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 3776–3800 of 10817 papers

TitleStatusHype
OneEncoder: A Lightweight Framework for Progressive Alignment of Modalities—0
Uncertainty-Guided Self-Questioning and Answering for Video-Language Alignment—0
Contextual Breach: Assessing the Robustness of Transformer-based QA Models—0
HALO: Hallucination Analysis and Learning Optimization to Empower LLMs with Retrieval-Augmented Context for Guided Clinical Decision MakingCode0
StruEdit: Structured Outputs Enable the Fast and Accurate Knowledge Editing for Large Language Models—0
NEVLP: Noise-Robust Framework for Efficient Vision-Language Pre-training—0
Explore the Hallucination on Low-level Perception for MLLMs—0
A Benchmark Dataset with Larger Context for Non-Factoid Question Answering over Islamic Text—0
Guiding Vision-Language Model Selection for Visual Question-Answering Across Tasks, Domains, and Knowledge TypesCode0
Active Learning to Guide Labeling Efforts for Question Difficulty EstimationCode0
QTG-VQA: Question-Type-Guided Architectural for VideoQA Systems—0
Expediting and Elevating Large Language Model Reasoning via Hidden Chain-of-Thought Decoding—0
Electrocardiogram Report Generation and Question Answering via Retrieval-Augmented Self-Supervised Modeling—0
KodeXv0.1: A Family of State-of-the-Art Financial Large Language Models—0
Contri(e)ve: Context + Retrieve for Scholarly Question Answering—0
Contextual Evaluation of Large Language Models for Classifying Tropical and Infectious Diseases—0
Experimenting with Legal AI Solutions: The Case of Question-Answering for Access to Justice—0
Enhancing Q&A Text Retrieval with Ranking Models: Benchmarking, fine-tuning and deploying Rerankers for RAG—0
OmniQuery: Contextually Augmenting Captured Multimodal Memory to Enable Personal Question Answering—0
Source2Synth: Synthetic Data Generation and Curation Grounded in Real Data Sources—0
An Evaluation Framework for Attributed Information Retrieval using Large Language ModelsCode0
Top-down Activity Representation Learning for Video Question Answering—0
Multi-object event graph representation learning for Video Question Answering—0
Integrating SPARQL and LLMs for Question Answering over Scholarly Data Sources—0
Learning to Compress Contexts for Efficient Knowledge-based Visual Question Answering—0
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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