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pro vyhledávání: '"Ji, Bin"'
Autor:
Ji, Bin
Many literatures have been published recently regarding the recovery of REEs from coal-related materials, such as coal waste, acid mine drainage, and coal combustion ash. The recovery of REEs from coal waste has been investigated by the author in rec
Externí odkaz:
http://hdl.handle.net/10919/113161
Autor:
Li, Xiaopeng, Wang, Shangwen, Li, Shasha, Ma, Jun, Yu, Jie, Liu, Xiaodong, Wang, Jing, Ji, Bin, Zhang, Weimin
Large Language Models for Code (LLMs4Code) have been found to exhibit outstanding performance in the software engineering domain, especially the remarkable performance in coding tasks. However, even the most advanced LLMs4Code can inevitably contain
Externí odkaz:
http://arxiv.org/abs/2411.06638
Autor:
Li, Xiaopeng, Wang, Shangwen, Song, Shezheng, Ji, Bin, Liu, Huijun, Li, Shasha, Ma, Jun, Yu, Jie
Knowledge editing has emerged as an efficient technology for updating the knowledge of large language models (LLMs), attracting increasing attention in recent years. However, there is a lack of effective measures to prevent the malicious misuse of th
Externí odkaz:
http://arxiv.org/abs/2409.19663
Code Pre-trained Models (CodePTMs) based vulnerability detection have achieved promising results over recent years. However, these models struggle to generalize as they typically learn superficial mapping from source code to labels instead of underst
Externí odkaz:
http://arxiv.org/abs/2406.03718
Autor:
Song, Shezheng, Li, Shasha, Zhao, Shan, Li, Xiaopeng, Wang, Chengyu, Yu, Jie, Ma, Jun, Yan, Tianwei, Ji, Bin, Mao, Xiaoguang
Multimodal entity linking (MEL) aims to utilize multimodal information (usually textual and visual information) to link ambiguous mentions to unambiguous entities in knowledge base. Current methods facing main issues: (1)treating the entire image as
Externí odkaz:
http://arxiv.org/abs/2404.04818
Achieving disentangled control over multiple facial motions and accommodating diverse input modalities greatly enhances the application and entertainment of the talking head generation. This necessitates a deep exploration of the decoupling space for
Externí odkaz:
http://arxiv.org/abs/2404.01647
Generating emotional talking faces is a practical yet challenging endeavor. To create a lifelike avatar, we draw upon two critical insights from a human perspective: 1) The connection between audio and the non-deterministic facial dynamics, encompass
Externí odkaz:
http://arxiv.org/abs/2403.06375
Although automatically animating audio-driven talking heads has recently received growing interest, previous efforts have mainly concentrated on achieving lip synchronization with the audio, neglecting two crucial elements for generating expressive v
Externí odkaz:
http://arxiv.org/abs/2403.06365
Generating stylized talking head with diverse head motions is crucial for achieving natural-looking videos but still remains challenging. Previous works either adopt a regressive method to capture the speaking style, resulting in a coarse style that
Externí odkaz:
http://arxiv.org/abs/2403.06363
Amidst the recent strides in evaluating Large Language Models for Code (Code LLMs), existing benchmarks have mainly focused on the functional correctness of generated code, neglecting the importance of their computational efficiency. To fill the gap,
Externí odkaz:
http://arxiv.org/abs/2402.07844