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 251300 of 1760 papers

TitleStatusHype
Annotating Entailment Relations for Shortanswer Questions0
Benchmarks for Pirá 2.0, a Reading Comprehension Dataset about the Ocean, the Brazilian Coast, and Climate Change0
Benefits of Intermediate Annotations in Reading Comprehension0
Annotating the MASC Corpus with BabelNet0
A BERT based Sentiment Analysis and Key Entity Detection Approach for Online Financial Texts0
Commonsense Knowledge Base Completion and Generation0
Annotating and Extracting Synthesis Process of All-Solid-State Batteries from Scientific Literature0
Recent Advances in Multi-Choice Machine Reading Comprehension: A Survey on Methods and Datasets0
AWS CORD-19 Search: A Neural Search Engine for COVID-19 Literature0
An NLP-based Reading Tool for Aiding Non-native English Readers0
A Framework for Learning Assessment through Multimodal Analysis of Reading Behaviour and Language Comprehension0
Commonsense Evidence Generation and Injection in Reading Comprehension0
A Vietnamese Dataset for Evaluating Machine Reading Comprehension0
An MRC Framework for Semantic Role Labeling0
A Vietnamese Dataset for Evaluating Machine Reading Comprehension0
Automating Reading Comprehension by Generating Question and Answer Pairs0
A Corpus of Text Data and Gaze Fixations from Autistic and Non-Autistic Adults0
Commonsense Inference in Natural Language Processing (COIN) - Shared Task Report0
Commonsense Knowledge + BERT for Level 2 Reading Comprehension Ability Test0
Automating Idea Unit Segmentation and Alignment for Assessing Reading Comprehension via Summary Protocol Analysis0
Automatic Word Segmentation and Part-of-Speech Tagging of Ancient Chinese Based on BERT Model0
An Intelligent Recommendation-cum-Reminder System0
Automatic True/False Question Generation for Educational Purpose0
An Initial Investigation of Non-Native Spoken Question-Answering0
A Framework and Dataset for Abstract Art Generation via CalligraphyGAN0
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning0
Automatic Question Generation using Relative Pronouns and Adverbs0
A Coordination-based Approach for Focused Learning in Knowledge-Based Systems0
App-Aware Response Synthesis for User Reviews0
Automatic Mining of Salient Events from Multiple Documents0
Automatic learner summary assessment for reading comprehension0
A Frame-based Sentence Representation for Machine Reading Comprehension0
Combining Formal and Distributional Models of Temporal and Intensional Semantics0
CoMeT: Integrating different levels of linguistic modeling for meaning assessment0
Automatic Judgment Prediction via Legal Reading Comprehension0
Automatic Generation of Multiple-Choice Questions0
中英文的文字蘊涵與閱讀測驗的初步探索 (An Exploration of Textual Entailment and Reading Comprehension for Chinese and English) [In Chinese]0
An Exploration of Data Augmentation and Sampling Techniques for Domain-Agnostic Question Answering0
Automatic Generation of Context-Based Fill-in-the-Blank Exercises Using Co-occurrence Likelihoods and Google n-grams0
A Fine-grained Interpretability Evaluation Benchmark for Neural NLP0
An Experimental Study of Deep Neural Network Models for Vietnamese Multiple-Choice Reading Comprehension0
Automatic Feedback Generation for Short Answer Questions using Answer Diagnostic Graphs0
Affective Common Sense Knowledge Acquisition for Sentiment Analysis0
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
A Constituent-Centric Neural Architecture for Reading Comprehension0
Collecting high-quality adversarial data for machine reading comprehension tasks with humans and models in the loop0
CoMiC: Adapting a Short Answer Assessment System for Answer Selection0
Comparative Analysis of Neural QA models on SQuAD0
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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