5 accepted papers
Precise event spotting (PES) aims to recognize fine-grained events at exact moments and has become a key component of sports analytics. This task is particularly challenging due to rapid succession, motion blur, and subtle visual differences. Consequently, most existing methods rely on domain-specif
Analyzing Fast, Frequent, and Fine-grained ($F^3$) events presents a significant challenge in video analytics and multi-modal LLMs. Current methods struggle to identify events that satisfy all the $F^3$ criteria with high accuracy due to challenges such as motion blur and subtle visual discrepancies…
Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing broad aspects of daily life. Despite their remarkable performance, LLMs exhibit a fundamental limitation: hallucination—the tendency to produce misleading outputs that appear plausible. This inherent…
Microrobots driven by magnetic fields hold significant promise in medical applications, particularly in drug delivery–a key area in the biomedical field. Traditional approaches primarily rely on global magnetic fields to control single microrobots, which makes it challenging to independently control
The application of microrobots in the biomedical field has attracted great interest, among which drug transportation is one of the application scenarios. Traditional studies used the global magnetic field to control single microrobot, therefore it is impossible to control multiple microrobots. To ad…