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Autor:
Ma, Yiyang, Liu, Xingchao, Chen, Xiaokang, Liu, Wen, Wu, Chengyue, Wu, Zhiyu, Pan, Zizheng, Xie, Zhenda, Zhang, Haowei, yu, Xingkai, Zhao, Liang, Wang, Yisong, Liu, Jiaying, Ruan, Chong
We present JanusFlow, a powerful framework that unifies image understanding and generation in a single model. JanusFlow introduces a minimalist architecture that integrates autoregressive language models with rectified flow, a state-of-the-art method
Externí odkaz:
http://arxiv.org/abs/2411.07975
Thermal broadening of the quasi-particle peak in the spectral function is an important physical feature in many statistical systems, but difficult to calculate. Within the projective truncation approximation (PTA) of Green's function equation of moti
Externí odkaz:
http://arxiv.org/abs/2411.06384
This paper aims to design a unified Computer-Aided Design (CAD) generation system that can easily generate CAD models based on the user's inputs in the form of textual description, images, point clouds, or even a combination of them. Towards this goa
Externí odkaz:
http://arxiv.org/abs/2411.04954
Autor:
Wu, Chengyue, Chen, Xiaokang, Wu, Zhiyu, Ma, Yiyang, Liu, Xingchao, Pan, Zizheng, Liu, Wen, Xie, Zhenda, Yu, Xingkai, Ruan, Chong, Luo, Ping
In this paper, we introduce Janus, an autoregressive framework that unifies multimodal understanding and generation. Prior research often relies on a single visual encoder for both tasks, such as Chameleon. However, due to the differing levels of inf
Externí odkaz:
http://arxiv.org/abs/2410.13848
Autor:
Gao, Yang, Zhai, Huanchen, Gray, Johnnie, Peng, Ruojing, Park, Gunhee, Liu, Wen-Yuan, Kjønstad, Eirik F., Chan, Garnet Kin-Lic
We describe our implementation of fermionic tensor network contraction on arbitrary lattices within both a globally ordered and locally ordered formalism. We provide a pedagogical description of these two conventions as implemented for the quimb libr
Externí odkaz:
http://arxiv.org/abs/2410.02215
Autor:
Zou, Chen, Liu, Wen, Chen, Shiyuan, Li, Songda, Yang, Fangwen, Yu, Linjiang, Zeng, Chaobin, Zhang, Yue-Yu, Hu, Xiaojuan, Han, Zhong-Kang, Jiang, Ying, Yuan, Wentao, Yang, Hangsheng, Wang, Yong
Understanding the dispersion process of supported catalysts is crucial for synthesizing atomic-level dispersed catalysts and precisely manipulating their chemical state. However, the underlying dispersion mechanism remains elusive due to the lack of
Externí odkaz:
http://arxiv.org/abs/2409.14041
Employing the renormalization group approach, we carefully investigate the critical behavior of two-dimensional tilted semi-Dirac semimetals induced by the fermion-fermion interactions in the low-energy regime. After incorporating all one-loop correc
Externí odkaz:
http://arxiv.org/abs/2409.07126
With the advancement of large-scale language modeling techniques, large multimodal models combining visual encoders with large language models have demonstrated exceptional performance in various visual tasks. Most of the current large-scale multimod
Externí odkaz:
http://arxiv.org/abs/2409.01179
Autor:
Deng, Zhaoli, Liu, Wen, Wang, Fanyi, Zhang, Junkang, Chen, Fan, Zhang, Meng, Zhang, Wendong, Mi, Zhenpeng
Portrait Fidelity Generation is a prominent research area in generative models, with a primary focus on enhancing both controllability and fidelity. Current methods face challenges in generating high-fidelity portrait results when faces occupy a smal
Externí odkaz:
http://arxiv.org/abs/2408.09248