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 151–175 of 10817 papers

TitleStatusHype
Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal ModelsCode3
ONE-PEACE: Exploring One General Representation Model Toward Unlimited ModalitiesCode3
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of ExpertsCode3
CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language ModelsCode3
MLLMs Know Where to Look: Training-free Perception of Small Visual Details with Multimodal LLMsCode3
MDocAgent: A Multi-Modal Multi-Agent Framework for Document UnderstandingCode3
MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video UnderstandingCode3
CRAG -- Comprehensive RAG BenchmarkCode3
Meta-Chunking: Learning Text Segmentation and Semantic Completion via Logical PerceptionCode3
LLaMA-Omni2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech SynthesisCode3
Longformer: The Long-Document TransformerCode3
Champion Solution for the WSDM2023 Toloka VQA ChallengeCode3
Language Models are Few-Shot LearnersCode3
DARWIN 1.5: Large Language Models as Materials Science Adapted LearnersCode3
RAGEval: Scenario Specific RAG Evaluation Dataset Generation FrameworkCode3
Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-ThoughtCode3
LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding Reasoning and PlanningCode3
KVzip: Query-Agnostic KV Cache Compression with Context ReconstructionCode3
Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question ComplexityCode3
CAD-Recode: Reverse Engineering CAD Code from Point CloudsCode3
Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action ModelsCode3
InfoChartQA: A Benchmark for Multimodal Question Answering on Infographic ChartsCode3
L0: Reinforcement Learning to Become General AgentsCode3
Odyssey: Empowering Minecraft Agents with Open-World SkillsCode3
LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive MemoryCode3
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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