IEEE

Personalizing Vision-Language Models With Hybrid Prompts for Zero-Shot Anomaly Detection

Abstract: Zero-shot anomaly detection (ZSAD) aims to develop a foundational model capable of detecting anomalies across arbitrary categories without relying on reference images. However, since ...
IEEE

Bridging Modality Gap with Large Speech and Language Models for End-to-End Speech-to-Text Translation

Abstract: End-to-end speech-to-text translation (E2E ST) has increasingly aroused interest and attention recently, attempting to address the problem of data scarcity and modeling burden. Several ...