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most citedTemporal Embeddings: Scalable Self-Supervised Temporal Representation Learning from Spatiotemporal Data for Multimodal Computer Vision

1 citations · 1 across the 4 of their papers we have counts for

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cs.CV2025

VLCache: Computing 2% Vision Tokens and Reusing 98% for Vision-Language Inference

Shengling Qin, Hao Yu, Chenxin Wu +10

This paper presents VLCache, a cache reuse framework that exploits both Key-Value (KV) cache and encoder cache from prior multimodal inputs to eliminate costly recomputation when t…

cs.CV2025

MIV: Towards Efficient and Fine-grained Multimodal In-Context Learning via Representation Engineering

Yanshu Li, Yi Cao, Hongyang He +5

Multimodal in-context learning (ICL) equips Large Vision-language Models (LVLMs) with the ability to adapt to new tasks via multiple user-provided demonstrations, without requiring…

cs.CV2024★ 1 cited

Temporal Embeddings: Scalable Self-Supervised Temporal Representation Learning from Spatiotemporal Data for Multimodal Computer Vision

Yi Cao, Swetava Ganguli, Vipul Pandey

There exists a correlation between geospatial activity temporal patterns and type of land use. A novel self-supervised approach is proposed to stratify landscape based on mobility…