Zobrazeno 1 - 10
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pro vyhledávání: '"Kim, In Soo"'
This paper aims to adapt the source model to the target environment, leveraging small user feedback (i.e., labeled target data) readily available in real-world applications. We find that existing semi-supervised domain adaptation (SemiSDA) methods of
Externí odkaz:
http://arxiv.org/abs/2407.15383
Wi-Fi fingerprinting is widely applied for indoor localization due to the widespread availability of Wi-Fi devices. However, traditional methods are not ideal for multi-building and multi-floor environments due to the scalability issues. Therefore, m
Externí odkaz:
http://arxiv.org/abs/2407.13303
In this paper, we present a new solution to the problem of large-scale multi-building and multi-floor indoor localization based on linked neural networks, where each neural network is dedicated to a sub-problem and trained under a hierarchical stage-
Externí odkaz:
http://arxiv.org/abs/2407.13288
This report describes the submission of HYU ASML team to the IEEE Signal Processing Cup 2024 (SP Cup 2024). This challenge, titled "ROBOVOX: Far-Field Speaker Recognition by a Mobile Robot," focuses on speaker recognition using a mobile robot in nois
Externí odkaz:
http://arxiv.org/abs/2407.11365
We propose a novel two-stage text-to-speech (TTS) framework with two types of discrete tokens, i.e., semantic and acoustic tokens, for high-fidelity speech synthesis. It features two core components: the Interpreting module, which processes text and
Externí odkaz:
http://arxiv.org/abs/2406.17310
Publikováno v:
Nanophotonics 12.13 (2023): 2415-2423
We propose a metasurface antenna capable of real time holographic beam steering. An array of reconfigurable dipoeles can generate on demand far field patterns of radiation through the specific encoding of meta atomic states. i.e., the configuration o
Externí odkaz:
http://arxiv.org/abs/2406.14585
In this paper, we conduct a study to utilize LLMs as a solution for decision making that requires complex data analysis. We define Decision QA as the task of answering the best decision, $d_{best}$, for a decision-making question $Q$, business rules
Externí odkaz:
http://arxiv.org/abs/2406.12430
In this paper, we propose MakeSinger, a semi-supervised training method for singing voice synthesis (SVS) via classifier-free diffusion guidance. The challenge in SVS lies in the costly process of gathering aligned sets of text, pitch, and audio data
Externí odkaz:
http://arxiv.org/abs/2406.05965
In traditional federated learning, a single global model cannot perform equally well for all clients. Therefore, the need to achieve the client-level fairness in federated system has been emphasized, which can be realized by modifying the static aggr
Externí odkaz:
http://arxiv.org/abs/2405.20821
Autor:
Lee, Yoonjoo, Son, Kihoon, Kim, Tae Soo, Kim, Jisu, Chung, John Joon Young, Adar, Eytan, Kim, Juho
As Large Language Models (LLMs) are nondeterministic, the same input can generate different outputs, some of which may be incorrect or hallucinated. If run again, the LLM may correct itself and produce the correct answer. Unfortunately, most LLM-powe
Externí odkaz:
http://arxiv.org/abs/2405.05581