SOTAVerified

Question Answering

Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.

( Image credit: SQuAD )

Papers

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Showing 6151–6175 of 10817 papers

TitleStatusHype
How Well can We Learn Interpretable Entity Types from Text?—0
How Well Can Vison-Language Models Understand Humans' Intention? An Open-ended Theory of Mind Question Evaluation Benchmark—0
How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey—0
How Transferable are Reasoning Patterns in VQA?—0
Continuous Perception Benchmark—0
A Survey on State-of-the-art Techniques for Knowledge Graphs Construction and Challenges ahead—0
MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering—0
MedExpQA: Multilingual Benchmarking of Large Language Models for Medical Question Answering—0
A Multi-World Approach to Question Answering about Real-World Scenes based on Uncertain Input—0
How to Seq2seq for SQL—0
MedFuzz: Exploring the Robustness of Large Language Models in Medical Question Answering—0
How to Pre-Train Your Model? Comparison of Different Pre-Training Models for Biomedical Question Answering—0
Continuous Active Learning Using Pretrained Transformers—0
MedGo: A Chinese Medical Large Language Model—0
MedGPT: Medical Concept Prediction from Clinical Narratives—0
MedHal: An Evaluation Dataset for Medical Hallucination Detection—0
How to Mitigate Information Loss in Knowledge Graphs for GraphRAG: Leveraging Triple Context Restoration and Query-Driven Feedback—0
MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models—0
MeDiaQA: A Question Answering Dataset on Medical Dialogues—0
ECNUCS: Recognizing Cross-lingual Textual Entailment Using Multiple Text Similarity and Text Difference Measures—0
Medical Exam Question Answering with Large-scale Reading Comprehension—0
Medical Knowledge-enriched Textual Entailment Framework—0
ECNU: Using Multiple Sources of CQA-based Information for Answers Selection and YES/NO Response Inference—0
A Generate-Validate Approach to Answering Questions about Qualitative Relationships—0
How to make qubits speak—0
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All datasetsSQuAD2.0SQuAD1.1HotpotQAPIQABoolQCOPATriviaQASQuAD1.1 devNatural QuestionsOpenBookQATruthfulQAMultiRC

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94—Unverified
2FPNet (ensemble)EM90.87—Unverified
3IE-NetV2 (ensemble)EM90.86—Unverified
4SA-Net on Albert (ensemble)EM90.72—Unverified
5SA-Net-V2 (ensemble)EM90.68—Unverified
6FPNet (ensemble)EM90.6—Unverified
7Retro-Reader (ensemble)EM90.58—Unverified
8EntitySpanFocusV2 (ensemble)EM90.52—Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49—Unverified
10EntitySpanFocus+AT (ensemble)EM90.45—Unverified