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 31–40 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
Unsupervised Vision-and-Language Pre-training via Retrieval-based Multi-Granular Alignment—0
AlignVE: Visual Entailment Recognition Based on Alignment Relations—0
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