corpora with User Requirements: the Case of Autistic Readers0
Analysing the Effect of Masking Length Distribution of MLM: An Evaluation Framework and Case Study on Chinese MRC Datasets0
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
Cross-lingual Machine Reading Comprehension with Language Branch Knowledge Distillation0
Automated Pyramid Scoring of Summaries using Distributional Semantics0
Coherent Zero-Shot Visual Instruction Generation0
Crowd-sourcing annotation of complex NLU tasks: A case study of argumentative content annotation0
CSReader at SemEval-2018 Task 11: Multiple Choice Question Answering as Textual Entailment0
CSS: Combining Self-training and Self-supervised Learning for Few-shot Dialogue State Tracking0
Assessing Chinese Readability using Term Frequency and Lexical Chain0
CuentosIE: can a chatbot about "tales with a message" help to teach emotional intelligence?0
Cut to the Chase: A Context Zoom-in Network for Reading Comprehension0
CWIG3G2 - Complex Word Identification Task across Three Text Genres and Two User Groups0
DADgraph: A Discourse-aware Dialogue Graph Neural Network for Multiparty Dialogue Machine Reading Comprehension0
Data Augmentation for Biomedical Factoid Question Answering0
Analyse automatique en cadres s\'emantiques pour l'apprentissage de mod\`eles de compr\'ehension de texte (Semantic Frame Parsing for training Machine Reading Comprehension models)0
A New Semantic Lexicon and Similarity Measure in Bangla0
Data-Driven Metaphor Recognition and Explanation0
Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension0
Show:102550
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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