arXiv:2509.08765v2 Announce Type: replace-cross Abstract: Data-driven acceleration of scientific computing workflows has been a high-profile aim of machine learning (ML) for science, with numerical simulation of transient partial differential equations (PDEs) being one of the main applications. The focus thus…
arXiv:2508.19468v2 Announce Type: replace-cross Abstract: We present an extension of the Levenberg-Marquardt algorithm for fitting multichannel nuclear cross section data. Our approach offers a practical and robust alternative to conventional trust-region methods for analyzing experimental data. The CoH$_3$ code, based…
arXiv:2509.10166v1 Announce Type: new Abstract: In this paper, we consider the problem of computing the integral of a function on the unit sphere, in any dimension, using Monte Carlo methods. Although the methods we present are general, our guiding thread…
arXiv:2507.04779v2 Announce Type: replace Abstract: We propose o1Neuro, a new neural network model built on sparse indicator activation neurons, with two key statistical properties. (1) Constructive universal approximation: At the population level, a deep o1Neuro can approximate any measurable function…
arXiv:2509.09683v1 Announce Type: cross Abstract: Forecasting click volume is a key task in digital advertising, influencing both revenue and campaign strategy. Traditional time series models rely solely on numerical data, often overlooking rich contextual information embedded in textual elements, such…
arXiv:2509.10128v1 Announce Type: cross Abstract: Legged robots are promising candidates for exploring challenging areas on low-gravity bodies such as the Moon, Mars, or asteroids, thanks to their advanced mobility on unstructured terrain. However, as planetary robots’ power and thermal budgets…
arXiv:2509.09681v1 Announce Type: cross Abstract: This paper presents the db3 team’s winning solution for the Meta CRAG-MM Challenge 2025 at KDD Cup’25. Addressing the challenge’s unique multi-modal, multi-turn question answering benchmark (CRAG-MM), we developed a comprehensive framework that integrates tailored…
arXiv:2509.10078v1 Announce Type: cross Abstract: Researchers have applied established psychometric questionnaires (e.g., BFI, PVQ) to measure the personality traits and values reflected in the responses of Large Language Models (LLMs). However, concerns have been raised about applying these human-designed questionnaires…
arXiv:2509.09470v1 Announce Type: cross Abstract: Keeping pace with the rapid growth of academia literature presents a significant challenge for researchers, funding bodies, and academic societies. To address the time-consuming manual effort required for scholarly discovery, we present a novel, fully…
arXiv:2509.10057v1 Announce Type: cross Abstract: We address the problem of automatic synchronisation of the spintronic oscillator (STO) by means of reinforcement learning (RL). A numerical solution of the macrospin Landau-Lifschitz-Gilbert-Slonczewski equation is used to simulate the STO and we train…
