3 papers
cs.CL2024
Editing the Mind of Giants: An In-Depth Exploration of Pitfalls of Knowledge Editing in Large Language Models
Cheng-Hsun Hsueh, Paul Kuo-Ming Huang, Tzu-Han Lin +4
Knowledge editing is a rising technique for efficiently updating factual knowledge in large language models (LLMs) with minimal alteration of parameters. However, recent studies ha…
eess.AS2023
Prompting and Adapter Tuning for Self-supervised Encoder-Decoder Speech Model
Kai-Wei Chang, Ming-Hsin Chen, Yun-Ping Lin +5
Prompting and adapter tuning have emerged as efficient alternatives to fine-tuning (FT) methods. However, existing studies on speech prompting focused on classification tasks and f…
cs.CV2023
Score-based Conditional Generation with Fewer Labeled Data by Self-calibrating Classifier Guidance
Paul Kuo-Ming Huang, Si-An Chen, Hsuan-Tien Lin
Score-based generative models (SGMs) are a popular family of deep generative models that achieve leading image generation quality. Early studies extend SGMs to tackle class-conditi…