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
Automatic Evaluation vs. User Preference in Neural Textual QuestionAnswering over COVID-19 Scientific Literature0
Automatic Feedback Generation for Short Answer Questions using Answer Diagnostic Graphs0
Automatic Generation of Context-Based Fill-in-the-Blank Exercises Using Co-occurrence Likelihoods and Google n-grams0
Automatic Generation of Multiple-Choice Questions0
Automatic Judgment Prediction via Legal Reading Comprehension0
Automatic learner summary assessment for reading comprehension0
Automatic Mining of Salient Events from Multiple Documents0
Automatic Question Generation using Relative Pronouns and Adverbs0
Automatic True/False Question Generation for Educational Purpose0
Automatic Word Segmentation and Part-of-Speech Tagging of Ancient Chinese Based on BERT Model0
Automating Idea Unit Segmentation and Alignment for Assessing Reading Comprehension via Summary Protocol Analysis0
Automating Reading Comprehension by Generating Question and Answer Pairs0
A Vietnamese Dataset for Evaluating Machine Reading Comprehension0
A Vietnamese Dataset for Evaluating Machine Reading Comprehension0
AWS CORD-19 Search: A Neural Search Engine for COVID-19 Literature0
Benben: A Chinese Intelligent Conversational Robot0
Comparison of Open-Source and Proprietary LLMs for Machine Reading Comprehension: A Practical Analysis for Industrial Applications0
Benchmarks for Pirá 2.0, a Reading Comprehension Dataset about the Ocean, the Brazilian Coast, and Climate Change0
Benefits of Intermediate Annotations in Reading Comprehension0
BERT-based knowledge extraction method of unstructured domain text0
BERT-CoQAC: BERT-based Conversational Question Answering in Context0
Better Retrieval May Not Lead to Better Question Answering0
Piecing Together Clues: A Benchmark for Evaluating the Detective Skills of Large Language Models0
Bi-directional Cognitive Thinking Network for Machine Reading Comprehension0
Bi-directional CognitiveThinking Network for Machine Reading Comprehension0
Bilingual Keyword Extraction and its Educational Application0
Bilingual Text Extraction as Reading Comprehension0
Biomedical Question Answering: A Survey of Approaches and Challenges0
BioMistral-NLU: Towards More Generalizable Medical Language Understanding through Instruction Tuning0
BiQuAD: Towards QA based on deeper text understanding0
BiTeM at WNUT 2020 Shared Task-1: Named Entity Recognition over Wet Lab Protocols using an Ensemble of Contextual Language Models0
BizBench: A Quantitative Reasoning Benchmark for Business and Finance0
BLCU-NLP at COIN-Shared Task1: Stagewise Fine-tuning BERT for Commonsense Inference in Everyday Narrations0
BloombergGPT: A Large Language Model for Finance0
Boosting Search Engines with Interactive Agents0
Brainstorming Brings Power to Large Language Models of Knowledge Reasoning0
Bridging Information-Seeking Human Gaze and Machine Reading Comprehension0
Bridging the Gap between Language Model and Reading Comprehension: Unsupervised MRC via Self-Supervision0
Bridging the Gap between Language Models and Cross-Lingual Sequence Labeling0
Bridging The Gap: Entailment Fused-T5 for Open-retrieval Conversational Machine Reading Comprehension0
Broad Context Language Modeling as Reading Comprehension0
BUAP: Evaluating Features for Multilingual and Cross-Level Semantic Textual Similarity0
Building A User-Centric and Content-Driven Socialbot0
Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension0
Bypassing DARCY Defense: Indistinguishable Universal Adversarial Triggers0
CAESAR: Context Awareness Enabled Summary-Attentive Reader0
Calibration of Machine Reading Systems at Scale0
Calibration of Machine Reading Systems at Scale0
CalibreNet: Calibration Networks for Multilingual Sequence Labeling0
CALOR-QUEST : generating a training corpus for Machine Reading Comprehension models from shallow semantic annotations0
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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