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pro vyhledávání: '"Kim, Jung‐in"'
Autor:
Sangarya, Vishwesh, Kim, Jung-Eun
As a strategy for sustainability of deep learning, reusing an existing model by retraining it rather than training a new model from scratch is critical. In this paper, we propose REpresentation Shift QUantifying Estimator (RESQUE), a predictive quant
Externí odkaz:
http://arxiv.org/abs/2412.15511
Large Language Models (LLMs) have shown strong performance in solving mathematical problems, with code-based solutions proving particularly effective. However, the best practice to leverage coding instruction data to enhance mathematical reasoning re
Externí odkaz:
http://arxiv.org/abs/2412.11699
Deep reinforcement learning (DRL) has emerged as an innovative solution for controlling legged robots in challenging environments using minimalist architectures. Traditional control methods for legged robots, such as inverse dynamics, either directly
Externí odkaz:
http://arxiv.org/abs/2412.09520
We theoretically and numerically elucidate the electrical control over spin waves in antiferromagnetic materials (AFM) with biaxial anisotropies and Dzyaloshinskii-Moriya interactions. The spin wave dispersion in an AFM manifests as a bifurcated spec
Externí odkaz:
http://arxiv.org/abs/2411.13309
In this paper we define absorptive Compton amplitudes, which captures the absorption factor for waves of spin-weight-$s$ scattering in black hole perturbation theory. At the leading order, in the $G M \omega$ expansion, such amplitudes are purely ima
Externí odkaz:
http://arxiv.org/abs/2411.03382
In a classical scattering problem, the classical eikonal is defined as the generator of the canonical transformation that maps in-states to out-states. It can be regarded as the classical limit of the log of the quantum S-matrix. In a classical analo
Externí odkaz:
http://arxiv.org/abs/2410.22988
Autor:
Kim, Jung-hun, Oh, Min-hwan
In this study, we consider multi-class multi-server asymmetric queueing systems consisting of $N$ queues on one side and $K$ servers on the other side, where jobs randomly arrive in queues at each time. The service rate of each job-server assignment
Externí odkaz:
http://arxiv.org/abs/2410.10098
Autor:
Li, Jianwei, Kim, Jung-Eun
As large language models (LLMs) are overwhelmingly more and more integrated into various applications, ensuring they generate safe and aligned responses is a pressing need. Previous research on alignment has largely focused on general instruction-fol
Externí odkaz:
http://arxiv.org/abs/2410.10862
Autor:
Rho, Donghwan, Kim, Taeseong, Park, Minje, Kim, Jung Woo, Chae, Hyunsik, Cheon, Jung Hee, Ryu, Ernest K.
Large language models (LLMs) offer personalized responses based on user interactions, but this use case raises serious privacy concerns. Homomorphic encryption (HE) is a cryptographic protocol supporting arithmetic computations in encrypted states an
Externí odkaz:
http://arxiv.org/abs/2410.02486
Abstract. The advancement of deep learning has coincided with the proliferation of both models and available data. The surge in dataset sizes and the subsequent surge in computational requirements have led to the development of the Dataset Condensati
Externí odkaz:
http://arxiv.org/abs/2409.14538