Zobrazeno 1 - 10
of 51 146
pro vyhledávání: '"AN, Jiayi"'
Autor:
Zhang, Jiayi, Sun, Chenxin, Gu, Yue, Zhang, Qingyu, Lin, Jiayi, Du, Xiaojiang, Qian, Chenxiong
The gaming industry has experienced substantial growth, but cheating in online games poses a significant threat to the integrity of the gaming experience. Cheating, particularly in first-person shooter (FPS) games, can lead to substantial losses for
Externí odkaz:
http://arxiv.org/abs/2409.14830
Multi-modal entity alignment (MMEA) is essential for enhancing knowledge graphs and improving information retrieval and question-answering systems. Existing methods often focus on integrating modalities through their complementarity but overlook the
Externí odkaz:
http://arxiv.org/abs/2410.14584
Autor:
Zhang, Chenyang, Lin, Jiayi, Tong, Haibo, Hou, Bingxuan, Zhang, Dongyu, Li, Jialin, Wang, Junli
Large language models (LLMs) show remarkable abilities with instruction tuning. However, they fail to achieve ideal tasks when lacking high-quality instruction tuning data on target tasks. Multi-Aspect Controllable Text Generation (MCTG) is a represe
Externí odkaz:
http://arxiv.org/abs/2410.14144
Despite the significant progress in multimodal large language models (MLLMs), their high computational cost remains a barrier to real-world deployment. Inspired by the mixture of depths (MoDs) in natural language processing, we aim to address this li
Externí odkaz:
http://arxiv.org/abs/2410.13859
Entity alignment (EA) refers to the task of linking entities in different knowledge graphs (KGs). Existing EA methods rely heavily on structural isomorphism. However, in real-world KGs, aligned entities usually have non-isomorphic neighborhood struct
Externí odkaz:
http://arxiv.org/abs/2410.13409
Autor:
Sun, Hao, Wu, Jiayi, Cai, Hengyi, Wei, Xiaochi, Feng, Yue, Wang, Bo, Wang, Shuaiqiang, Zhang, Yan, Yin, Dawei
Recent advancements in large language models (LLMs) have been remarkable. Users face a choice between using cloud-based LLMs for generation quality and deploying local-based LLMs for lower computational cost. The former option is typically costly and
Externí odkaz:
http://arxiv.org/abs/2410.13181
Autor:
Chen, Xiangping, Hu, Xing, Huang, Yuan, Jiang, He, Ji, Weixing, Jiang, Yanjie, Jiang, Yanyan, Liu, Bo, Liu, Hui, Li, Xiaochen, Lian, Xiaoli, Meng, Guozhu, Peng, Xin, Sun, Hailong, Shi, Lin, Wang, Bo, Wang, Chong, Wang, Jiayi, Wang, Tiantian, Xuan, Jifeng, Xia, Xin, Yang, Yibiao, Yang, Yixin, Zhang, Li, Zhou, Yuming, Zhang, Lu
Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineer
Externí odkaz:
http://arxiv.org/abs/2410.13110
Image fusion is famous as an alternative solution to generate one high-quality image from multiple images in addition to image restoration from a single degraded image. The essence of image fusion is to integrate complementary information from source
Externí odkaz:
http://arxiv.org/abs/2410.12274
Autor:
Liao, Jiayi, He, Xiangnan, Xie, Ruobing, Wu, Jiancan, Yuan, Yancheng, Sun, Xingwu, Kang, Zhanhui, Wang, Xiang
Recently, there has been a growing interest in leveraging Large Language Models (LLMs) for recommendation systems, which usually adapt a pre-trained LLM to the recommendation scenario through supervised fine-tuning (SFT). However, both the pre-traini
Externí odkaz:
http://arxiv.org/abs/2410.12519
Visual-textual correlations in the attention maps derived from text-to-image diffusion models are proven beneficial to dense visual prediction tasks, e.g., semantic segmentation. However, a significant challenge arises due to the input distributional
Externí odkaz:
http://arxiv.org/abs/2410.11473