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 20262050 of 10817 papers

TitleStatusHype
Context Awareness Gate For Retrieval Augmented GenerationCode1
AllenAct: A Framework for Embodied AI ResearchCode1
CodeQueries: A Dataset of Semantic Queries over CodeCode1
Asking Clarification Questions to Handle Ambiguity in Open-Domain QACode1
Learning to Ask Like a PhysicianCode1
ConditionalQA: A Complex Reading Comprehension Dataset with Conditional AnswersCode1
A Dataset and Baselines for Visual Question Answering on ArtCode1
Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation ExtractionCode1
Learning to Discretely Compose Reasoning Module Networks for Video CaptioningCode1
Conformal Alignment: Knowing When to Trust Foundation Models with GuaranteesCode1
Coarse-to-Fine Vision-Language Pre-training with Fusion in the BackboneCode1
Asking Questions the Human Way: Scalable Question-Answer Generation from Text CorpusCode1
TurkishMMLU: Measuring Massive Multitask Language Understanding in TurkishCode1
CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic SurgeryCode1
COBRA: Contrastive Bi-Modal Representation AlgorithmCode1
Learning to Perturb Word Embeddings for Out-of-distribution QACode1
TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse LanguagesCode1
LLaSA: A Multimodal LLM for Human Activity Analysis Through Wearable and Smartphone SensorsCode1
Learning to Poison Large Language Models for Downstream ManipulationCode1
UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-world Document AnalysisCode1
CodeQA: A Question Answering Dataset for Source Code ComprehensionCode1
LLaVA-SpaceSGG: Visual Instruct Tuning for Open-vocabulary Scene Graph Generation with Enhanced Spatial RelationsCode1
LogEval: A Comprehensive Benchmark Suite for Large Language Models In Log AnalysisCode1
ComQA:Compositional Question Answering via Hierarchical Graph Neural NetworksCode1
LIQUID: A Framework for List Question Answering Dataset GenerationCode1
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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