3 papers
cs.CV2025
Beyond Human-prompting: Adaptive Prompt Tuning with Semantic Alignment for Anomaly Detection
Pi-Wei Chen, Jerry Chun-Wei Lin, Wei-Han Chen +4
Pre-trained Vision-Language Models (VLMs) have recently shown promise in detecting anomalies. However, previous approaches are fundamentally limited by their reliance on human-desi…
cs.CL2025
Continual Pre-Training is (not) What You Need in Domain Adaption
Pin-Er Chen, Da-Chen Lian, Shu-Kai Hsieh +8
The recent advances in Legal Large Language Models (LLMs) have transformed the landscape of legal research and practice by automating tasks, enhancing research precision, and suppo…
cs.CL2024
NeKo: Cross-Modality Post-Recognition Error Correction with Tasks-Guided Mixture-of-Experts Language Model
Yen-Ting Lin, Zhehuai Chen, Piotr Zelasko +11
Construction of a general-purpose post-recognition error corrector poses a crucial question: how can we most effectively train a model on a large mixture of domain datasets? The an…