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Found 8 papers, 3 papers with code
KAFA: Rethinking Image Ad Understanding with Knowledge-Augmented Feature Adaptation of Vision-Language Models
Image ad understanding is a crucial task with wide real-world applications.
MetaCLUE: Towards Comprehensive Visual Metaphors Research
Towards this goal, we introduce MetaCLUE, a set of vision tasks on visual metaphor.
Question Generation for Evaluating Cross-Dataset Shifts in Multi-modal Grounding
Visual question answering (VQA) is the multi-modal task of answering natural language questions about an input image.
CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models
More concretely, our CX-ToM framework generates sequence of explanations in a dialog by mediating the differences between the minds of machine and human user.
Words aren't enough, their order matters: On the Robustness of Grounding Visual Referring Expressions
To measure the true progress of existing models, we split the test set into two sets, one which requires reasoning on linguistic structure and the other which doesn't.
X-ToM: Explaining with Theory-of-Mind for Gaining Justified Human Trust
We present a new explainable AI (XAI) framework aimed at increasing justified human trust and reliance in the AI machine through explanations.
Action Recognition
Explainable Artificial Intelligence (XAI)
+2
Natural Language Interaction with Explainable AI Models
This paper presents an explainable AI (XAI) system that provides explanations for its predictions.
Discourse Parsing in Videos: A Multi-modal Appraoch
We propose the task of Visual Discourse Parsing, which requires understanding discourse relations among scenes in a video.
