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 101150 of 1760 papers

TitleStatusHype
LawLuo: A Multi-Agent Collaborative Framework for Multi-Round Chinese Legal Consultation0
Harmonizing Visual Text Comprehension and GenerationCode2
How to Engage Your Readers? Generating Guiding Questions to Promote Active ReadingCode0
Clinical Reading Comprehension with Encoder-Decoder Models Enhanced by Direct Preference Optimization0
Multi-Grained Query-Guided Set Prediction Network for Grounded Multimodal Named Entity RecognitionCode1
Struct-X: Enhancing Large Language Models Reasoning with Structured Data0
Large Language Models as Misleading Assistants in Conversation0
DOCBENCH: A Benchmark for Evaluating LLM-based Document Reading SystemsCode2
Look Within, Why LLMs Hallucinate: A Causal Perspective0
sPhinX: Sample Efficient Multilingual Instruction Fine-Tuning Through N-shot Guided Prompting0
Have We Reached AGI? Comparing ChatGPT, Claude, and Gemini to Human Literacy and Education Benchmarks0
AgentInstruct: Toward Generative Teaching with Agentic Flows0
RVISA: Reasoning and Verification for Implicit Sentiment Analysis0
MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in EducationCode0
Evaluation of Instruction-Following Ability for Large Language Models on Story-Ending Generation0
It Is Not About What You Say, It Is About How You Say It: A Surprisingly Simple Approach for Improving Reading Comprehension0
FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language ModelsCode1
Improving Visual Commonsense in Language Models via Multiple Image GenerationCode1
Comparison of Open-Source and Proprietary LLMs for Machine Reading Comprehension: A Practical Analysis for Industrial Applications0
Exploring the Robustness of Language Models for Tabular Question Answering via Attention Analysis0
InternalInspector I^2: Robust Confidence Estimation in LLMs through Internal States0
VEGA: Learning Interleaved Image-Text Comprehension in Vision-Language Large Models0
Unused information in token probability distribution of generative LLM: improving LLM reading comprehension through calculation of expected valuesCode0
2DP-2MRC: 2-Dimensional Pointer-based Machine Reading Comprehension Method for Multimodal Moment Retrieval0
M-QALM: A Benchmark to Assess Clinical Reading Comprehension and Knowledge Recall in Large Language Models via Question AnsweringCode0
FairytaleQA Translated: Enabling Educational Question and Answer Generation in Less-Resourced LanguagesCode0
Coherent Zero-Shot Visual Instruction Generation0
Analyzing Temporal Complex Events with Large Language Models? A Benchmark towards Temporal, Long Context UnderstandingCode0
Unsupervised Distractor Generation via Large Language Model Distilling and Counterfactual Contrastive Decoding0
TabPedia: Towards Comprehensive Visual Table Understanding with Concept SynergyCode2
Brainstorming Brings Power to Large Language Models of Knowledge Reasoning0
Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training0
Long-Span Question-Answering: Automatic Question Generation and QA-System Ranking via Side-by-Side Evaluation0
Automated Focused Feedback Generation for Scientific Writing AssistanceCode0
Can GPT Redefine Medical Understanding? Evaluating GPT on Biomedical Machine Reading Comprehension0
DGRC: An Effective Fine-tuning Framework for Distractor Generation in Chinese Multi-choice Reading Comprehension0
Time Matters: Enhancing Pre-trained News Recommendation Models with Robust User Dwell Time Injection0
MTVQA: Benchmarking Multilingual Text-Centric Visual Question AnsweringCode2
Benchmarking Large Language Models on CFLUE -- A Chinese Financial Language Understanding Evaluation DatasetCode3
Auto FAQ Generation0
MMGER: Multi-modal and Multi-granularity Generative Error Correction with LLM for Joint Accent and Speech Recognition0
Compressing Long Context for Enhancing RAG with AMR-based Concept Distillation0
Can Large Language Models Make the Grade? An Empirical Study Evaluating LLMs Ability to Mark Short Answer Questions in K-12 Education0
UQA: Corpus for Urdu Question AnsweringCode0
QLSC: A Query Latent Semantic Calibrator for Robust Extractive Question Answering0
Efficient LLM Inference with Kcache0
Enhancing Pre-Trained Generative Language Models with Question Attended Span Extraction on Machine Reading Comprehension0
Transfer Learning Enhanced Single-choice Decision for Multi-choice Question Answering0
From Multiple-Choice to Extractive QA: A Case Study for English and ArabicCode0
PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Rational Reasoner / IDOLTest80.6Unverified
2AMR-LE-EnsembleTest80Unverified
3MERIt-deberta-v2-xxlarge deberta.v2.xxlarge.path.override_True.norm_1.1.0.w2.A100.cp200.s42Test79.3Unverified
4MERIt(MERIt-deberta-v2-xxlarge )Test79.3Unverified
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