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

Showing 226250 of 10817 papers

TitleStatusHype
Med3DVLM: An Efficient Vision-Language Model for 3D Medical Image AnalysisCode2
MC-LLaVA: Multi-Concept Personalized Vision-Language ModelCode2
LLaVAction: evaluating and training multi-modal large language models for action recognitionCode2
Chain-of-Tools: Utilizing Massive Unseen Tools in the CoT Reasoning of Frozen Language ModelsCode2
Where do Large Vision-Language Models Look at when Answering Questions?Code2
DriveLMM-o1: A Step-by-Step Reasoning Dataset and Large Multimodal Model for Driving Scenario UnderstandingCode2
Teaching LMMs for Image Quality Scoring and InterpretingCode2
A Multimodal Benchmark Dataset and Model for Crop Disease DiagnosisCode2
MedAgentsBench: Benchmarking Thinking Models and Agent Frameworks for Complex Medical ReasoningCode2
Keeping Yourself is Important in Downstream Tuning Multimodal Large Language ModelCode2
AnyAnomaly: Zero-Shot Customizable Video Anomaly Detection with LVLMCode2
SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-CheckingCode2
Streaming Video Question-Answering with In-context Video KV-Cache RetrievalCode2
LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented SearchersCode2
Benchmarking Retrieval-Augmented Generation in Multi-Modal ContextsCode2
Multimodal RewardBench: Holistic Evaluation of Reward Models for Vision Language ModelsCode2
Re-Align: Aligning Vision Language Models via Retrieval-Augmented Direct Preference OptimizationCode2
Talk Structurally, Act Hierarchically: A Collaborative Framework for LLM Multi-Agent SystemsCode2
SVBench: A Benchmark with Temporal Multi-Turn Dialogues for Streaming Video UnderstandingCode2
KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAGCode2
ScoreFlow: Mastering LLM Agent Workflows via Score-based Preference OptimizationCode2
LUCY: Linguistic Understanding and Control Yielding Early Stage of HerCode2
Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement LearningCode2
Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language ModelsCode2
EmbodiedEval: Evaluate Multimodal LLMs as Embodied AgentsCode2
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Benchmark Results

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