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 151200 of 10817 papers

TitleStatusHype
M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language ModelsCode3
PCToolkit: A Unified Plug-and-Play Prompt Compression Toolkit of Large Language ModelsCode3
The Unreasonable Ineffectiveness of the Deeper LayersCode3
Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question ComplexityCode3
AlphaFin: Benchmarking Financial Analysis with Retrieval-Augmented Stock-Chain FrameworkCode3
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextCode3
Vision-Language Models for Medical Report Generation and Visual Question Answering: A ReviewCode3
Towards Building Multilingual Language Model for MedicineCode3
ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language ModelsCode3
PreFLMR: Scaling Up Fine-Grained Late-Interaction Multi-modal RetrieversCode3
Q-Bench+: A Benchmark for Multi-modal Foundation Models on Low-level Vision from Single Images to PairsCode3
A Survey of Large Language Models in Finance (FinLLMs)Code3
CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language ModelsCode3
AutoAct: Automatic Agent Learning from Scratch for QA via Self-PlanningCode3
LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding Reasoning and PlanningCode3
TinyGPT-V: Efficient Multimodal Large Language Model via Small BackbonesCode3
DriveLM: Driving with Graph Visual Question AnsweringCode3
Generative Multimodal Models are In-Context LearnersCode3
FinanceBench: A New Benchmark for Financial Question AnsweringCode3
Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal ModelsCode3
SALMONN: Towards Generic Hearing Abilities for Large Language ModelsCode3
Evaluating Hallucinations in Chinese Large Language ModelsCode3
Generative Data Augmentation using LLMs improves Distributional Robustness in Question AnsweringCode3
Towards CausalGPT: A Multi-Agent Approach for Faithful Knowledge Reasoning via Promoting Causal Consistency in LLMsCode3
3D-LLM: Injecting the 3D World into Large Language ModelsCode3
Emu: Generative Pretraining in MultimodalityCode3
SVIT: Scaling up Visual Instruction TuningCode3
WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human PreferencesCode3
Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language ModelsCode3
Self-QA: Unsupervised Knowledge Guided Language Model AlignmentCode3
ONE-PEACE: Exploring One General Representation Model Toward Unlimited ModalitiesCode3
Visual Causal Scene Refinement for Video Question AnsweringCode3
REPLUG: Retrieval-Augmented Black-Box Language ModelsCode3
ThoughtSource: A central hub for large language model reasoning dataCode3
Champion Solution for the WSDM2023 Toloka VQA ChallengeCode3
TextBox 2.0: A Text Generation Library with Pre-trained Language ModelsCode3
Prompting Is Programming: A Query Language for Large Language ModelsCode3
A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and MultimodalCode3
Scaling Instruction-Finetuned Language ModelsCode3
Vision-Language Pre-training: Basics, Recent Advances, and Future TrendsCode3
Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-ThoughtCode3
Time-series Transformer Generative Adversarial NetworksCode3
All You May Need for VQA are Image CaptionsCode3
ST-MoE: Designing Stable and Transferable Sparse Expert ModelsCode3
Finetuned Language Models Are Zero-Shot LearnersCode3
Language Models are Few-Shot LearnersCode3
Longformer: The Long-Document TransformerCode3
ERNIE 2.0: A Continual Pre-training Framework for Language UnderstandingCode3
Generating Long Sequences with Sparse TransformersCode3
ERNIE: Enhanced Representation through Knowledge IntegrationCode3
Show:102550
← PrevPage 4 of 217Next →

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