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 1251–1275 of 10817 papers

TitleStatusHype
CogMG: Collaborative Augmentation Between Large Language Model and Knowledge GraphCode1
Code-Style In-Context Learning for Knowledge-Based Question AnsweringCode1
Automated Crossword SolvingCode1
Callee: Recovering Call Graphs for Binaries with Transfer and Contrastive LearningCode1
IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language ReasoningCode1
IDA-VLM: Towards Movie Understanding via ID-Aware Large Vision-Language ModelCode1
HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal ReasoningCode1
Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM CollaborationCode1
Anchor-based Large Language ModelsCode1
Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model EvaluationCode1
Check It Again: Progressive Visual Question Answering via Visual EntailmentCode1
Improving BERT with Syntax-aware Local AttentionCode1
Automated question generation and question answering from Turkish textsCode1
CommonsenseQA: A Question Answering Challenge Targeting Commonsense KnowledgeCode1
Improving LLM Reasoning with Multi-Agent Tree-of-Thought Validator AgentCode1
Harnessing Large Language Models for Knowledge Graph Question Answering via Adaptive Multi-Aspect Retrieval-AugmentationCode1
CompAct: Compressing Retrieved Documents Actively for Question AnsweringCode1
Improving Passage Retrieval with Zero-Shot Question GenerationCode1
ChatVLA: Unified Multimodal Understanding and Robot Control with Vision-Language-Action ModelCode1
Automatically Generating Cause-and-Effect Questions from PassagesCode1
Fine-tuned LLMs Know More, Hallucinate Less with Few-Shot Sequence-to-Sequence Semantic Parsing over WikidataCode1
Check It Again:Progressive Visual Question Answering via Visual EntailmentCode1
An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP TasksCode1
Complex Reasoning over Logical Queries on Commonsense Knowledge GraphsCode1
Harnessing Multi-Role Capabilities of Large Language Models for Open-Domain Question AnsweringCode1
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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