Zobrazeno 1 - 10
of 17 360
pro vyhledávání: '"CHEN, Qing"'
Although the superradiant phase transition (SRPT) is prohibited in the paradigmatic quantum Rabi model due to the no-go theorem caused by the $\mathbf{A}$-square term, we demonstrate two distinct types of SRPTs emerging from the normal phase in the a
Externí odkaz:
http://arxiv.org/abs/2412.08305
The rapid advancements in Large Language Models (LLMs) have significantly expanded their applications, ranging from multilingual support to domain-specific tasks and multimodal integration. In this paper, we present OmniEvalKit, a novel benchmarking
Externí odkaz:
http://arxiv.org/abs/2412.06693
Autor:
Chang, Tianyu, Wei, Xiaohao Chen. Zhichao, Zhang, Xuanpu, Chen, Qing-Guo, Luo, Weihua, Yang, Xun
Video Virtual Try-on aims to fluently transfer the garment image to a semantically aligned try-on area in the source person video. Previous methods leveraged the inpainting mask to remove the original garment in the source video, thus achieving accur
Externí odkaz:
http://arxiv.org/abs/2412.03021
The $\mathcal{PT}$ symmetric semiclassical Rabi model elucidates the fundamental interaction between a two-level atom and a classical field, exploring novel phenomena within open systems through the inclusion of non-Hermitian terms. We propose a sing
Externí odkaz:
http://arxiv.org/abs/2412.02918
Autor:
Bai, Jinbin, Ye, Tian, Chow, Wei, Song, Enxin, Chen, Qing-Guo, Li, Xiangtai, Dong, Zhen, Zhu, Lei, Yan, Shuicheng
We present Meissonic, which elevates non-autoregressive masked image modeling (MIM) text-to-image to a level comparable with state-of-the-art diffusion models like SDXL. By incorporating a comprehensive suite of architectural innovations, advanced po
Externí odkaz:
http://arxiv.org/abs/2410.08261
Autor:
Zhu, Li-Fang, Koermann, Fritz, Chen, Qing, Selleby, Malin, Neugebauer, Joerg, Grabowski, and Blazej
Melting properties are critical for designing novel materials, especially for discovering high-performance, high-melting refractory materials. Experimental measurements of these properties are extremely challenging due to their high melting temperatu
Externí odkaz:
http://arxiv.org/abs/2408.08654
Autor:
Chen, Sijia, Wang, Yibo, Wu, Yi-Feng, Chen, Qing-Guo, Xu, Zhao, Luo, Weihua, Zhang, Kaifu, Zhang, Lijun
Tool-augmented large language models (LLMs) leverage tools, often in the form of APIs, to enhance their reasoning capabilities on complex tasks, thus taking on the role of intelligent agents interacting with the real world. The recently introduced To
Externí odkaz:
http://arxiv.org/abs/2406.07115
Autor:
Zhang, Yi-Kai, Lu, Shiyin, Li, Yang, Ma, Yanqing, Chen, Qing-Guo, Xu, Zhao, Luo, Weihua, Zhang, Kaifu, Zhan, De-Chuan, Ye, Han-Jia
Multimodal large language models (MLLMs), initiated with a trained LLM, first align images with text and then fine-tune on multimodal mixed inputs. However, the MLLM catastrophically forgets the text-only instructions, which do not include images and
Externí odkaz:
http://arxiv.org/abs/2406.03496
Autor:
Sun, Hai-Long, Zhou, Da-Wei, Li, Yang, Lu, Shiyin, Yi, Chao, Chen, Qing-Guo, Xu, Zhao, Luo, Weihua, Zhang, Kaifu, Zhan, De-Chuan, Ye, Han-Jia
The rapid development of Multimodal Large Language Models (MLLMs) like GPT-4V has marked a significant step towards artificial general intelligence. Existing methods mainly focus on aligning vision encoders with LLMs through supervised fine-tuning (S
Externí odkaz:
http://arxiv.org/abs/2406.02539
Current Multimodal Large Language Models (MLLMs) typically integrate a pre-trained LLM with another pre-trained vision transformer through a connector, such as an MLP, endowing the LLM with visual capabilities. However, the misalignment between two e
Externí odkaz:
http://arxiv.org/abs/2405.20797