Zobrazeno 1 - 10
of 10 160
pro vyhledávání: '"An, Seunghyun"'
Autor:
Lee, Seunghyun, Gu, Yuqi
In the era of generative AI, deep generative models (DGMs) with latent representations have gained tremendous popularity. Despite their impressive empirical performance, the statistical properties of these models remain underexplored. DGMs are often
Externí odkaz:
http://arxiv.org/abs/2501.01414
Autor:
Choi, Sungik, Park, Sungwoo, Lee, Jaehoon, Kim, Seunghyun, Choi, Stanley Jungkyu, Lee, Moontae
Dramatic advances in the quality of the latent diffusion models (LDMs) also led to the malicious use of AI-generated images. While current AI-generated image detection methods assume the availability of real/AI-generated images for training, this is
Externí odkaz:
http://arxiv.org/abs/2412.20704
Multimodal large language models (MLLMs) excel at generating highly detailed captions but often produce hallucinations. Our analysis reveals that existing hallucination detection methods struggle with detailed captions. We attribute this to the incre
Externí odkaz:
http://arxiv.org/abs/2412.15484
Autor:
Cha, Junuk, Ren, Mengwei, Singh, Krishna Kumar, Zhang, He, Hold-Geoffroy, Yannick, Yoon, Seunghyun, Jung, HyunJoon, Yoon, Jae Shin, Baek, Seungryul
We present a lighting-aware image editing pipeline that, given a portrait image and a text prompt, performs single image relighting. Our model modifies the lighting and color of both the foreground and background to align with the provided text descr
Externí odkaz:
http://arxiv.org/abs/2412.13734
Autor:
Nguyen, Dang, Chen, Jian, Wang, Yu, Wu, Gang, Park, Namyong, Hu, Zhengmian, Lyu, Hanjia, Wu, Junda, Aponte, Ryan, Xia, Yu, Li, Xintong, Shi, Jing, Chen, Hongjie, Lai, Viet Dac, Xie, Zhouhang, Kim, Sungchul, Zhang, Ruiyi, Yu, Tong, Tanjim, Mehrab, Ahmed, Nesreen K., Mathur, Puneet, Yoon, Seunghyun, Yao, Lina, Kveton, Branislav, Nguyen, Thien Huu, Bui, Trung, Zhou, Tianyi, Rossi, Ryan A., Dernoncourt, Franck
Graphical User Interface (GUI) agents, powered by Large Foundation Models, have emerged as a transformative approach to automating human-computer interaction. These agents autonomously interact with digital systems or software applications via GUIs,
Externí odkaz:
http://arxiv.org/abs/2412.13501
Inductive reasoning - the process of inferring general rules from a small number of observations - is a fundamental aspect of human intelligence. Recent works suggest that large language models (LLMs) can engage in inductive reasoning by sampling mul
Externí odkaz:
http://arxiv.org/abs/2412.13422
For embodied reinforcement learning (RL) agents interacting with the environment, it is desirable to have rapid policy adaptation to unseen visual observations, but achieving zero-shot adaptation capability is considered as a challenging problem in t
Externí odkaz:
http://arxiv.org/abs/2412.11484
Autor:
Ogata, Shiki, Kitagawa, Shunsaku, Kinjo, Katsuki, Ishida, Kenji, Brando, Manuel, Hassinger, Elena, Geibel, Christoph, Khim, Seunghyun
Publikováno v:
Phys. Rev. B 110, 214509 (2024)
CeRh$_2$As$_2$ shows the superconducting (SC) multiphase under the $c$-axis magnetic field, which is considered to originate from local inversion symmetry breaking at the Ce site. We reported that the antiferromagnetic (AFM) order is inside the SC ph
Externí odkaz:
http://arxiv.org/abs/2412.10148
This paper addresses a data detection problem for multiple-input multiple-output (MIMO) communication systems with hardware impairments. To facilitate maximum likelihood (ML) data detection without knowledge of nonlinear and unknown hardware impairme
Externí odkaz:
http://arxiv.org/abs/2412.06049
The generalized persistence diagram (GPD) is a natural extension of the classical persistence barcode to the setting of multi-parameter persistence and beyond. The GPD is defined as an integer-valued function whose domain is the set of intervals in t
Externí odkaz:
http://arxiv.org/abs/2412.05900