IEEE

Variational Adapter: Improving CLIP in Data-Imbalanced Scenarios

Abstract: In this paper, we propose the Prompt-based Variational Adapter (PVA), a novel approach designed to fine-tune the pre-trained Vision-Language Models (VLMs) in data-imbalanced scenarios.
Australian Broadcasting Corporation

In Data Dreams: Art and AI at the MCA, 10 artists explore the impact of AI on contemporary life

What does truth look like in the AI age? That's one of the pressing questions asked by British Tamil artist Christopher Kulendran Thomas in his video installation The Finesse, one of the works ...
W magazine

Matthieu Blazy’s First Chanel Métiers d’Art Collection Takes On New York Style

It’s a new era at Chanel, and it’s big on personality and characters. On a dark and stormy December evening, the brand’s 2026 Métiers d’Art runway show took place on an abandoned subway platform in ...
The New York Times

Inside the Museum-Style Home of Michael Ovitz, an A-List Collector

He is best known as a former Hollywood power broker, but Ovitz has filled his Beverly Hills home with a collection that shows how serious he is about art. Michael Ovitz and Tamara Mellon in front of ...
IEEE

OW-CLIP: Data-Efficient Visual Supervision for Open-World Object Detection via Human-AI Collaboration

Open-world object detection (OWOD) extends traditional object detection to identifying both known and unknown object, necessitating continuous model adaptation as new annotations emerge. Current ...