Robust Prompt Learning For Vision|Language Models With Noisy ...

Robust Prompt Learning For Vision-Language Models With Noisy ...

TL;DR: We propose a robust prompt learning algorithm that utilizes various input prompts to minimize the impact of noisy labels. Abstract:.

Why Is Prompt Tuning for Vision-Language Models Robust to Noisy ...

Abstract:Vision-language models such as CLIP learn a generic text-image embedding from large-scale training data. A vision-language model ...

Why Is Prompt Tuning for Vision-Language Models Robust to Noisy ...

Figure 1: Comparison with transfer learning approaches on two datasets with training labels that have incremental noisy rates. ImageNet Finetuning is finetuning ...

ROBUST PROMPT LEARNING FOR VISION-LANGUAGE MODELS ...

In this paper, our objective is to enhance classification fine-tuning performance by leveraging the zero-shot classification capability under a noisy labeled ...

JoAPR: Cleaning the Lens of Prompt Learning for Vision-Language ...

Our comprehensive experiments confirm that JoAPR substantially enhances the robustness of prompt learning for Vision-Language Models against label noise,.

Why Is Prompt Tuning for Vision-Language Models Robust to Noisy ...

Figure 1: Comparison with transfer learning approaches on two datasets with training labels that have incremental noisy rates. ImageNet Finetuning is finetuning ...

[PDF] Why Is Prompt Tuning for Vision-Language Models Robust to ...

... robustness of prompt learning for Vision-Language Models against label noise. Expand. Add to Library. Alert. 2 Excerpts. Prototypical Contrastive Learning-based ...

Vision-Language Models are Strong Noisy Label Detectors - arXiv

The proposed framework establishes a noisy label detector by learning positive and negative textual prompts for each class. The positive prompt ...

Why Is Prompt Tuning for Vision-Language Models Robust to Noisy ...

Why Is Prompt Tuning for Vision-Language Models Robust to Noisy Labels? 12 views · 3 months ago ...more ...

Cleaning the Lens of Prompt Learning for Vision-Language Models

Leveraging few-shot datasets in prompt learning for Vision-Language Models eliminates the need for manual prompt engineering while highlighting the ...

(PDF) Towards Robust Prompts on Vision-Language Models

We propose robust prompt learning by integrating multiple-scale image features into the prompt, which improves both types of robustness.

Add ICCV 2023 paper: Why Is Prompt Tuning for Vision-Language ...

Paper name: Why Is Prompt Tuning for Vision-Language Models Robust to Noisy Labels? Paper link: https://arxiv.org/abs/2307.11978 Code link: ...

Vision-Language Models are Strong Noisy Label Detectors

The pro- posed framework establishes a noisy label detector by learning positive and negative textual prompts for each class. The positive prompt seeks to ...

Adversarial Prompt Tuning for Vision-Language Models

future robust multimodal learning research. These findings open up new possibilities for enhancing the security of VLMs. Our code is available at https ...

Noisy Exemplars Make Large Language Models More Robust

Recent advances in prompt engineering enable large language models (LLMs) to solve multi- hop logical reasoning problems with impres-.

A Literature Survey about Why Is Prompt Tuning for Vision ... - 博客园

VI.Author's Contribution. We demonstrate that prompt tuning for pre-trained vision-language models (e.g., CLIP) is more robust to noisy labels than traditional ...

nhussein/promptsmooth: Official implementation of the ... - GitHub

Official implementation of the paper "PromptSmooth: Certifying Robustness of Medical Vision-Language Models via Prompt Learning" - nhussein/promptsmooth.

PromptSmooth: Certifying Robustness of Medical Vision-Language ...

tational cost compared to traditional methods that rely on training a separate model for each noise level. Comprehensive experiments based on three Med-VLMs ...

Why Vision Language Models Are Not As Robust As We Might Think?

67 votes, 33 comments. I recently came across this paper where researchers showed that Vision Language Model performance decreases if we ...

Prompt Perturbation Consistency Learning for Robust Language ...

Token-level consistency involves regularizing the model to. 1358. Page 3. remain unaffected by Gaussian noise (Lowell et al.,. 2020) or word ...