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pro vyhledávání: '"Kim Jaemin"'
Diffusion models have achieved impressive results in generative tasks like text-to-image (T2I) and text-to-video (T2V) synthesis. However, achieving accurate text alignment in T2V generation remains challenging due to the complex temporal dependency
Externí odkaz:
http://arxiv.org/abs/2411.17041
While text-to-video diffusion models have made significant strides, many still face challenges in generating videos with temporal consistency. Within diffusion frameworks, guidance techniques have proven effective in enhancing output quality during i
Externí odkaz:
http://arxiv.org/abs/2411.15540
Gradient-based methods are a prototypical family of explainability techniques, especially for image-based models. Nonetheless, they have several shortcomings in that they (1) require white-box access to models, (2) are vulnerable to adversarial attac
Externí odkaz:
http://arxiv.org/abs/2411.15265
Publikováno v:
Micro and Nano Engineering, Vol 14, Iss , Pp 100101- (2022)
We present a cryogenic system design and development for ice lithography. The cryo-stage is designed with embedded channels to allow direct liquid nitrogen flow, enabling fast cryogenic cooling, and low sample temperature. The stage cools down to 78.
Externí odkaz:
https://doaj.org/article/54dd450ecc104e0b9f8f1b21d135434a
State preparation that initializes quantum systems in a fiducial state and measurements to read outcomes after the evolution of quantum states, both essential elements in quantum information processing in general, may contain noise from which errors,
Externí odkaz:
http://arxiv.org/abs/2405.06291
We consider entanglement distillation in a realistic scenario with noisy operations in which quantum measurements that constitute a general quantum operation are particularly noisy. We present a protocol for purifying noisy measurements and show that
Externí odkaz:
http://arxiv.org/abs/2404.10538
Publikováno v:
LREC-COLING2024
Recently, sentiment-aware pre-trained language models (PLMs) demonstrate impressive results in downstream sentiment analysis tasks. However, they neglect to evaluate the quality of their constructed sentiment representations; they just focus on impro
Externí odkaz:
http://arxiv.org/abs/2404.01104
Diffusion models (DMs) excel in unconditional generation, as well as on applications such as image editing and restoration. The success of DMs lies in the iterative nature of diffusion: diffusion breaks down the complex process of mapping noise to da
Externí odkaz:
http://arxiv.org/abs/2403.12510
Autor:
Oh, Hyungjun, Kim, Kihong, Kim, Jaemin, Kim, Sungkyun, Lee, Junyeol, Chang, Du-seong, Seo, Jiwon
Publikováno v:
29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems(ASPLOS 24 summer cycle), Volume 2, Nov 15, 2023 (Notification Date)
This paper presents ExeGPT, a distributed system designed for constraint-aware LLM inference. ExeGPT finds and runs with an optimal execution schedule to maximize inference throughput while satisfying a given latency constraint. By leveraging the dis
Externí odkaz:
http://arxiv.org/abs/2404.07947
We present a comprehensive theoretical and computational model that explores the behavior of a thin hydrated film bonded to a non-hydrated / impermeable soft substrate in the context of surface and bulk elasticity coupled with surface diffusion kinet
Externí odkaz:
http://arxiv.org/abs/2403.06005