3 papers
cs.CV2026
Diagnosing the Sources of Compositional Failure in Vision-Language Models: A Controlled Analysis
Mona Gandhi, Cenk Merih Olcay, Kuan-Chieh Lo +3
Vision-language models (VLMs) often struggle with compositional reasoning tasks, but the reasons for this underperformance remain unclear. A common hypothesis is that models strugg…
cs.IR2026
Multimedia Asset Personalization via Multimodal Embeddings at Netflix
Emma Yanyang Kong, Aditya Deshpande, Bowei Yan +5
Personalized promotional assets, namely artwork images and video preview clips, are critical to content discovery on Netflix. Traditional models for asset selection rely on ID-base…
cs.CV2024
CLoVe: Encoding Compositional Language in Contrastive Vision-Language Models
Santiago Castro, Amir Ziai, Avneesh Saluja +2
Recent years have witnessed a significant increase in the performance of Vision and Language tasks. Foundational Vision-Language Models (VLMs), such as CLIP, have been leveraged in…