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 751800 of 1760 papers

TitleStatusHype
Conversational Answer Generation and Factuality for Reading Comprehension Question-Answering0
A Two-Stage Approach for Generating Unbiased Estimates of Text Complexity0
Controlling Risk of Web Question Answering0
An Attentive Sequence Model for Adverse Drug Event Extraction from Biomedical Text0
Contrastive Perplexity for Controlled Generation: An Application in Detoxifying Large Language Models0
Continuous fluency tracking and the challenges of varying text complexity0
Attention-Guided Answer Distillation for Machine Reading Comprehension0
An Annotation Scheme of A Large-scale Multi-party Dialogues Dataset for Discourse Parsing and Machine Comprehension0
Adversarial Domain Adaptation for Machine Reading Comprehension0
Continual Machine Reading Comprehension via Uncertainty-aware Fixed Memory and Adversarial Domain Adaptation0
Continual Domain Adaptation for Machine Reading Comprehension0
Attention for Implicit Discourse Relation Recognition0
Contextual Recurrent Units for Cloze-style Reading Comprehension0
Attention-Based Convolutional Neural Network for Machine Comprehension0
An Annotated Corpus of Picture Stories Retold by Language Learners0
Contextualized Representations Using Textual Encyclopedic Knowledge0
Context-Paraphrase Enhanced Commonsense Question Answering0
Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes0
Explicit Contextual Semantics for Text Comprehension0
Context Modeling with Evidence Filter for Multiple Choice Question Answering0
Attendre: Wait To Attend By Retrieval With Evicted Queries in Memory-Based Transformers for Long Context Processing0
An Annotated Corpus for Machine Reading of Instructions in Wet Lab Protocols0
Adversarial Augmentation Policy Search for Domain and Cross-Lingual Generalization in Reading Comprehension0
IIRC: A Dataset of Incomplete Information Reading Comprehension Questions0
Constructing Datasets for Multi-hop Reading Comprehension Across Documents0
Attacks against Abstractive Text Summarization Models through Lead Bias and Influence Functions0
Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks0
Consensus Attention-based Neural Networks for Chinese Reading Comprehension0
An Analysis of Prerequisite Skills for Reading Comprehension0
IBERT: Idiom Cloze-style reading comprehension with Attention0
Human Needs Categorization of Affective Events Using Labeled and Unlabeled Data0
HRCA+: Advanced Multiple-choice Machine Reading Comprehension Method0
How You Ask Matters: The Effect of Paraphrastic Questions to BERT Performance on a Clinical SQuAD Dataset0
How Well Do Multi-hop Reading Comprehension Models Understand Date Information?0
How to Pre-Train Your Model? Comparison of Different Pre-Training Models for Biomedical Question Answering0
Computing Semantic Text Similarity Using Rich Features0
A Tagging Approach to Identify Complex Constituents for Text Simplification0
Analyzing Zero-shot Cross-lingual Transfer in Supervised NLP Tasks0
Advances in Multi-turn Dialogue Comprehension: A Survey0
IdeaReader: A Machine Reading System for Understanding the Idea Flow of Scientific Publications0
Computational Approaches to Sentence Completion0
Identifying Where to Focus in Reading Comprehension for Neural Question Generation0
How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks0
A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset0
I Do Not Understand What I Cannot Define: Automatic Question Generation With Pedagogically-Driven Content Selection0
IIE-NLP-Eyas at SemEval-2021 Task 4: Enhancing PLM for ReCAM with Special Tokens, Re-Ranking, Siamese Encoders and Back Translation0
How Context Affects Language Models' Factual Predictions0
IIT-KGP at COIN 2019: Using pre-trained Language Models for modeling Machine Comprehension0
HoT: Highlighted Chain of Thought for Referencing Supporting Facts from Inputs0
Compressing Long Context for Enhancing RAG with AMR-based Concept Distillation0
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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