Zobrazeno 1 - 10
of 24 257
pro vyhledávání: '"An, Jiancheng"'
Autor:
Zhou, Donghao, Huang, Jiancheng, Bai, Jinbin, Wang, Jiaze, Chen, Hao, Chen, Guangyong, Hu, Xiaowei, Heng, Pheng-Ann
Recent advancements in text-to-image (T2I) diffusion models have enabled the creation of high-quality images from text prompts, but they still struggle to generate images with precise control over specific visual concepts. Existing approaches can rep
Externí odkaz:
http://arxiv.org/abs/2410.13370
Autor:
Zhang, Weiyi, Yang, Jiancheng, Chen, Ruoyu, Huang, Siyu, Xu, Pusheng, Chen, Xiaolan, Lu, Shanfu, Cao, Hongyu, He, Mingguang, Shi, Danli
Fundus fluorescein angiography (FFA) is crucial for diagnosing and monitoring retinal vascular issues but is limited by its invasive nature and restricted accessibility compared to color fundus (CF) imaging. Existing methods that convert CF images to
Externí odkaz:
http://arxiv.org/abs/2410.13242
PANACEA: Towards Influence-driven Profiling of Drug Target Combinations in Cancer Signaling Networks
Data profiling has garnered increasing attention within the data science community, primarily focusing on structured data. In this paper, we introduce a novel framework called panacea, designed to profile known cancer target combinations in cancer ty
Externí odkaz:
http://arxiv.org/abs/2410.11458
Autor:
Zhan, Yifan, Zhu, Qingtian, Niu, Muyao, Ma, Mingze, Zhao, Jiancheng, Zhong, Zhihang, Sun, Xiao, Qiao, Yu, Zheng, Yinqiang
In this paper, we highlight a critical yet often overlooked factor in most 3D human tasks, namely modeling humans with complex garments. It is known that the parameterized formulation of SMPL is able to fit human skin; while complex garments, e.g., h
Externí odkaz:
http://arxiv.org/abs/2410.08082
In this work, we address the problem of large language model (LLM) unlearning, aiming to remove unwanted data influences and associated model capabilities (e.g., copyrighted data or harmful content generation) while preserving essential model utiliti
Externí odkaz:
http://arxiv.org/abs/2410.07163
Autor:
Yu, Yijiong, Xiufa, Ma, Jianwei, Fang, Xu, Zhi, Guangyao, Su, Jiancheng, Wang, Huang, Yongfeng, Qi, Zhixiao, Wang, Wei, Liu, Weifeng, Chen, Ran, Pei, Ji
Long-context language models (LCLM), characterized by their extensive context window, is becoming increasingly popular. Meanwhile, many long-context benchmarks present challenging tasks that even the most advanced LCLMs struggle to complete. However,
Externí odkaz:
http://arxiv.org/abs/2410.04422
Autor:
Dong, Wenquan, Zhu, Songyan, Xu, Jian, Ryan, Casey M., Chen, Man, Zeng, Jingya, Yu, Hao, Cao, Congfeng, Shi, Jiancheng
Gross Primary Productivity (GPP), the amount of carbon plants fixed by photosynthesis, is pivotal for understanding the global carbon cycle and ecosystem functioning. Process-based models built on the knowledge of ecological processes are susceptible
Externí odkaz:
http://arxiv.org/abs/2410.03951
Cell-free (CF) massive multiple-input multiple-output (mMIMO) systems are emerging as promising alternatives to cellular networks, especially in ultra-dense environments. However, further capacity enhancement requires the deployment of more access po
Externí odkaz:
http://arxiv.org/abs/2409.12870
In this paper, we explore the integration of low-power, low-cost stacked intelligent metasurfaces (SIM) into cell-free (CF) massive multiple-input multiple-output (mMIMO) systems to enhance access point (AP) capabilities and address high power consum
Externí odkaz:
http://arxiv.org/abs/2409.12851
Autor:
Shi, Danli, Zhang, Weiyi, Yang, Jiancheng, Huang, Siyu, Chen, Xiaolan, Yusufu, Mayinuer, Jin, Kai, Lin, Shan, Liu, Shunming, Zhang, Qing, He, Mingguang
Early detection of eye diseases like glaucoma, macular degeneration, and diabetic retinopathy is crucial for preventing vision loss. While artificial intelligence (AI) foundation models hold significant promise for addressing these challenges, existi
Externí odkaz:
http://arxiv.org/abs/2409.06644