Tootfinder

Generalizable Geometric Image Caption Synthesis
Yue Xin, Wenyuan Wang, Rui Pan, Ruida Wang, Howard Meng, Renjie Pi, Shizhe Diao, Tong Zhang
https://arxiv.org/abs/2509.15217 http…

Generalizable Geometric Image Caption Synthesis
Multimodal large language models have various practical applications that demand strong reasoning abilities. Despite recent advancements, these models still struggle to solve complex geometric problems. A key challenge stems from the lack of high-quality image-text pair datasets for understanding geometric images. Furthermore, most template-based data synthesis pipelines typically fail to generalize to questions beyond their predefined templates. In this paper, we bridge this gap by introducing…

Hm...
This sounds like something that needs to be changed...
... dunno if on the side of #PeerTube or #Mastodon.
https://

Embedded DevOps: A Survey on the Application of DevOps Practices in Embedded Software and Firmware Development
Parthiv Katapara, Anand Sharma
https://arxiv.org/abs/2507.00421

Embedded DevOps: A Survey on the Application of DevOps Practices in Embedded Software and Firmware Development
The adoption of DevOps practices in embedded systems and firmware development is emerging as a response to the growing complexity of modern hardware--software co-designed products. Unlike cloud-native applications, embedded systems introduce challenges such as hardware dependency, real-time constraints, and safety-critical requirements. This literature review synthesizes findings from 20 academic and industrial sources to examine how DevOps principles--particularly continuous integration, conti…

The Early Career Workshop of GR-Amaldi 2025
S Al-Shammari, C P L Berry, C E A Chapman-Bird, F T Chowdhury, K Cunningham, M Emma, R Gray, C Hoy, I S Heng, M Korobko, E Maggio, A-K Malz, H Middleton, M Prathaban, I M Romero-Shaw, G Shaifullah, S Singh, J Steinlechner, K Toland, D Williams, M J Williams
https://arxiv.org/abs/2509.03360…

The Early Career Workshop of GR-Amaldi 2025
Gravitational physics and astronomy have developed rapidly over the last decade, driven by new observations and theoretical breakthroughs. As new as the science and technology of this field are, its greatest asset may be the body of early-career researchers actively engaged in driving it forward. With the aim of bringing together this community of enthusiastic scientists from a broad array of disciplines, the organisers of the GR-Amaldi meeting joined with the Gravitational-Wave Early Career Sc…

Variable selection for minimum-variance portfolios
Guilherme V. Moura, Andr\'e P. Santos, Hudson S. Torrent
https://arxiv.org/abs/2508.14986 https://ar…

Variable selection for minimum-variance portfolios
Machine learning (ML) methods have been successfully employed in identifying variables that can predict the equity premium of individual stocks. In this paper, we investigate if ML can also be helpful in selecting variables relevant for optimal portfolio choice. To address this question, we parameterize minimum-variance portfolio weights as a function of a large pool of firm-level characteristics as well as their second-order and cross-product transformations, yielding a total of 4,610 predicto…

Benchmark-Neutral Risk-Minimization for insurance products and nonreplicable claims
Michael Schmutz, Eckhard Platen, Thorsten Schmidt
https://arxiv.org/abs/2506.19494

Benchmark-Neutral Risk-Minimization for insurance products and nonreplicable claims
In this paper we study the pricing and hedging of nonreplicable contingent claims, such as long-term insurance contracts like variable annuities. Our approach is based on the benchmark-neutral pricing framework of Platen (2024), which differs from the classical benchmark approach by using the stock growth optimal portfolio as the numéraire. In typical settings, this choice leads to an equivalent martingale measure, the benchmark-neutral measure. The resulting prices can be significantly lower …