Zobrazeno 1 - 10
of 410
pro vyhledávání: '"Liu, Yijiang"'
This study aims to investigate, through neuroscientific methods, the effects of particular architectural elements on pedestrian spatial cognition and experience in the analysis and design of walking street spaces. More precisely, this paper will desc
Externí odkaz:
http://arxiv.org/abs/2409.01027
Mental-Gen: A Brain-Computer Interface-Based Interactive Method for Interior Space Generative Design
Autor:
Liu, Yijiang, Wang, Hui
Interior space design significantly influences residents' daily lives. However, the process often presents high barriers and complex reasoning for users, leading to semantic losses in articulating comprehensive requirements and communicating them to
Externí odkaz:
http://arxiv.org/abs/2409.00962
Large language models (LLMs) excel in language tasks, especially with supervised fine-tuning after pre-training. However, their substantial memory and computational requirements hinder practical applications. Structural pruning, which reduces less si
Externí odkaz:
http://arxiv.org/abs/2408.14721
Autor:
Liu, Yijiang, Zhang, Rongyu, Yang, Huanrui, Keutzer, Kurt, Du, Yuan, Du, Li, Zhang, Shanghang
Large Language Models (LLMs) have demonstrated significant potential in performing multiple tasks in multimedia applications, ranging from content generation to interactive entertainment, and artistic creation. However, the diversity of downstream ta
Externí odkaz:
http://arxiv.org/abs/2404.08985
Autor:
Wang, Guanqun, Liu, Jiaming, Li, Chenxuan, Ma, Junpeng, Zhang, Yuan, Wei, Xinyu, Zhang, Kevin, Chong, Maurice, Zhang, Ray, Liu, Yijiang, Zhang, Shanghang
The burgeoning field of Multimodal Large Language Models (MLLMs) has exhibited remarkable performance in diverse tasks such as captioning, commonsense reasoning, and visual scene understanding. However, the deployment of these large-scale MLLMs on cl
Externí odkaz:
http://arxiv.org/abs/2312.16279
Autor:
Chi, Xiaowei, Zhang, Rongyu, Jiang, Zhengkai, Liu, Yijiang, Wang, Yatian, Qi, Xingqun, Luo, Wenhan, Gao, Peng, Zhang, Shanghang, Liu, Qifeng, Guo, Yike
While current LLM chatbots like GPT-4V bridge the gap between human instructions and visual representations to enable text-image generations, they still lack efficient alignment methods for high-fidelity performance on multiple downstream tasks. In t
Externí odkaz:
http://arxiv.org/abs/2311.17963
Autor:
Li, Xiuyu, Liu, Yijiang, Lian, Long, Yang, Huanrui, Dong, Zhen, Kang, Daniel, Zhang, Shanghang, Keutzer, Kurt
Diffusion models have achieved great success in image synthesis through iterative noise estimation using deep neural networks. However, the slow inference, high memory consumption, and computation intensity of the noise estimation model hinder the ef
Externí odkaz:
http://arxiv.org/abs/2302.04304
The complicated architecture and high training cost of vision transformers urge the exploration of post-training quantization. However, the heavy-tailed distribution of vision transformer activations hinders the effectiveness of previous post-trainin
Externí odkaz:
http://arxiv.org/abs/2211.16056
Autor:
Li, Bobo, Fei, Hao, Li, Fei, Wu, Yuhan, Zhang, Jinsong, Wu, Shengqiong, Li, Jingye, Liu, Yijiang, Liao, Lizi, Chua, Tat-Seng, Ji, Donghong
The rapid development of aspect-based sentiment analysis (ABSA) within recent decades shows great potential for real-world society. The current ABSA works, however, are mostly limited to the scenario of a single text piece, leaving the study in dialo
Externí odkaz:
http://arxiv.org/abs/2211.05705
Publikováno v:
In Construction and Building Materials 25 October 2024 449