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 12511275 of 10817 papers

TitleStatusHype
Baby's CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact ModelsCode1
ADEM-VL: Adaptive and Embedded Fusion for Efficient Vision-Language TuningCode1
Differentiable Reasoning on Large Knowledge Bases and Natural LanguageCode1
Encoding and Controlling Global Semantics for Long-form Video Question AnsweringCode1
End-to-End Training of Neural Retrievers for Open-Domain Question AnsweringCode1
Engineering flexible machine learning systems by traversing functionally-invariant pathsCode1
Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under DiscussionCode1
Enhancing Complex Question Answering over Knowledge Graphs through Evidence Pattern RetrievalCode1
Divide and Conquer: Text Semantic Matching with Disentangled Keywords and IntentsCode1
Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model EvaluationCode1
Enhancing Multi-modal and Multi-hop Question Answering via Structured Knowledge and Unified Retrieval-GenerationCode1
Enhancing Table Recognition with Vision LLMs: A Benchmark and Neighbor-Guided Toolchain ReasonerCode1
DyGKT: Dynamic Graph Learning for Knowledge TracingCode1
Entailment Tree Explanations via Iterative Retrieval-Generation ReasonerCode1
Entity-Enriched Neural Models for Clinical Question AnsweringCode1
EntQA: Entity Linking as Question AnsweringCode1
Attention-Based Context Aware Reasoning for Situation RecognitionCode1
ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive LearningCode1
Detecting Hate Speech in Multi-modal MemesCode1
Automatically Generating Cause-and-Effect Questions from PassagesCode1
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resourcesCode1
Detecting and Preventing Hallucinations in Large Vision Language ModelsCode1
An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP TasksCode1
Ethics Sheets for AI TasksCode1
DeVLBert: Learning Deconfounded Visio-Linguistic RepresentationsCode1
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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