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SOTA
Visual Entailment
Visual Entailment On Snli Ve Val
Visual Entailment On Snli Ve Val
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Accuracy
Paper Title
OFA
91.0
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Prompt Tuning
90.04
Prompt Tuning for Generative Multimodal Pretrained Models
CoCa
87.0
CoCa: Contrastive Captioners are Image-Text Foundation Models
SimVLM
86.21
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision
SOHO
85.00
Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning
CLIP-ViL
80.20
How Much Can CLIP Benefit Vision-and-Language Tasks?
VILLA-LARGE
80.18
Large-Scale Adversarial Training for Vision-and-Language Representation Learning
UNITER
78.98
UNITER: UNiversal Image-TExt Representation Learning
EVE-ROI*
70.81
Visual Entailment: A Novel Task for Fine-Grained Image Understanding
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Visual Entailment On Snli Ve Val | SOTA | HyperAI