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 13511400 of 1760 papers

TitleStatusHype
CALOR-QUEST : un corpus d'entra\^ et d'\'evaluation pour la compr\'ehension automatique de textes (Machine reading comprehension is a task related to Question-Answering where questions are not generic in scope but are related to a particular document)0
CAMB at CWI Shared Task 2018: Complex Word Identification with Ensemble-Based Voting0
Can GPT Redefine Medical Understanding? Evaluating GPT on Biomedical Machine Reading Comprehension0
Can Large Language Models Make the Grade? An Empirical Study Evaluating LLMs Ability to Mark Short Answer Questions in K-12 Education0
Can LLMs Augment Low-Resource Reading Comprehension Datasets? Opportunities and Challenges0
Can LLMs Grade Short-Answer Reading Comprehension Questions : An Empirical Study with a Novel Dataset0
Can Question Generation Debias Question Answering Models? A Case Study on Question–Context Lexical Overlap0
CausalBench: A Comprehensive Benchmark for Causal Learning Capability of LLMs0
Causal Tree Extraction from Medical Case Reports: A Novel Task for Experts-like Text Comprehension0
CFO: A Framework for Building Production NLP Systems0
Challenges in Information-Seeking QA: Unanswerable Questions and Paragraph Retrieval0
Challenges in Procedural Multimodal Machine Comprehension:A Novel Way To Benchmark0
Challenging Reading Comprehension on Daily Conversation: Passage Completion on Multiparty Dialog0
ChartText: Linking Text with Charts in Documents0
ChatGPT-4 as a Tool for Reviewing Academic Books in Spanish0
Integrating LLM, EEG, and Eye-Tracking Biomarker Analysis for Word-Level Neural State Classification in Semantic Inference Reading Comprehension0
ChatGPT-EDSS: Empathetic Dialogue Speech Synthesis Trained from ChatGPT-derived Context Word Embeddings0
ChatPRCS: A Personalized Support System for English Reading Comprehension based on ChatGPT0
ChemistryQA: A Complex Question Answering Dataset from Chemistry0
Chinese Hypernym-Hyponym Extraction from User Generated Categories0
Choose Your Own Adventure: Interactive E-Books to Improve Word Knowledge and Comprehension Skills0
CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension0
CLCM - A Linguistic Resource for Effective Simplification of Instructions in the Crisis Management Domain and its Evaluations0
CLER: Cross-task Learning with Expert Representation to Generalize Reading and Understanding0
Clinical Concept and Relation Extraction Using Prompt-based Machine Reading Comprehension0
Clinical Reading Comprehension with Encoder-Decoder Models Enhanced by Direct Preference Optimization0
CliqueParcel: An Approach For Batching LLM Prompts That Jointly Optimizes Efficiency And Faithfulness0
Clozer: Adaptable Data Augmentation for Cloze-style Reading Comprehension0
Clozer”:" Adaptable Data Augmentation for Cloze-style Reading Comprehension0
CL-ReKD: Cross-lingual Knowledge Distillation for Multilingual Retrieval Question Answering0
CLUF: a Neural Model for Second Language Acquisition Modeling0
Coarse-grained decomposition and fine-grained interaction for multi-hop question answering0
Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models0
Coarse-to-Fine Question Answering for Long Documents0
Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension0
Coherent Zero-Shot Visual Instruction Generation0
Collecting high-quality adversarial data for machine reading comprehension tasks with humans and models in the loop0
Combining Formal and Distributional Models of Temporal and Intensional Semantics0
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning0
CoMeT: Integrating different levels of linguistic modeling for meaning assessment0
CoMiC: Adapting a Short Answer Assessment System for Answer Selection0
Commonsense Evidence Generation and Injection in Reading Comprehension0
Commonsense Inference in Natural Language Processing (COIN) - Shared Task Report0
Commonsense knowledge adversarial dataset that challenges ELECTRA0
Commonsense Knowledge Base Completion and Generation0
Commonsense Knowledge + BERT for Level 2 Reading Comprehension Ability Test0
Comparative Analysis of Neural QA models on SQuAD0
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
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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