3 papers
cs.CV2026
S2FT: Parameter-Efficient Fine-Tuning in Sparse Spectrum Domain
Baoquan Zhang, Zhehao Yu, Lisai Zhang +5
Parameter Efficient Fine-Tuning (PEFT) is a key technique for adapting a large pretrained model to downstream tasks by fine-tuning only a small number of parameters. Recent methods…
cs.LG2026
From Tokenizer Bias to Backbone Capability: A Controlled Study of LLMs for Time Series Forecasting
Xinyu Zhang, Shanshan Feng, Xutao Li +3
Using pre-trained large language models (LLMs) as a backbone for time series prediction has recently attracted growing research interest. Existing approaches typically split time s…
cs.CV2024
AsyncDSB: Schedule-Asynchronous Diffusion Schrödinger Bridge for Image Inpainting
Zihao Han, Baoquan Zhang, Lisai Zhang +6
Image inpainting is an important image generation task, which aims to restore corrupted image from partial visible area. Recently, diffusion Schrödinger bridge methods effectively…