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 951–975 of 10817 papers

TitleStatusHype
REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question AnsweringCode1
MoZIP: A Multilingual Benchmark to Evaluate Large Language Models in Intellectual PropertyCode1
Efficient Temporal Extrapolation of Multimodal Large Language Models with Temporal Grounding BridgeCode1
EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge SummariesCode1
Bridging the Gap between 2D and 3D Visual Question Answering: A Fusion Approach for 3D VQACode1
Interactive-KBQA: Multi-Turn Interactions for Knowledge Base Question Answering with Large Language ModelsCode1
Leveraging Large Language Models for Concept Graph Recovery and Question Answering in NLP EducationCode1
SIMPLOT: Enhancing Chart Question Answering by Distilling EssentialsCode1
Uncertainty-Aware Evaluation for Vision-Language ModelsCode1
Visual Hallucinations of Multi-modal Large Language ModelsCode1
Triad: A Framework Leveraging a Multi-Role LLM-based Agent to Solve Knowledge Base Question AnsweringCode1
Learning to Poison Large Language Models for Downstream ManipulationCode1
Cognitive Visual-Language Mapper: Advancing Multimodal Comprehension with Enhanced Visual Knowledge AlignmentCode1
DrBenchmark: A Large Language Understanding Evaluation Benchmark for French Biomedical DomainCode1
BiMediX: Bilingual Medical Mixture of Experts LLMCode1
MARS: Meaning-Aware Response Scoring for Uncertainty Estimation in Generative LLMsCode1
LEIA: Facilitating Cross-lingual Knowledge Transfer in Language Models with Entity-based Data AugmentationCode1
Benchmarking Knowledge Boundary for Large Language Models: A Different Perspective on Model EvaluationCode1
BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity AllocationCode1
LongAgent: Scaling Language Models to 128k Context through Multi-Agent CollaborationCode1
Learning From Failure: Integrating Negative Examples when Fine-tuning Large Language Models as AgentsCode1
KnowTuning: Knowledge-aware Fine-tuning for Large Language ModelsCode1
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge GraphsCode1
Language Models as Science TutorsCode1
Multi-modal Preference Alignment Remedies Degradation of Visual Instruction Tuning on Language ModelsCode1
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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