6 accepted papers
Foundation segmentation models, such as SAM and its video-oriented variant SAM2, have achieved remarkable success in natural image and video segmentation. However, their direct application to echocardiography video is challenged by structural uncertainty arising from severe speckle noise and blurry
Imitation learning (IL) offers a promising pathway for enabling surgical robots to perform autonomous wound repair. However, existing methods often neglect spatial semantics and wound-shape information, leading to poor generalization and low success rates. This paper presents the <bold>S</bold>patia
Large Language Models (LLMs) show great capabilities in a wide range of applications, but serving them efficiently becomes increasingly challenging as requests (prompts) become more complex. Context caching improves serving performance by reusing Key-Value (KV) vectors, the intermediate representati…
Large Language Models (LLMs) have demonstrated strong capabilities across various domains, with recent advancements in challenging reasoning tasks such as mathematics and programming. However, solving reasoning tasks often requires an LLM to generate long sequences, incurring O(N) time and memory co…
We present a method for efficiently exploring highly convoluted environments. The method incorporates two planning stages - an exploration stage for extending the boundary of the map, and a relocation stage for explicitly transiting the robot to different sub-areas in the environment. The exploratio…
Up to this day, precise manipulation still relies on human hands, which benefits from the rich neural sensing in the fingertips. For robotic hands, force perception, recognizing the softness of objects, and detecting slip can significantly improve the grasping and manipulating abilities. However, it