output
20232026
most citedA Survey on Efficient Large Language Model Training: From Data-centric Perspectives

4 citations

7 papers

math.AP2026

Optimal Spectral Inequality for the Higher-Dimensional Landau Operator

Sedef Özcan, Matthias Täufer

We prove optimal spectral inequalities for Landau operators in full space and in arbitrary dimension. Spectral inequalities are lower bounds on the L 2 -mass of functions in spectr…

cs.CL2025★ 4 cited

A Survey on Efficient Large Language Model Training: From Data-centric Perspectives

Junyu Luo, Bohan Wu, Xiao Luo +8

Post-training of Large Language Models (LLMs) is crucial for unlocking their task generalization potential and domain-specific capabilities. However, the current LLM post-training…

physics.class-ph2025★ 1 cited

Tracking the normal modes of an overpass highway bridge using Distributed Acoustic Sensing

E. Diego Mercerat, Martijn P. A. van den Ende, Anthony Sladen +6

Distributed Acoustic Sensing (DAS) of ambient vibrations is a promising technique in the context of structural health monitoring of civil engineering structures. The methodology us…

math.NT2025

Large smooth twins from short lattice vectors

Erik Mulder, Bruno Sterner, Wessel van Woerden

Finding the largest pair of consecutive -smooth integers is computationally challenging. Current algorithms to find such pairs have an exponential runtime -- which has only be p…

gr-qc2025

Modified Black Hole Potentials and Their Korteweg-de Vries Integrals: Instabilities and Beyond

Michele Lenzi, Arnau Montava Agudo, Carlos F. Sopuerta

Black Hole (BH) Quasi-Normal Modes (QNMs) and Greybody Factors (GBFs) are key signatures of BH dynamics that are crucial for testing fundamental physics via gravitational waves. Re…

cond-mat.soft2025★ 2 cited

Confusion-driven machine learning of structural phases of a flexible, magnetic Stockmayer polymer

Dilina Perera, Samuel McAllister, Joan Josep Cerdà +1

We use a semi-supervised, neural-network based machine learning technique, the confusion method, to investigate structural transitions in magnetic polymers, which we model as chain…