Zobrazeno 1 - 10
of 121 834
pro vyhledávání: '"Ré, A."'
The search for accreted satellites in the Galactic disk is a challenging task, to which Gaia plays a crucial role in synergy with ground-based spectroscopic surveys. In 2021, Re Fiorentin et al. discovered five substructures with disk kinematics incl
Externí odkaz:
http://arxiv.org/abs/2410.12581
Publikováno v:
New Frontiers in Science in the Era of AI, edited by M. Streit-Bianchi \& V. Gorini, 2024, Springer reproduced with permission of Springer Nature Switzerland AG
Among the great mysteries that physics has not yet solved are undoubtedly those of dark energy and dark matter. In this chapter we deal with the first of them. We will expound in detail the motivations that led to hypothesise the existence of dark en
Externí odkaz:
http://arxiv.org/abs/2410.10435
Autor:
Zhang, Michael, Arora, Simran, Chalamala, Rahul, Wu, Alan, Spector, Benjamin, Singhal, Aaryan, Ramesh, Krithik, Ré, Christopher
Recent works show we can linearize large language models (LLMs) -- swapping the quadratic attentions of popular Transformer-based LLMs with subquadratic analogs, such as linear attention -- avoiding the expensive pretraining costs. However, linearizi
Externí odkaz:
http://arxiv.org/abs/2410.10254
Autor:
Sarukkai, Vishnu, Shacklett, Brennan, Majercik, Zander, Bhatia, Kush, Ré, Christopher, Fatahalian, Kayvon
Large Language Models (LLMs) have the potential to automate reward engineering by leveraging their broad domain knowledge across various tasks. However, they often need many iterations of trial-and-error to generate effective reward functions. This p
Externí odkaz:
http://arxiv.org/abs/2410.09187
Autor:
Fifty, Christopher, Junkins, Ronald G., Duan, Dennis, Iger, Aniketh, Liu, Jerry W., Amid, Ehsan, Thrun, Sebastian, Ré, Christopher
Vector Quantized Variational AutoEncoders (VQ-VAEs) are designed to compress a continuous input to a discrete latent space and reconstruct it with minimal distortion. They operate by maintaining a set of vectors -- often referred to as the codebook -
Externí odkaz:
http://arxiv.org/abs/2410.06424
Fine-tuning large language models (LLMs) on instruction datasets is a common way to improve their generative capabilities. However, instruction datasets can be expensive and time-consuming to manually curate, and while LLM-generated data is less labo
Externí odkaz:
http://arxiv.org/abs/2410.05224
Autor:
Saad-Falcon, Jon, Lafuente, Adrian Gamarra, Natarajan, Shlok, Maru, Nahum, Todorov, Hristo, Guha, Etash, Buchanan, E. Kelly, Chen, Mayee, Guha, Neel, Ré, Christopher, Mirhoseini, Azalia
Inference-time techniques are emerging as highly effective tools to enhance large language model (LLM) capabilities. However, best practices for developing systems that combine these techniques remain underdeveloped due to our limited understanding o
Externí odkaz:
http://arxiv.org/abs/2409.15254
The control of quantum systems has been proven to possess trap-free optimization landscapes under the satisfaction of proper assumptions. However, many details of the landscape geometry and their influence on search efficiency still need to be fully
Externí odkaz:
http://arxiv.org/abs/2409.15139
Autor:
Blundo, Elena, Cuccu, Marzia, Tuzi, Federico, Fiorentin, Michele Re, Pettinari, Giorgio, Patra, Atanu, Cianci, Salvatore, Kudrynskyi, Zakhar, Felici, Marco, Taniguchi, Takashi, Watanabe, Kenji, Patanè, Amalia, Palummo, Maurizia, Polimeni, Antonio
Two-dimensional crystals stack together through weak van der Waals (vdW) forces, offering unlimited possibilities to play with layer number, order and twist angle in vdW heterostructures (HSs). The realisation of high-performance optoelectronic devic
Externí odkaz:
http://arxiv.org/abs/2409.09799
Research conducted previously has focused on either attitudes toward or behaviors associated with autonomous driving. In this paper, we bridge these two dimensions by exploring how attitudes towards autonomous driving influence behavior in an autonom
Externí odkaz:
http://arxiv.org/abs/2409.02556