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 376–400 of 10817 papers

TitleStatusHype
Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory PredictionCode2
An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLMCode2
OmniVid: A Generative Framework for Universal Video UnderstandingCode2
Visually Guided Generative Text-Layout Pre-training for Document IntelligenceCode2
LLaVA-PruMerge: Adaptive Token Reduction for Efficient Large Multimodal ModelsCode2
Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based RetrieversCode2
VL-ICL Bench: The Devil in the Details of Multimodal In-Context LearningCode2
RAGGED: Towards Informed Design of Retrieval Augmented Generation SystemsCode2
Beyond Text: Frozen Large Language Models in Visual Signal ComprehensionCode2
ERA-CoT: Improving Chain-of-Thought through Entity Relationship AnalysisCode2
KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking TechniquesCode2
Debiasing Multimodal Large Language ModelsCode2
CAT: Enhancing Multimodal Large Language Model to Answer Questions in Dynamic Audio-Visual ScenariosCode2
QAQ: Quality Adaptive Quantization for LLM KV CacheCode2
Are Language Models Puzzle Prodigies? Algorithmic Puzzles Unveil Serious Challenges in Multimodal ReasoningCode2
Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented GenerationCode2
The First Place Solution of WSDM Cup 2024: Leveraging Large Language Models for Conversational Multi-Doc QACode2
Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A SurveyCode2
BlendSQL: A Scalable Dialect for Unifying Hybrid Question Answering in Relational AlgebraCode2
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful SpaceCode2
RetrievalQA: Assessing Adaptive Retrieval-Augmented Generation for Short-form Open-Domain Question AnsweringCode2
Data Science with LLMs and Interpretable ModelsCode2
ActiveRAG: Autonomously Knowledge Assimilation and Accommodation through Retrieval-Augmented AgentsCode2
FanOutQA: A Multi-Hop, Multi-Document Question Answering Benchmark for Large Language ModelsCode2
Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMsCode2
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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