3 papers
cs.DC2025
Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges
Senyao Li, Haozhao Wang, Wenchao Xu +6
As large language models (LLMs) evolve, deploying them solely in the cloud or compressing them for edge devices has become inadequate due to concerns about latency, privacy, cost,…
cs.CV2025
Expanding Zero-Shot Object Counting with Rich Prompts
Huilin Zhu, Senyao Li, Jingling Yuan +5
Expanding pre-trained zero-shot counting models to handle unseen categories requires more than simply adding new prompts, as this approach does not achieve the necessary alignment…
cs.CV2025
FocalCount: Towards Class-Count Imbalance in Class-Agnostic Counting
Huilin Zhu, Jingling Yuan, Zhengwei Yang +3
In class-agnostic object counting, the goal is to estimate the total number of object instances in an image without distinguishing between specific categories. Existing methods oft…