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

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Showing 626–650 of 10817 papers

TitleStatusHype
Context-Efficient Retrieval with Factual Decomposition—0
DomainCQA: Crafting Expert-Level QA from Domain-Specific Charts—0
ImF: Implicit Fingerprint for Large Language Models—0
Improved Alignment of Modalities in Large Vision Language Models—0
Can Vision-Language Models Answer Face to Face Questions in the Real-World?—0
ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation—0
Mind the Gap: Benchmarking Spatial Reasoning in Vision-Language ModelsCode1
VGAT: A Cancer Survival Analysis Framework Transitioning from Generative Visual Question Answering to Genomic ReconstructionCode0
BiblioPage: A Dataset of Scanned Title Pages for Bibliographic Metadata ExtractionCode0
LEGO-Puzzles: How Good Are MLLMs at Multi-Step Spatial Reasoning?—0
PAVE: Patching and Adapting Video Large Language ModelsCode1
Med3DVLM: An Efficient Vision-Language Model for 3D Medical Image AnalysisCode2
DeCAP: Context-Adaptive Prompt Generation for Debiasing Zero-shot Question Answering in Large Language Models—0
Open-Vocabulary Functional 3D Scene Graphs for Real-World Indoor Spaces—0
Where is this coming from? Making groundedness count in the evaluation of Document VQA models—0
A Survey of Large Language Model Agents for Question Answering—0
When is dataset cartography ineffective? Using training dynamics does not improve robustness against Adversarial SQuAD—0
MC-LLaVA: Multi-Concept Personalized Vision-Language ModelCode2
MAGIC-VQA: Multimodal And Grounded Inference with Commonsense Knowledge for Visual Question Answering—0
DiN: Diffusion Model for Robust Medical VQA with Semantic Noisy Labels—0
Synthetic Function Demonstrations Improve Generation in Low-Resource Programming Languages—0
LLaVAction: evaluating and training multi-modal large language models for action recognitionCode2
Expanding the Boundaries of Vision Prior Knowledge in Multi-modal Large Language Models—0
SLIDE: Sliding Localized Information for Document Extraction—0
Retrieval Augmented Generation and Understanding in Vision: A Survey and New OutlookCode3
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All datasetsSQuAD2.0SQuAD1.1HotpotQAPIQABoolQCOPATriviaQASQuAD1.1 devNatural QuestionsOpenBookQATruthfulQAMultiRC

Benchmark Results

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