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pro vyhledávání: '"Son, In"'
Transformer-based large-scale pre-trained models achieve great success, and fine-tuning, which tunes a pre-trained model on a task-specific dataset, is the standard practice to utilize these models for downstream tasks. Recent work has developed adap
Externí odkaz:
http://arxiv.org/abs/2412.03587
Autor:
Nguyen, Viet Anh, Nguyen, Linh Thi Dieu, Do, Thi Thu Ha, Wu, Ye, Sergeev, Aleksandr A., Zhu, Ding, Valuckas, Vytautas, Pham, Duong, Bui, Hai Xuan Son, Hoang, Duy Mai, Bui, Son Tung, Bui, Xuan Khuyen, Nguyen, Binh Thanh, Nguyen, Hai Son, Vu, Lam Dinh, Rogach, Andrey, Ha, Son Tung, Le-Van, Quynh
Publikováno v:
J Phys Chem Lett J Phys Chem Lett . 2024 Nov 14;15(45):11291-11299
Enhancing light emission from perovskite nanocrystal (NC) films is essential in light-emitting devices, as their conventional stacks often restrict the escape of emitted light. This work addresses this challenge by employing a TiO$_2$ grating to enha
Externí odkaz:
http://arxiv.org/abs/2411.12463
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence, 2025
Most techniques approach the problem of image forgery localization as a binary segmentation task, training neural networks to label original areas as 0 and forged areas as 1. In contrast, we tackle this issue from a more fundamental perspective by pa
Externí odkaz:
http://arxiv.org/abs/2412.08197
Given a simple graph $G$, the artinian monomial algebra associated to $G$, denoted by $A(G)$, is defined by the edge ideal of $G$ and the squares of the variables. In this article, we classify some tadpole graphs $G$ for which $A(G)$ has or fails the
Externí odkaz:
http://arxiv.org/abs/2412.08037
Large language models (LLMs) often struggle to objectively identify latent characteristics in large datasets due to their reliance on pre-trained knowledge rather than actual data patterns. To address this data grounding issue, we propose Data Scient
Externí odkaz:
http://arxiv.org/abs/2412.06303
Autor:
Son, Jeongrak, Ganardi, Ray, Minagawa, Shintaro, Buscemi, Francesco, Lie, Seok Hyung, Ng, Nelly H. Y.
In resource theories, catalysis refers to the possibility of enabling otherwise inaccessible quantum state transitions by providing the agent with an auxiliary system, under the condition that this auxiliary is returned to its initial state at the en
Externí odkaz:
http://arxiv.org/abs/2412.06900
Efficiently preparing approximate ground-states of large, strongly correlated systems on quantum hardware is challenging and yet nature is innately adept at this. This has motivated the study of thermodynamically inspired approaches to ground-state p
Externí odkaz:
http://arxiv.org/abs/2412.04554
Autor:
Cho, Sung Woong, Son, Hwijae
Inverse problems involving partial differential equations (PDEs) can be seen as discovering a mapping from measurement data to unknown quantities, often framed within an operator learning approach. However, existing methods typically rely on large am
Externí odkaz:
http://arxiv.org/abs/2412.03161
Contrastive learning has significantly improved representation quality, enhancing knowledge transfer across tasks in continual learning (CL). However, catastrophic forgetting remains a key challenge, as contrastive based methods primarily focus on "s
Externí odkaz:
http://arxiv.org/abs/2412.02865
Autor:
Nguyen, Trung-Hieu, Vuong, Truong-Giang, Duong, Hong-Nam, Nguyen, Son, Vo, Hieu Dinh, Aoki, Toshiaki, Nguyen, Thu-Trang
Autonomous vehicles (AVs) have demonstrated significant potential in revolutionizing transportation, yet ensuring their safety and reliability remains a critical challenge, especially when exposed to dynamic and unpredictable environments. Real-world
Externí odkaz:
http://arxiv.org/abs/2412.02574