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Visual Entailment On Snli Ve Val

评估指标

Accuracy

评测结果

各个模型在此基准测试上的表现结果

模型名称
Accuracy
Paper TitleRepository
CLIP-ViL80.20How Much Can CLIP Benefit Vision-and-Language Tasks?
EVE-ROI*70.81Visual Entailment: A Novel Task for Fine-Grained Image Understanding
OFA91.0OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
SimVLM86.21SimVLM: Simple Visual Language Model Pretraining with Weak Supervision
UNITER78.98UNITER: UNiversal Image-TExt Representation Learning
Prompt Tuning90.04Prompt Tuning for Generative Multimodal Pretrained Models
VILLA-LARGE80.18Large-Scale Adversarial Training for Vision-and-Language Representation Learning
CoCa87.0CoCa: Contrastive Captioners are Image-Text Foundation Models
SOHO85.00Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning
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