2 papers
cs.CL2024
Layer-wise Importance Matters: Less Memory for Better Performance in Parameter-efficient Fine-tuning of Large Language Models
Kai Yao, Penglei Gao, Lichun Li +4
Parameter-Efficient Fine-Tuning (PEFT) methods have gained significant popularity for adapting pre-trained Large Language Models (LLMs) to downstream tasks, primarily due to their…
cs.CV2024
OPa-Ma: Text Guided Mamba for 360-degree Image Out-painting
Penglei Gao, Kai Yao, Tiandi Ye +3
In this paper, we tackle the recently popular topic of generating 360-degree images given the conventional narrow field of view (NFoV) images that could be taken from a single came…