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 15261550 of 10817 papers

TitleStatusHype
End-to-End Training of Neural Retrievers for Open-Domain Question AnsweringCode1
A Symmetric Dual Encoding Dense Retrieval Framework for Knowledge-Intensive Visual Question AnsweringCode1
MMBERT: Multimodal BERT Pretraining for Improved Medical VQACode1
Enhancing Contextual Understanding in Large Language Models through Contrastive DecodingCode1
Information Theoretic Representation DistillationCode1
Enhancing In-Context Learning with Answer Feedback for Multi-Span Question AnsweringCode1
Enhancing LLM's Cognition via StructurizationCode1
Initial Nugget Evaluation Results for the TREC 2024 RAG Track with the AutoNuggetizer FrameworkCode1
CL-ReLKT: Cross-lingual Language Knowledge Transfer for Multilingual Retrieval Question AnsweringCode1
SentenceMIM: A Latent Variable Language ModelCode1
CLTR: An End-to-End, Transformer-Based System for Cell Level Table Retrieval and Table Question AnsweringCode1
Enhancing Vision-Language Pre-Training with Jointly Learned Questioner and Dense CaptionerCode1
ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive LearningCode1
BioPlanner: Automatic Evaluation of LLMs on Protocol Planning in BiologyCode1
BioProBench: Comprehensive Dataset and Benchmark in Biological Protocol Understanding and ReasoningCode1
Modeling Worlds in TextCode1
Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented GenerationCode1
Clover: Towards A Unified Video-Language Alignment and Fusion ModelCode1
InfoBERT: Improving Robustness of Language Models from An Information Theoretic PerspectiveCode1
InforMask: Unsupervised Informative Masking for Language Model PretrainingCode1
EntQA: Entity Linking as Question AnsweringCode1
Entailment Tree Explanations via Iterative Retrieval-Generation ReasonerCode1
Entity-Based Knowledge Conflicts in Question AnsweringCode1
Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip PredictionCode1
Injecting Numerical Reasoning Skills into 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