Tootfinder

TR-PTS: Task-Relevant Parameter and Token Selection for Efficient Tuning
Siqi Luo, Haoran Yang, Yi Xin, Mingyang Yi, Guangyang Wu, Guangtao Zhai, Xiaohong Liu
https://arxiv.org/abs/2507.22872

TR-PTS: Task-Relevant Parameter and Token Selection for Efficient Tuning
Large pre-trained models achieve remarkable performance in vision tasks but are impractical for fine-tuning due to high computational and storage costs. Parameter-Efficient Fine-Tuning (PEFT) methods mitigate this issue by updating only a subset of parameters; however, most existing approaches are task-agnostic, failing to fully exploit task-specific adaptations, which leads to suboptimal efficiency and performance. To address this limitation, we propose Task-Relevant Parameter and Token Select…

New York city to ban all processed meats in hospitals, schools and shelters https://www.speciesunite.com/news-stories/new-york-city-to-ban-all-processed-meats-in-hospitals-schools-and-shelters

New York city to ban all processed meats in hospitals, schools and shelters — Species Unite
Mayor Eric Adams is determined to promote healthy eating among New Yorkers, having turned his own life around after adopting a plant-based diet.

Sequences of odd length in strict partitions IV: the combinatorics of parameterized Rogers-Ramanujan type identities
Haijun Li
https://arxiv.org/abs/2509.24942 https://

Sequences of odd length in strict partitions IV: the combinatorics of parameterized Rogers-Ramanujan type identities
In the first three papers, we conducted a series of discussions on the statistics of strict partitions and Rogers-Ramanujan partitions, specifically the sequences of odd length (denoted as $\mathrm{sol}$) and its extensions. We established bijections for some Rogers-Ramanujan type identities. This paper will continue that series of work, and first we will use the bijective method to re-establish several parameterized Rogers-Ramanujan type identities, which appeared in the recent work of Hao-Kua…

A surrogate model for topology optimisation of elastic structures via parametric autoencoders
Matteo Giacomini, Antonio Huerta
https://arxiv.org/abs/2507.22539 https://

A surrogate model for topology optimisation of elastic structures via parametric autoencoders
A surrogate-based topology optimisation algorithm for linear elastic structures under parametric loads and boundary conditions is proposed. Instead of learning the parametric solution of the state (and adjoint) problems or the optimisation trajectory as a function of the iterations, the proposed approach devises a surrogate version of the entire optimisation pipeline. First, the method predicts a quasi-optimal topology for a given problem configuration as a surrogate model of high-fidelity topo…

Parameterized Hardness of Zonotope Containment and Neural Network Verification
Vincent Froese, Moritz Grillo, Christoph Hertrich, Moritz Stargalla
https://arxiv.org/abs/2509.22849

Parameterized Hardness of Zonotope Containment and Neural Network Verification
Neural networks with ReLU activations are a widely used model in machine learning. It is thus important to have a profound understanding of the properties of the functions computed by such networks. Recently, there has been increasing interest in the (parameterized) computational complexity of determining these properties. In this work, we close several gaps and resolve an open problem posted by Froese et al. [COLT '25] regarding the parameterized complexity of various problems related to netwo…

One-loop analytic structure of the deep-infrared Landau-gauge gluon propagator at finite temperature
Giorgio Comitini
https://arxiv.org/abs/2509.23889 https://

One-loop analytic structure of the deep-infrared Landau-gauge gluon propagator at finite temperature
With the aim of looking for signatures of deconfinement, the poles and the spectral function of the Landau-gauge gluon propagator are investigated at one loop, vanishing spatial momentum and finite temperature within the framework of the screened massive expansion of pure Yang-Mills theory and of full QCD. When computed using both temperature-independent parameters optimized by principles of gauge invariance and temperature-dependent parameters obtained by fitting lattice data at zero Matsubara…

Light-SQ: Structure-aware Shape Abstraction with Superquadrics for Generated Meshes
Yuhan Wang, Weikai Chen, Zeyu Hu, Runze Zhang, Yingda Yin, Ruoyu Wu, Keyang Luo, Shengju Qian, Yiyan Ma, Hongyi Li, Yuan Gao, Yuhuan Zhou, Hao Luo, Wan Wang, Xiaobin Shen, Zhaowei Li, Kuixin Zhu, Chuanlang Hong, Yueyue Wang, Lijie Feng, Xin Wang, Chen Change Loy
https://

Light-SQ: Structure-aware Shape Abstraction with Superquadrics for Generated Meshes
In user-generated-content (UGC) applications, non-expert users often rely on image-to-3D generative models to create 3D assets. In this context, primitive-based shape abstraction offers a promising solution for UGC scenarios by compressing high-resolution meshes into compact, editable representations. Towards this end, effective shape abstraction must therefore be structure-aware, characterized by low overlap between primitives, part-aware alignment, and primitive compactness. We present Light-…

Atmospheric parameters and chemical abundances of young stars with APOGEE. I. Orion star-forming region
Ricardo L\'opez-Valdivia, Luc\'ia Adame, Carlos G. Rom\'an-Z\'u\~niga, Jes\'us Hern\'andez, Edilberto S\'anchez, Itzarel Herrn\'andez-Aburto, Jos\'e G. Fern\'andez-Trincado, Eduardo Zagala Lagunas, Leticia Carigi, J. E. M\'endez-Delgado, Marina Kounkel, Javier Serna, Richard R. Lane, Keivan G. Stassun, Sandro Villanova, Jinyoung Serena Kim,…

Atmospheric parameters and chemical abundances of young stars with APOGEE. I. Orion star-forming region
We derive atmospheric parameters and chemical abundances in young G-, K-, and M-type stars (temperatures between 6500 and 3100 K) using infrared APOGEE-2 spectra. Atmospheric parameters were determined for 548 young stars in the Orion complex (Orion A, B, OB1, and $λ$ Ori) using the TONALLI code. For 340 slow rotators v sini $\leq$ 30 km s$^{-1}$), we derived C, Mg, Si, K, Ti, and Fe abundances using 19 atomic lines, MARCS model atmospheres, and BACCHUS. To mitigate the impact of circumstellar…

Darksuite: an Algorithm for Dark Matter-Admixed Neutron Stars
Nguyen Thi Lan Anh, Peter Lott, Quynh Lan Nguyen
https://arxiv.org/abs/2507.22415 https://arx…

Darksuite: an Algorithm for Dark Matter-Admixed Neutron Stars
Gravitational-wave observations provide a unique window into the fundamental nature of massive objects. In particular, neutron star equations of state have been constrained due to the success of gravitational wave observatories. Recently, the possibility of detecting dark matter-admixed neutron stars via ground-based laser interferometry has been explored. Dark matter would impact the gravitational waveform of an inspiraling neutron star system through tidal parameters, namely the tidal deforma…

On an optimization framework for damage localization in structures
Owais Saleem, Tim Suchan, Natalie Rauter, Kathrin Welker
https://arxiv.org/abs/2509.22492 https://

On an optimization framework for damage localization in structures
Efficient structural damage localization remains a challenge in structural health monitoring (SHM), particularly when the problem is coupled with uncertainty of conditions and complexity of structures. Traditional methods simply based on experimental data processing are often not sufficiently reliable, while complex models often struggle with computational inefficiency given the tremendous amount of model parameters. This paper focuses on closing the gap between data-driven SHM and physics-base…