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 1032610350 of 10817 papers

TitleStatusHype
Does RAG Introduce Unfairness in LLMs? Evaluating Fairness in Retrieval-Augmented Generation SystemsCode0
Acquiring Common Sense Spatial Knowledge through Implicit Spatial TemplatesCode0
Does Chain-of-Thought Reasoning Help Mobile GUI Agent? An Empirical StudyCode0
Document Haystacks: Vision-Language Reasoning Over Piles of 1000+ DocumentsCode0
MedLogic-AQA: Enhancing Medical Question Answering with Abstractive Models Focusing on Logical StructuresCode0
DocTabQA: Answering Questions from Long Documents Using TablesCode0
DocMIA: Document-Level Membership Inference Attacks against DocVQA ModelsCode0
MedMobile: A mobile-sized language model with expert-level clinical capabilitiesCode0
D-NET: A Pre-Training and Fine-Tuning Framework for Improving the Generalization of Machine Reading ComprehensionCode0
Answering Diverse Questions via Text Attached with Key Audio-Visual CluesCode0
Answering Count Queries with Explanatory EvidenceCode0
Med-PMC: Medical Personalized Multi-modal Consultation with a Proactive Ask-First-Observe-Next ParadigmCode0
Med-REFL: Medical Reasoning Enhancement via Self-Corrected Fine-grained ReflectionCode0
Proximity QA: Unleashing the Power of Multi-Modal Large Language Models for Spatial Proximity AnalysisCode0
A Survey of Video Datasets for Grounded Event UnderstandingCode0
Representation Learning for Answer Selection with LSTM-Based Importance WeightingCode0
Reading Between the Lanes: Text VideoQA on the RoadCode0
Pruning Pre-trained Language Models with Principled Importance and Self-regularizationCode0
MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generationCode0
Representation Learning for Text-level Discourse ParsingCode0
Training Heterogeneous Features in Sequence to Sequence Tasks: Latent Enhanced Multi-filter Seq2Seq ModelCode0
MeeQA: Natural Questions in Meeting TranscriptsCode0
PSYCHIC: A Neuro-Symbolic Framework for Knowledge Graph Question-Answering GroundingCode0
DLP-LoRA: Efficient Task-Specific LoRA Fusion with a Dynamic, Lightweight Plugin for Large Language ModelsCode0
Ontology-Guided, Hybrid Prompt Learning for Generalization in Knowledge Graph Question AnsweringCode0
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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