Zobrazeno 1 - 10
of 20 081
pro vyhledávání: '"Arjun, A. P."'
The growing power of data science can play a crucial role in addressing social discrimination, necessitating nuanced understanding and effective mitigation strategies of potential biases. Data Science Looks At Discrimination (dsld) is an R and Python
Externí odkaz:
http://arxiv.org/abs/2411.04228
We discover a surprising connection between Carrollian symmetries and hydrodynamics in the shallow water approximation. Carrollian symmetries arise in the speed of light going to zero limit of relativistic Poincar\'e symmetries. Using a recent gauge
Externí odkaz:
http://arxiv.org/abs/2411.04190
Autor:
Zabel, Nikki, Loni, Alessandro, Sarzi, Marc, Serra, Paolo, Chawla, Arjun, Davis, Timothy A., Kleiner, Dane, Loubser, S. Ilani, Peletier, Reynier
We combine new and archival MUSE observations with data from the MeerKAT Fornax Survey and the ALMA Fornax Cluster Survey to study the ionised, atomic, and molecular gas in six gas-rich dwarf galaxies in the Fornax cluster in detail. We compare the d
Externí odkaz:
http://arxiv.org/abs/2411.02931
The increasing prevalence of AI-generated content alongside human-written text underscores the need for reliable discrimination methods. To address this challenge, we propose a novel framework with textual embeddings from Pre-trained Language Models
Externí odkaz:
http://arxiv.org/abs/2411.00411
In safeguarding mission-critical systems, such as Unmanned Aerial Vehicles (UAVs), preserving the privacy of path trajectories during navigation is paramount. While the combination of Reinforcement Learning (RL) and Fully Homomorphic Encryption (FHE)
Externí odkaz:
http://arxiv.org/abs/2411.00403
In many industrial applications, it is common that the graph embeddings generated from training GNNs are used in an ensemble model where the embeddings are combined with other tabular features (e.g., original node or edge features) in a downstream ML
Externí odkaz:
http://arxiv.org/abs/2411.00287
Autor:
Pucha, Ragadeepika, Juneau, S., Dey, Arjun, Siudek, M., Mezcua, M., Moustakas, J., BenZvi, S., Hainline, K., Hviding, R., Mao, Yao-Yuan, Alexander, D. M., Alfarsy, R., Circosta, C., Guo, Wei-Jian, Manwadkar, V., Martini, P., Weaver, B. A., Aguilar, J., Ahlen, S., Bianchi, D., Brooks, D., Canning, R., Claybaugh, T., Dawson, K., de la Macorra, A., Dey, Biprateep, Doel, P., Font-Ribera, A., Forero-Romero, J. E., Gaztañaga, E., Gontcho, S. Gontcho A, Gutierrez, G., Honscheid, K., Kehoe, R., Koposov, S. E., Lambert, A., Landriau, M., Guillou, L. Le, Meisner, A., Miquel, R., Prada, F., Rossi, G., Sanchez, E., Schlegel, D., Schubnell, M., Seo, H., Sprayberry, D., Tarlé, G., Zou, H.
Using early data from the Dark Energy Spectroscopic Instrument (DESI) survey, we search for AGN signatures in 410,757 line-emitting galaxies. By employing the BPT emission-line ratio diagnostic diagram, we identify AGN in 75,928/296,261 ($\approx$25.
Externí odkaz:
http://arxiv.org/abs/2411.00091
Autor:
Wei, Yuxiang, Cassano, Federico, Liu, Jiawei, Ding, Yifeng, Jain, Naman, Mueller, Zachary, de Vries, Harm, von Werra, Leandro, Guha, Arjun, Zhang, Lingming
Instruction tuning is a supervised fine-tuning approach that significantly improves the ability of large language models (LLMs) to follow human instructions. We propose SelfCodeAlign, the first fully transparent and permissive pipeline for self-align
Externí odkaz:
http://arxiv.org/abs/2410.24198
Autor:
Maneesha, P., Samantaray, Koyal Suman, Saha, Rakhi, Urkude, Rajashri, Ghosh, Biplab, Pathak, Arjun K, Bhaumik, Indranil, Mekki, Abdelkrim, Harrabi, Khalil, Sen, Somaditya
Materials with magnetoelectric coupling (MEC) between ferroic orders at room temperature are extremely important in modern technology and physics. BaTiO$_3$ is a robust ferroelectric in which several doping have led to MEC. However, often MEC depends
Externí odkaz:
http://arxiv.org/abs/2410.22018
Autor:
Williams, Andrew Robert, Ashok, Arjun, Marcotte, Étienne, Zantedeschi, Valentina, Subramanian, Jithendaraa, Riachi, Roland, Requeima, James, Lacoste, Alexandre, Rish, Irina, Chapados, Nicolas, Drouin, Alexandre
Forecasting is a critical task in decision making across various domains. While numerical data provides a foundation, it often lacks crucial context necessary for accurate predictions. Human forecasters frequently rely on additional information, such
Externí odkaz:
http://arxiv.org/abs/2410.18959