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pro vyhledávání: '"Elkins A"'
As a powerful and rapidly advancing dual-use technology, AI offers both immense benefits and worrisome risks. In response, governing bodies around the world are developing a range of regulatory AI laws and policies. This paper compares three distinct
Externí odkaz:
http://arxiv.org/abs/2410.21279
Speech-based depression detection poses significant challenges for automated detection due to its unique manifestation across individuals and data scarcity. Addressing these challenges, we introduce DAAMAudioCNNLSTM and DAAMAudioTransformer, two para
Externí odkaz:
http://arxiv.org/abs/2409.00391
It has been known since 1992 that the McKay-Thompson series $T_g(q)$ of the Moonshine module form Hauptmoduln for genus zero subgroups of $SL(2, \mathbb{R})$. In 2021, Lin and Shao constructed a series analogous to the McKay-Thompson series (a twined
Externí odkaz:
http://arxiv.org/abs/2408.16263
Detecting out-of-distribution (OOD) data is crucial in machine learning applications to mitigate the risk of model overconfidence, thereby enhancing the reliability and safety of deployed systems. The majority of existing OOD detection methods predom
Externí odkaz:
http://arxiv.org/abs/2408.11237
Autor:
Jarmak, Stephanie G., Becker, Tracy M., Woodward, Charles E., Honniball, Casey I., Rivkin, Andrew S., McAdam, Margaret M., Landsman, Zoe A., Cambioni, Saverio, Müller, Thomas G., Takir, Driss, Retherford, Kurt D., Arredondo, Anicia, Elkins-Tanton, Linda T.
Our understanding of Solar System evolution is closely tied to interpretations of asteroid composition, particularly the M-class asteroids. These asteroids were initially thought to be the exposed cores of differentiated planetesimals, a hypothesis b
Externí odkaz:
http://arxiv.org/abs/2407.12162
Autor:
Eiras, Francisco, Petrov, Aleksandar, Vidgen, Bertie, Schroeder, Christian, Pizzati, Fabio, Elkins, Katherine, Mukhopadhyay, Supratik, Bibi, Adel, Purewal, Aaron, Botos, Csaba, Steibel, Fabro, Keshtkar, Fazel, Barez, Fazl, Smith, Genevieve, Guadagni, Gianluca, Chun, Jon, Cabot, Jordi, Imperial, Joseph, Nolazco, Juan Arturo, Landay, Lori, Jackson, Matthew, Torr, Phillip H. S., Darrell, Trevor, Lee, Yong, Foerster, Jakob
Applications of Generative AI (Gen AI) are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about the potential risks of the tec
Externí odkaz:
http://arxiv.org/abs/2405.08597
Autor:
Eiras, Francisco, Petrov, Aleksandar, Vidgen, Bertie, de Witt, Christian Schroeder, Pizzati, Fabio, Elkins, Katherine, Mukhopadhyay, Supratik, Bibi, Adel, Csaba, Botos, Steibel, Fabro, Barez, Fazl, Smith, Genevieve, Guadagni, Gianluca, Chun, Jon, Cabot, Jordi, Imperial, Joseph Marvin, Nolazco-Flores, Juan A., Landay, Lori, Jackson, Matthew, Röttger, Paul, Torr, Philip H. S., Darrell, Trevor, Lee, Yong Suk, Foerster, Jakob
In the next few years, applications of Generative AI are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about potential risks
Externí odkaz:
http://arxiv.org/abs/2404.17047
Autor:
Elkins, Jacob G., Fahimi, Farbod
Deep neural networks (DNNs), trained with gradient-based optimization and backpropagation, are currently the primary tool in modern artificial intelligence, machine learning, and data science. In many applications, DNNs are trained offline, through s
Externí odkaz:
http://arxiv.org/abs/2402.00761
We propose the Multi-Head Density Adaptive Attention Mechanism (DAAM), a novel probabilistic attention framework that can be used for Parameter-Efficient Fine-tuning (PEFT), and the Density Adaptive Transformer (DAT), designed to enhance information
Externí odkaz:
http://arxiv.org/abs/2401.11143
Question generation (QG) is a natural language processing task with an abundance of potential benefits and use cases in the educational domain. In order for this potential to be realized, QG systems must be designed and validated with pedagogical nee
Externí odkaz:
http://arxiv.org/abs/2401.05914