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 13011350 of 1760 papers

TitleStatusHype
Are you tough enough? Framework for Robustness Validation of Machine Comprehension SystemsCode0
未登錄詞之向量表示法模型於中文機器閱讀理解之應用 (An OOV Word Embedding Framework for Chinese Machine Reading Comprehension)0
Towards an Automatic Text Comprehension for the Arabic Question-Answering: Semantic and Logical Representation of Texts0
Visual Question Answering as Reading Comprehension0
Multi-granularity hierarchical attention fusion networks for reading comprehension and question answeringCode0
A Deep Cascade Model for Multi-Document Reading Comprehension0
Recurrently Controlled Recurrent NetworksCode0
Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions0
Implicit Argument Prediction as Reading ComprehensionCode0
Effective Subword Segmentation for Text ComprehensionCode0
Exploiting Explicit Paths for Multi-hop Reading ComprehensionCode0
Textbook Question Answering with Multi-modal Context Graph Understanding and Self-supervised Open-set Comprehension0
An Adaption of BIOASQ Question Answering dataset for Machine Reading systems by Manual Annotations of Answer Spans.0
Normalization in Context: Inter-Annotator Agreement for Meaning-Based Target Hypothesis Annotation0
Visual Interrogation of Attention-Based Models for Natural Language Inference and Machine Comprehension0
Work Smart - Reducing Effort in Short-Answer Grading0
Automatic Opinion Question GenerationCode0
UCL Machine Reading Group: Four Factor Framework For Fact Finding (HexaF)0
Learning to Describe Phrases with Local and Global ContextsCode0
Textual Entailment based Question Generation0
Team SWEEPer: Joint Sentence Extraction and Fact Checking with Pointer Networks0
Improving Machine Reading Comprehension with General Reading StrategiesCode0
ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension0
Are you tough enough? Framework for Robustness Validation of Machine Comprehension SystemsCode0
Lightweight Convolutional Approaches to Reading Comprehension on SQuAD0
A Span-Extraction Dataset for Chinese Machine Reading ComprehensionCode0
Composing RNNs and FSTs for Small Data: Recovering Missing Characters in Old Hawaiian Text0
Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension0
U-Net: Machine Reading Comprehension with Unanswerable QuestionsCode0
Query Tracking for E-commerce Conversational Search: A Machine Comprehension Perspective0
FlowQA: Grasping Flow in History for Conversational Machine ComprehensionCode0
Entity Tracking Improves Cloze-style Reading ComprehensionCode0
Commonsense Knowledge Base Completion and Generation0
A Multi-answer Multi-task Framework for Real-world Machine Reading Comprehension0
Speed Reading: Learning to Read ForBackward via ShuttleCode0
QuAC: Question Answering in Context0
Listening Comprehension over Argumentative Content0
Ranking Paragraphs for Improving Answer Recall in Open-Domain Question AnsweringCode0
Answer-focused and Position-aware Neural Question Generation0
Multi-Granular Sequence Encoding via Dilated Compositional Units for Reading Comprehension0
A dataset and baselines for sequential open-domain question answering0
Cut to the Chase: A Context Zoom-in Network for Reading Comprehension0
MemoReader: Large-Scale Reading Comprehension through Neural Memory Controller0
A Nil-Aware Answer Extraction Framework for Question AnsweringCode0
Somm: Into the Model0
未登錄詞之向量表示法模型於中文機器閱讀理解之應用 (An OOV Word Embedding Framework for Chinese Machine Reading Comprehension) [In Chinese]0
Recovering Missing Characters in Old Hawaiian Writing0
Denoise while Aggregating: Collaborative Learning in Open-Domain Question Answering0
Stochastic Answer Networks for SQuAD 2.0Code0
A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements0
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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