SOTAVerified

Visual Entailment

Visual Entailment (VE) - is a task consisting of image-sentence pairs whereby a premise is defined by an image, rather than a natural language sentence as in traditional Textual Entailment tasks. The goal is to predict whether the image semantically entails the text.

Papers

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Showing 41–50 of 56 papers

TitleStatusHype
Playing Lottery Tickets with Vision and Language—0
Pre-training image-language transformers for open-vocabulary tasks—0
Probing Inter-modality: Visual Parsing with Self-Attention for Vision-Language Pre-training—0
Probing Inter-modality: Visual Parsing with Self-Attention for Vision-and-Language Pre-training—0
Few-shot Multimodal Multitask Multilingual Learning—0
Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing—0
How Much Can CLIP Benefit Vision-and-Language Tasks?—0
Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning—0
Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation—0
"Let's not Quote out of Context": Unified Vision-Language Pretraining for Context Assisted Image Captioning—0
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