3 papers
cs.CV2026
Domain-Invariant Prompt Learning for Vision-Language Models
Arsham Gholamzadeh Khoee, Yinan Yu, Robert Feldt
Large pre-trained vision-language models like CLIP have transformed computer vision by aligning images and text in a shared feature space, enabling robust zero-shot transfer via pr…
cs.SE2026
GateLens: A Reasoning-Enhanced LLM Agent for Automotive Software Release Analytics
Arsham Gholamzadeh Khoee, Shuai Wang, Robert Feldt +2
Ensuring reliable data-driven decisions is crucial in domains where analytical accuracy directly impacts safety, compliance, or operational outcomes. Decision support in such domai…
cs.LG2026
Latent Domain Prompt Learning for Vision-Language Models
Zhixing Li, Arsham Gholamzadeh Khoee, Yinan Yu
The objective of domain generalization (DG) is to enable models to be robust against domain shift. DG is crucial for deploying vision-language models (VLMs) in real-world applicati…