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 351400 of 1760 papers

TitleStatusHype
Advances in Multi-turn Dialogue Comprehension: A Survey0
A Survey on Machine Reading Comprehension: Tasks, Evaluation Metrics and Benchmark Datasets0
A Comparative Study of Word Embeddings for Reading Comprehension0
Dependent Gated Reading for Cloze-Style Question Answering0
Deriving Commonsense Inference Tasks from Interactive Fictions0
Designing a Tag-Based Statistical Math Word Problem Solver with Reasoning and Explanation0
Developing ChatGPT for Biology and Medicine: A Complete Review of Biomedical Question Answering0
Discrete Reasoning Templates for Natural Language Understanding0
A Survey on Machine Reading Comprehension Systems0
A Survey on Explainability in Machine Reading Comprehension0
Advancements and Challenges in Bangla Question Answering Models: A Comprehensive Review0
A Study on Contextualized Language Modeling for Machine Reading Comprehension0
Commonsense Knowledge + BERT for Level 2 Reading Comprehension Ability Test0
2DP-2MRC: 2-Dimensional Pointer-based Machine Reading Comprehension Method for Multimodal Moment Retrieval0
Delta Embedding Learning0
A study of Vietnamese readability assessing through semantic and statistical features0
Commonsense Inference in Natural Language Processing (COIN) - Shared Task Report0
A Study of the Tasks and Models in Machine Reading Comprehension0
Analyzing Multiple-Choice Reading and Listening Comprehension Tests0
DiVA-DocRE: A Discriminative and Voice-Aware Paradigm for Document-Level Relation Extraction0
Commonsense Evidence Generation and Injection in Reading Comprehension0
A Strong Lexical Matching Method for the Machine Comprehension Test0
Commonsense knowledge adversarial dataset that challenges ELECTRA0
Commonsense Knowledge Base Completion and Generation0
Analyzing and Mitigating Interference in Neural Architecture Search0
Comparative Analysis of Neural QA models on SQuAD0
A Survey of Machine Narrative Reading Comprehension Assessments0
Complementary Advantages of ChatGPTs and Human Readers in Reasoning: Evidence from English Text Reading Comprehension0
Complex Factoid Question Answering with a Free-Text Knowledge Graph0
Complex Reading Comprehension Through Question Decomposition0
Complex Word Identification Based on Frequency in a Learner Corpus0
Composing Answer from Multi-spans for Reading Comprehension0
Composing RNNs and FSTs for Small Data: Recovering Missing Characters in Old Hawaiian Text0
Composing RNNs and FSTs for Small Data: Recovering Missing Characters in Old Hawaiian Text0
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehension0
Comprehending Knowledge Graphs with Large Language Models for Recommender Systems0
Comprehensive Multi-Dataset Evaluation of Reading Comprehension0
Compressing Long Context for Enhancing RAG with AMR-based Concept Distillation0
CoMiC: Adapting a Short Answer Assessment System for Answer Selection0
Computational Approaches to Sentence Completion0
CoMeT: Integrating different levels of linguistic modeling for meaning assessment0
Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets0
Analyzing Zero-shot Cross-lingual Transfer in Supervised NLP Tasks0
A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements0
Deleter: Leveraging BERT to Perform Unsupervised Successive Text Compression0
Denoise while Aggregating: Collaborative Learning in Open-Domain Question Answering0
Constructing Datasets for Multi-hop Reading Comprehension Across Documents0
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning0
Combining Formal and Distributional Models of Temporal and Intensional Semantics0
Assessing Distractors in Multiple-Choice Tests0
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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