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In-context learning (ICL) is a powerful paradigm where large language models (LLMs) benefit from task demonstrations added to the prompt. Yet, selecting optimal demonstrations is not trivial, especially for complex or multi-modal tasks where input an
Externí odkaz:
http://arxiv.org/abs/2410.14049
Autor:
Wang, Lei, Dong, Shan, Xu, Yuhui, Dong, Hanze, Wang, Yalu, Saha, Amrita, Lim, Ee-Peng, Xiong, Caiming, Sahoo, Doyen
Recent large language models (LLMs) have demonstrated versatile capabilities in long-context scenarios. Although some recent benchmarks have been developed to evaluate the long-context capabilities of LLMs, there is a lack of benchmarks evaluating th
Externí odkaz:
http://arxiv.org/abs/2410.04698
Autor:
Pang, Khang Ee
The classical no-slip boundary condition of the Navier-Stokes equations fails to describe the spreading motion of a droplet on a substrate due to the missing small-scale physics near the contact line. In this thesis, we introduce a novel regularizati
Externí odkaz:
http://arxiv.org/abs/2409.17187
In this technical report, we describe the SNTL-NTU team's submission for Task 1 Data-Efficient Low-Complexity Acoustic Scene Classification of the detection and classification of acoustic scenes and events (DCASE) 2024 challenge. Three systems are in
Externí odkaz:
http://arxiv.org/abs/2409.11964
Sound event localization and detection (SELD) is critical for various real-world applications, including smart monitoring and Internet of Things (IoT) systems. Although deep neural networks (DNNs) represent the state-of-the-art approach for SELD, the
Externí odkaz:
http://arxiv.org/abs/2409.11700
High-dimensional variable selection has emerged as one of the prevailing statistical challenges in the big data revolution. Many variable selection methods have been adapted for identifying single nucleotide polymorphisms (SNPs) linked to phenotypic
Externí odkaz:
http://arxiv.org/abs/2408.10401
Autor:
Ee, Shaun Kai Ern
Publikováno v:
Pacific Forum Issues and Insights (2021), Vol. 21, SR4
The partnership between the United States and Singapore is founded in no small part on the shared recognition of the value that technology has for national security. Over the last 55 years, Singapore has become an established purchaser of U.S. defens
Externí odkaz:
http://arxiv.org/abs/2408.07946
The complex and evolving threat landscape of frontier AI development requires a multi-layered approach to risk management ("defense-in-depth"). By reviewing cybersecurity and AI frameworks, we outline three approaches that can help identify gaps in t
Externí odkaz:
http://arxiv.org/abs/2408.07933
Publikováno v:
IEEE IoT Journal, 2021
With rapid urbanization comes the increase of community, construction, and transportation noise in residential areas. The conventional approach of solely relying on sound pressure level (SPL) information to decide on the noise environment and to plan
Externí odkaz:
http://arxiv.org/abs/2408.05721
Autor:
Yap, Teng Ee, Batygin, Konstantin
Publikováno v:
Icarus, 417, 116085 (2024)
The degree of coupling between dust particles and their surrounding gas in protoplanetary disks is quantified by the dimensionless Stokes number. The Stokes number (St) governs particle size and spatial distributions, in turn establishing the dominan
Externí odkaz:
http://arxiv.org/abs/2408.00159