Jun 2, 2023 · We study the use of pseudolabels, i.e., heuristic labels for unlabeled data, to enhance CLIP via prompt tuning. Conventional pseudolabeling ...

This paper investigates how the use of out-of-the-box pseudolabels assigned by CLIP can contribute to improving CLIP's own performance. To this end, we conduct ...

Dec 10, 2023 · We study the use of pseudolabels, ie, heuristic labels for unlabeled data, to enhance CLIP via prompt tuning.

Mar 8, 2024 · We present empirical evidence showcasing the effectiveness of iterative prompt-training strategies that leverage CLIP-based pseudolabels, ...

Jun 2, 2023 · We find that (1) unexplored prompt tuning strategies that iteratively refine pseudolabels consistently improve CLIP accuracy, by 19.5 points in ...

A paper review on “Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning”. Post by: Naamii; January 23, 2024; No Comment.

This research paper explores how to improve a powerful AI model called CLIP, which understands both images and text. The authors find that using ...

Enhancing clip with clip: Exploring pseudolabeling for limited-label prompt tuning. C Menghini, A Delworth, S Bach. Advances in Neural Information Processing ...

Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning · Cristina Menghini, Andrew Delworth, Stephen Bach. Published: 21 Sept 2023 ...

In this section, we provide a detailed formulation of un- supervised federated learning for classification tasks with. CLIP and introduce our proposed method.