Tootfinder

This https://arxiv.org/abs/2409.15104 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

PecSched: Preemptive and Efficient Cluster Scheduling for LLM Inference
The scaling of transformer-based Large Language Models (LLMs) has significantly expanded their context lengths, enabling applications where inputs exceed 100K tokens. Our analysis of a recent Azure LLM inference trace reveals a highly skewed long-tail distribution of input lengths, with approximately 80% of inputs shorter than 2K tokens. Long inputs constitute only a small fraction. Existing cluster-level LLM scheduling strategies, including First-In-First-Out (FIFO), reservation-based, and pri…

Jazzaria – Fire and Forget
#byncnd

A Cubic Regularization Method for Multiobjective Optimization
Douglas S. Gon\c{c}alves, Max L. N. Gon\c{c}alves, Jefferson G. Melo
https://arxiv.org/abs/2506.08181

A Cubic Regularization Method for Multiobjective Optimization
This work introduces a new cubic regularization method for nonconvex unconstrained multiobjective optimization problems. At each iteration of the method, a model associated with the cubic regularization of each component of the objective function is minimized. This model allows approximations for the first- and second-order derivatives, which must satisfy suitable error conditions. One interesting feature of the proposed algorithm is that the regularization parameter of the model and the accura…

Less is More: some Computational Principles based on Parcimony, and Limitations of Natural Intelligence
Laura Cohen, Xavier Hinaut, Lilyana Petrova, Alexandre Pitti, Syd Reynal, Ichiro Tsuda
https://arxiv.org/abs/2506.07060

Less is More: some Computational Principles based on Parcimony, and Limitations of Natural Intelligence
Natural intelligence (NI) consistently achieves more with less. Infants learn language, develop abstract concepts, and acquire sensorimotor skills from sparse data, all within tight neural and energy limits. In contrast, today's AI relies on virtually unlimited computational power, energy, and data to reach high performance. This paper argues that constraints in NI are paradoxically catalysts for efficiency, adaptability, and creativity. We first show how limited neural bandwidth promotes conci…

Revealing the Dominance of the Orbital Hall Effect over Spin in Transition Metal Heterostructures
J. L. Costa, E. Santos, J. B. S. Mendes, A. Azevedo
https://arxiv.org/abs/2506.08425

Revealing the Dominance of the Orbital Hall Effect over Spin in Transition Metal Heterostructures
We study inverse spin and orbital Hall effects in 19 transition metals using spin-pumping driven by ferromagnetic resonance. Spin-to-charge conversion was measured in YIG/X(5), while orbital-to-charge conversion was probed in YIG/Pt(2)/X(5) heterostructures. Here, X represents the different transition metals. Surprisingly, the orbital contribution overwhelmingly dominates over the spin response, clarifying the challenge of disentangling these effects. Our results largely agree with first-princi…

Relativistic Core-Valence-Separated Molecular Mean-Field Exact-Two-Component Equation-of-Motion Coupled Cluster Theory: Applications to L-edge X-ray Absorption Spectroscopy
Samragni Banerjee, Run R. Li, Brandon C. Cooper, Tianyuan Zhang, Edward F. Valeev, Xiaosong Li, A. Eugene DePrince III
https://arxiv.org/abs/2506.09008

Relativistic Core-Valence-Separated Molecular Mean-Field Exact-Two-Component Equation-of-Motion Coupled Cluster Theory: Applications to L-edge X-ray Absorption Spectroscopy
L-edge X-ray absorption spectra for first-row transition metal complexes are obtained from relativistic equation-of-motion singles and doubles coupled-cluster (EOM-CCSD) calculations that make use of the core-valence separation (CVS) scheme, with scalar and spin--orbit relativistic effects modeled within the molecular mean-field exact two-component (X2C) framework. By incorporating relativistic effects variationally at the Dirac--Coulomb--Breit (DCB) reference level, this method delivers accura…

This https://arxiv.org/abs/2407.19353 has been replaced.
initial toot: https://mastoxiv.page/@arX…

A spring-block theory of feature learning in deep neural networks
Feature-learning deep nets progressively collapse data to a regular low-dimensional geometry. How this emerges from the collective action of nonlinearity, noise, learning rate, and other factors, has eluded first-principles theories built from microscopic neuronal dynamics. We exhibit a noise-nonlinearity phase diagram that identifies regimes where shallow or deep layers learn more effectively and propose a macroscopic mechanical theory that reproduces the diagram and links feature learning acr…

Frustrated $J_1-J_2$ Diamond Lattice Antiferromagnet Co$_2$Ti$_3$O$_8$ with a Vacancy-ordered Spinel Structure Synthesized via a Topochemical Reaction
Rio Kumeda, Yuya Haraguchi, Daisuke Nishio-Hamane, Akira Matsuo, Koichi Kindo, Hiroko Aruga Katori
https://arxiv.org/abs/2506.05099

Frustrated $J_1-J_2$ Diamond Lattice Antiferromagnet Co$_2$Ti$_3$O$_8$ with a Vacancy-ordered Spinel Structure Synthesized via a Topochemical Reaction
Metastable Co$_2$Ti$_3$O$_8$ was synthesized through a topochemical reaction using Li$_2$CoTi$_3$O$_8$ as the precursor, resulting in a vacancy-ordered spinel structure. Crystal structure analysis confirmed that Co ions selectively occupy the A-site, giving rise to a frustrated diamond lattice. Magnetic susceptibility and heat capacity measurements revealed antiferromagnetic order at 4.4 K, which is markedly suppressed compared to the negative Weiss temperature of ${\sim}-27$ K, indicating a hi…

Cowboys new backup QB outranks 10 drafted higher, including 2 first-round picks https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2025/06/04/cowboys-milton-backup-qb-rankings-2025/84029638007/

ONLINE WORKSHOP> Navigating Indra’s Net: Digital Approaches to Text Reuse-based Inter-textuality in Pre-Modern East Asian Texts
https://ift.tt/ajGgrIY
When did aliens become a problem? The Mediterranean Association for Marine Biology and Oceanology in…
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