Zobrazeno 1 - 10
of 7 195
pro vyhledávání: '"A. Akshat"'
Autor:
Otter, Justin Atsushi, Alatalo, Katherine, Rowlands, Kate, McDermid, Richard M., Davis, Timothy A., Federrath, Christoph, French, K. Decker, Heckman, Timothy, Ogle, Patrick, Kakkad, Darshan, Luo, Yuanze, Nyland, Kristina, Tripathi, Akshat, Patil, Pallavi, Petric, Andreea, Smercina, Adam, Skarbinski, Maya, Lanz, Lauranne, Larson, Kristin, Appleton, Philip N., Aalto, Susanne, Olander, Gustav, Sazonova, Elizaveta, Smith, J. D. T.
We present Gemini near-infrared integral field spectrograph (NIFS) K-band observations of the central 400 pc of NGC 1266, a nearby (D$\approx$30 Mpc) post-starburst galaxy with a powerful multi-phase outflow and a shocked ISM. We detect 7 H$_2$ ro-vi
Externí odkaz:
http://arxiv.org/abs/2409.17319
Autor:
Mittu, Fazal, Bu, Yihuan, Gupta, Akshat, Devireddy, Ashok, Ozdarendeli, Alp Eren, Singh, Anant, Anumanchipalli, Gopala
While the language modeling objective has been shown to be deeply connected with compression, it is surprising that modern LLMs are not employed in practical text compression systems. In this paper, we provide an in-depth analysis of neural network a
Externí odkaz:
http://arxiv.org/abs/2409.17141
In the case of compute-intensive machine learning, efficient operating system scheduling is crucial for performance and energy efficiency. This paper conducts a comparative study over FIFO(First-In-First-Out) and RR(Round-Robin) scheduling policies w
Externí odkaz:
http://arxiv.org/abs/2409.15704
Layer normalization is a pivotal step in the transformer architecture. This paper delves into the less explored geometric implications of this process, examining how LayerNorm influences the norm and orientation of hidden vectors in the representatio
Externí odkaz:
http://arxiv.org/abs/2409.12951
Let $d,k$ be natural numbers and let $\mathcal{L}_1, \dots, \mathcal{L}_k \in \mathrm{GL}_d(\mathbb{Q})$ be linear transformations such that there are no non-trivial subspaces $U, V \subseteq \mathbb{Q}^d$ of the same dimension satisfying $\mathcal{L
Externí odkaz:
http://arxiv.org/abs/2409.05638
We show how the 2-Higgs Doublet Model (2HDM) Type-I can explain some excesses recently seen at the Large Hadron Collider (LHC) in $\gamma\gamma$ and $\tau^+\tau^-$ final states in turn matching Large Electron Positron (LEP) data in $b\bar b$ signatur
Externí odkaz:
http://arxiv.org/abs/2409.02587
Autor:
Huber, Patrick, Einolghozati, Arash, Conway, Rylan, Narang, Kanika, Smith, Matt, Nayyar, Waqar, Sagar, Adithya, Aly, Ahmed, Shrivastava, Akshat
Distilling conversational skills into Small Language Models (SLMs) with approximately 1 billion parameters presents significant challenges. Firstly, SLMs have limited capacity in their model parameters to learn extensive knowledge compared to larger
Externí odkaz:
http://arxiv.org/abs/2408.11219
Moving Target Defense (MTD) has emerged as a proactive and dynamic framework to counteract evolving cyber threats. Traditional MTD approaches often rely on assumptions about the attackers knowledge and behavior. However, real-world scenarios are inhe
Externí odkaz:
http://arxiv.org/abs/2408.08934
Modern data centres are increasingly adopting containers to enhance power and performance efficiency. These data centres consist of multiple heterogeneous machines, each equipped with varying amounts of resources such as CPU, I/O, memory, and network
Externí odkaz:
http://arxiv.org/abs/2408.01176
Autor:
Lin, Xi Victoria, Shrivastava, Akshat, Luo, Liang, Iyer, Srinivasan, Lewis, Mike, Ghosh, Gargi, Zettlemoyer, Luke, Aghajanyan, Armen
We introduce MoMa, a novel modality-aware mixture-of-experts (MoE) architecture designed for pre-training mixed-modal, early-fusion language models. MoMa processes images and text in arbitrary sequences by dividing expert modules into modality-specif
Externí odkaz:
http://arxiv.org/abs/2407.21770