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 651700 of 1760 papers

TitleStatusHype
Approximating Givenness in Content Assessment through Distributional Semantics0
Challenging Reading Comprehension on Daily Conversation: Passage Completion on Multiparty Dialog0
Exploiting Multiple Sources for Open-Domain Hypernym Discovery0
Argument structure of adverbial derivatives in Russian0
Graph Sequential Network for Reasoning over Sequences0
Exploring and Exploiting Multi-Granularity Representations for Machine Reading Comprehension0
Exploring Autonomous Agents through the Lens of Large Language Models: A Review0
ChatGPT-4 as a Tool for Reviewing Academic Books in Spanish0
Exploring Gap Filling as a Cheaper Alternative to Reading Comprehension Questionnaires when Evaluating Machine Translation for Gisting0
Exploring Graph-structured Passage Representation for Multi-hop Reading Comprehension with Graph Neural Networks0
Explicit Utilization of General Knowledge in Machine Reading Comprehension0
EXPLORING NEURAL ARCHITECTURE SEARCH FOR LANGUAGE TASKS0
Entity Linking meets Word Sense Disambiguation: a Unified Approach0
Exploring Question Understanding and Adaptation in Neural-Network-Based Question Answering0
ChatPRCS: A Personalized Support System for English Reading Comprehension based on ChatGPT0
Exploring Semantic Properties of Sentence Embeddings0
Exploring the BERT Cross-Lingual Transferability: a Case Study in Reading Comprehension0
Exploring the Intersection of Short Answer Assessment, Authorship Attribution, and Plagiarism Detection0
Exploring the Nexus of Large Language Models and Legal Systems: A Short Survey0
Exploring the Potential of Large Language Models for Estimating the Reading Comprehension Question Difficulty0
Entity Linking for Tweets0
Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension0
Grounding Gradable Adjectives through Crowdsourcing0
Eye Tracking as a Tool for Machine Translation Error Analysis0
Entity-Centric Joint Modeling of Japanese Coreference Resolution and Predicate Argument Structure Analysis0
Facial Electromyography-based Adaptive Virtual Reality Gaming for Cognitive Training0
Ensemble Learning-Based Approach for Improving Generalization Capability of Machine Reading Comprehension Systems0
Building A User-Centric and Content-Driven Socialbot0
Ensemble approach for natural language question answering problem0
Addressing Semantic Drift in Generative Question Answering with Auxiliary Extraction0
Enhancing Text-to-Image Diffusion Transformer via Split-Text Conditioning0
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
FCM: A Fine-grained Comparison Model for Multi-turn Dialogue Reasoning0
Feature-augmented Machine Reading Comprehension with Auxiliary Tasks0
Feature-Rich Two-Stage Logistic Regression for Monolingual Alignment0
BUAP: Evaluating Features for Multilingual and Cross-Level Semantic Textual Similarity0
Applications of BERT Based Sequence Tagging Models on Chinese Medical Text Attributes Extraction0
Have We Reached AGI? Comparing ChatGPT, Claude, and Gemini to Human Literacy and Education Benchmarks0
Enhancing Robustness of Retrieval-Augmented Language Models with In-Context Learning0
Broad Context Language Modeling as Reading Comprehension0
Few-shot Mining of Naturally Occurring Inputs and Outputs0
Apples to Apples: Learning Semantics of Common Entities Through a Novel Comprehension Task0
Filling a Knowledge Graph with a Crowd0
Enhancing Pre-Trained Generative Language Models with Question Attended Span Extraction on Machine Reading Comprehension0
Enhancing Multiple-choice Machine Reading Comprehension by Punishing Illogical Interpretations0
Bridging The Gap: Entailment Fused-T5 for Open-retrieval Conversational Machine Reading Comprehension0
Clinical Reading Comprehension with Encoder-Decoder Models Enhanced by Direct Preference Optimization0
Clozer: Adaptable Data Augmentation for Cloze-style Reading Comprehension0
Graph-combined Coreference Resolution Methods on Conversational Machine Reading Comprehension with Pre-trained Language Model0
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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