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pro vyhledávání: '"Phan, Huy"'
Predicting program behavior without execution is a crucial and challenging task in software engineering. Traditional models often struggle to capture the dynamic dependencies and interactions within code. This paper introduces a novel machine learnin
Externí odkaz:
http://arxiv.org/abs/2408.02816
Reinforcement learning from human feedback plays a crucial role in aligning language models towards human preferences, traditionally represented through comparisons between pairs or sets of responses within a given context. While many studies have en
Externí odkaz:
http://arxiv.org/abs/2407.14477
Autor:
Chen, Mingjie, Zhang, Hezhao, Li, Yuanchao, Luo, Jiachen, Wu, Wen, Ma, Ziyang, Bell, Peter, Lai, Catherine, Reiss, Joshua, Wang, Lin, Woodland, Philip C., Chen, Xie, Phan, Huy, Hain, Thomas
Speech emotion recognition is a challenging classification task with natural emotional speech, especially when the distribution of emotion types is imbalanced in the training and test data. In this case, it is more difficult for a model to learn to s
Externí odkaz:
http://arxiv.org/abs/2405.20064
Novice researchers often face difficulties in understanding a multitude of academic papers and grasping the fundamentals of a new research field. To solve such problems, the knowledge graph supporting research survey is gradually being developed. Exi
Externí odkaz:
http://arxiv.org/abs/2407.01553
Detecting the presence of animal vocalisations in nature is essential to study animal populations and their behaviors. A recent development in the field is the introduction of the task known as few-shot bioacoustic sound event detection, which aims t
Externí odkaz:
http://arxiv.org/abs/2403.18638
Autor:
Liang, Jinhua, Zhang, Huan, Liu, Haohe, Cao, Yin, Kong, Qiuqiang, Liu, Xubo, Wang, Wenwu, Plumbley, Mark D., Phan, Huy, Benetos, Emmanouil
We introduce WavCraft, a collective system that leverages large language models (LLMs) to connect diverse task-specific models for audio content creation and editing. Specifically, WavCraft describes the content of raw audio materials in natural lang
Externí odkaz:
http://arxiv.org/abs/2403.09527
Code Large Language Models (CodeLLMs) have demonstrated impressive proficiency in code completion tasks. However, they often fall short of fully understanding the extensive context of a project repository, such as the intricacies of relevant files an
Externí odkaz:
http://arxiv.org/abs/2403.06095
Autor:
Yang, Shanglin, Benedic, Yohann, Phan-Huy, Dinh-Thuy, Gorce, Jean-Marie, Villemaud, Guillaume
In this paper, we present a new ultra-low power method of indoor localization of smartphones (SM) based on zero-energy-devices (ZEDs) beacons instead of active wireless beacons. Each ZED is equipped with a unique identification number coded into a bi
Externí odkaz:
http://arxiv.org/abs/2402.16446
The 3GPP has recently conducted a study on the Ambient Internet of Things (AIoT), with a particular emphasis on examining backscatter communications as one of the primary techniques under consideration. Previous investigations into Ambient Backscatte
Externí odkaz:
http://arxiv.org/abs/2402.12657
Autor:
López, Onel, Singh, Ritesh Kumar, Phan-Huy, Dinh-Thuy, Katranaras, Efstathios, Mazloum, Nafiseh, Jäntti, Riku, Khan, Hamza, Rosabal, Osmel, Alexias, Pavlos, Raghuwanshi, Prasoon, Ruiz-Guirola, David, Singh, Bikramjit, Höglund, Andreas, Van, Dung Pham, Azarbahram, Amirhossein, Famaey, Jeroen
Low-cost, resource-constrained, maintenance-free, and energy-harvesting (EH) Internet of Things (IoT) devices, referred to as zero-energy devices (ZEDs), are rapidly attracting attention from industry and academia due to their myriad of applications.
Externí odkaz:
http://arxiv.org/abs/2402.09244