3 papers
cs.CV2026
Harnessing Domain Specialists in Multimodal Mixture-of-Experts for Efficient Adaptation
Damiano Marsili, Raphi Kang, Aditya Mehta +2
Mixture-of-Experts (MoE) architectures scale model capacity through sparse computation, routing each token through only a small subset of experts. In this work, we explore whether…
cs.CV2026
Linear Mechanisms for Spatiotemporal Reasoning in Vision Language Models
Raphi Kang, Hongqiao Chen, Georgia Gkioxari +1
Spatio-temporal reasoning is a remarkable capability of Vision Language Models (VLMs), but the underlying mechanisms of such abilities remain largely opaque. We postulate that visu…
cs.LG2025
Is CLIP ideal? No. Can we fix it? Yes!
Raphi Kang, Yue Song, Georgia Gkioxari +1
Contrastive Language-Image Pre-Training (CLIP) is a popular method for learning multimodal latent spaces with well-organized semantics. Despite its wide range of applications, CLIP…