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20232026
most citedTowards Optimal Feature-Shaping Methods for Out-of-Distribution Detection

1 citations · 2 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

Negative Token Merging: Image-based Adversarial Feature Guidance

Jaskirat Singh, Lindsey Li, Weijia Shi +7

Text-based adversarial guidance using a negative prompt has emerged as a widely adopted approach to steer diffusion models away from producing undesired concepts. While useful, per…

cs.CV2024

Can We Predict Performance of Large Models across Vision-Language Tasks?

Qinyu Zhao, Ming Xu, Kartik Gupta +3

Evaluating large vision-language models (LVLMs) is very expensive, due to high computational cost and the wide variety of tasks. The good news is that if we already have some obser…

cs.CV2024

Temporally Consistent Unbalanced Optimal Transport for Unsupervised Action Segmentation

Ming Xu, Stephen Gould

We propose a novel approach to the action segmentation task for long, untrimmed videos, based on solving an optimal transport problem. By encoding a temporal consistency prior into…

cs.CV2024

The First to Know: How Token Distributions Reveal Hidden Knowledge in Large Vision-Language Models?

Qinyu Zhao, Ming Xu, Kartik Gupta +3

Large vision-language models (LVLMs), designed to interpret and respond to human instructions, occasionally generate hallucinated or harmful content due to inappropriate instructio…

cs.CV2024★ 1 cited

Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection

Qinyu Zhao, Ming Xu, Kartik Gupta +3

Feature shaping refers to a family of methods that exhibit state-of-the-art performance for out-of-distribution (OOD) detection. These approaches manipulate the feature representat…