Advancing Multimodal Large Language Models with Quantization-Aware Scale Learning for Efficient Adaptation
This paper presents the first study to explore the potential of parameter quantization for
multimodal large language models to alleviate the significant resource constraint …
multimodal large language models to alleviate the significant resource constraint …
Foundation Models for Video Understanding: A Survey
Video Foundation Models (ViFMs) aim to learn a general-purpose representation for various
video understanding tasks. Leveraging large-scale datasets and powerful models, ViFMs …
video understanding tasks. Leveraging large-scale datasets and powerful models, ViFMs …
Efficient Ransomware Detection via Portable Executable File Image Analysis By LLaMA-7b
X Li, T Zhu, W Zhang - 2023 - researchsquare.com
This research focuses on developing a novel ransomware detection methodology
leveraging the capabilities of the open source large language model LLaMA-7b and image …
leveraging the capabilities of the open source large language model LLaMA-7b and image …
Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
The rise of deep learning has marked significant progress in fields such as computer vision,
natural language processing, and medical imaging, primarily through the adaptation of pre …
natural language processing, and medical imaging, primarily through the adaptation of pre …
Knowledge Enhancement and Disentanglement Learning for Video Captioning
M Wang, Y Ma, B Cai, D Li, X He… - Available at SSRN …, 2024 - papers.ssrn.com
Video captioning, bridging computer vision and natural language, is crucial for various
knowledge-based systems in the age of video streaming. Recent advancements in video …
knowledge-based systems in the age of video streaming. Recent advancements in video …