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 14511500 of 1760 papers

TitleStatusHype
GYM at Qur’an QA 2023 Shared Task: Multi-Task Transfer Learning for Quranic Passage Retrieval and Question Answering with Large Language ModelsCode0
Exploiting Word Semantics to Enrich Character Representations of Chinese Pre-trained ModelsCode0
Exploiting Explicit Paths for Multi-hop Reading ComprehensionCode0
Stochastic Answer Networks for SQuAD 2.0Code0
Have my arguments been replied to? Argument Pair Extraction as Machine Reading ComprehensionCode0
Can Question Generation Debias Question Answering Models? A Case Study on Question-Context Lexical OverlapCode0
"You are grounded!": Latent Name Artifacts in Pre-trained Language ModelsCode0
Multi-granularity hierarchical attention fusion networks for reading comprehension and question answeringCode0
ZeQR: Zero-shot Query Reformulation for Conversational SearchCode0
Recurrent Batch NormalizationCode0
HICD: Hallucination-Inducing via Attention Dispersion for Contrastive Decoding to Mitigate Hallucinations in Large Language ModelsCode0
From Multiple-Choice to Extractive QA: A Case Study for English and ArabicCode0
Hierarchical Attention: What Really Counts in Various NLP TasksCode0
Multi-hop Reading Comprehension through Question Decomposition and RescoringCode0
Multi-hop Reading Comprehension via Deep Reinforcement Learning based Document TraversalCode0
Recurrent Entity Networks with Delayed Memory Update for Targeted Aspect-based Sentiment AnalysisCode0
Multilingual Controllable Transformer-Based Lexical SimplificationCode0
Multilingual Extractive Reading Comprehension by Runtime Machine TranslationCode0
Recurrently Controlled Recurrent NetworksCode0
How Many Answers Should I Give? An Empirical Study of Multi-Answer Reading ComprehensionCode0
UQA: Corpus for Urdu Question AnsweringCode0
Explaining Interactions Between Text SpansCode0
How to Engage Your Readers? Generating Guiding Questions to Promote Active ReadingCode0
A Causal View of Entity Bias in (Large) Language ModelsCode0
Reference Knowledgeable Network for Machine Reading ComprehensionCode0
How Well Do Multi-hop Reading Comprehension Models Understand Date Information?Code0
Human Attention during Goal-directed Reading Comprehension Relies on Task OptimizationCode0
Attentive Memory Networks: Efficient Machine Reading for Conversational SearchCode0
Reinforced Mnemonic Reader for Machine Reading ComprehensionCode0
Building Large Machine Reading-Comprehension Datasets using Paragraph VectorsCode0
Multi-Perspective Context Matching for Machine ComprehensionCode0
Bridging the Gap between Decision and Logits in Decision-based Knowledge Distillation for Pre-trained Language ModelsCode0
Structural Scaffolds for Citation Intent Classification in Scientific PublicationsCode0
IDK-MRC: Unanswerable Questions for Indonesian Machine Reading ComprehensionCode0
EviDR: Evidence-Emphasized Discrete Reasoning for Reasoning Machine Reading ComprehensionCode0
Towards Robust Text Retrieval with Progressive LearningCode0
MultiQA: An Empirical Investigation of Generalization and Transfer in Reading ComprehensionCode0
A Compare-Aggregate Model for Matching Text SequencesCode0
A Co-Matching Model for Multi-choice Reading ComprehensionCode0
Subword-augmented Embedding for Cloze Reading ComprehensionCode0
Implicit Argument Prediction as Reading ComprehensionCode0
DCMN+: Dual Co-Matching Network for Multi-choice Reading ComprehensionCode0
Repartitioning of the ComplexWebQuestions DatasetCode0
Summarize-then-Answer: Generating Concise Explanations for Multi-hop Reading ComprehensionCode0
Multi-step Retriever-Reader Interaction for Scalable Open-domain Question AnsweringCode0
REPT: Bridging Language Models and Machine Reading Comprehension via Retrieval-Based Pre-trainingCode0
A Parallel-Hierarchical Model for Machine Comprehension on Sparse DataCode0
Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine ComprehensionCode0
Improving Machine Reading Comprehension with General Reading StrategiesCode0
Multi-tasking Dialogue Comprehension with Discourse ParsingCode0
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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