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

Showing 13011325 of 10817 papers

TitleStatusHype
Exploring the State of the Art in Legal QA SystemsCode1
CLIP-Guided Vision-Language Pre-training for Question Answering in 3D ScenesCode1
Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language UnderstandingCode1
Evaluation of ChatGPT Family of Models for Biomedical Reasoning and ClassificationCode1
I2I: Initializing Adapters with Improvised KnowledgeCode1
ScandEval: A Benchmark for Scandinavian Natural Language ProcessingCode1
Creating Custom Event Data Without Dictionaries: A Bag-of-TricksCode1
Specialty-Oriented Generalist Medical AI for Chest CT ScreeningCode1
UKP-SQuARE v3: A Platform for Multi-Agent QA ResearchCode1
AISecKG: Knowledge Graph Dataset for Cybersecurity EducationCode1
Explicit Planning Helps Language Models in Logical ReasoningCode1
MGTBench: Benchmarking Machine-Generated Text DetectionCode1
Natural Language Reasoning, A SurveyCode1
Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation LearningCode1
Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language ModelsCode1
MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation ModelsCode1
Mordecai 3: A Neural Geoparser and Event GeocoderCode1
NS3D: Neuro-Symbolic Grounding of 3D Objects and RelationsCode1
TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question AnsweringCode1
Location-Free Scene Graph GenerationCode1
COVID-19 event extraction from Twitter via extractive question answering with continuous promptsCode1
AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-TuningCode1
Can AI-Generated Text be Reliably Detected?Code1
Can ChatGPT Replace Traditional KBQA Models? An In-depth Analysis of the Question Answering Performance of the GPT LLM FamilyCode1
Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language ModelsCode1
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Benchmark Results

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