Tootfinder

Detailed Microwave Continuum Spectra from Bright Protoplanetary Disks in Taurus
Caleb Painter, Sean M. Andrews, Claire J. Chandler, Takahiro Ueda, David J. Wilner, Feng Long, Enrique Macias, Carlos Carrasco-Gonzalez, Chia-Ying Chung, Hauyu Baobab Liu, Tilman Birnstiel, A. Meredith Hughes
https://arxiv.org/abs/2507.21268

Detailed Microwave Continuum Spectra from Bright Protoplanetary Disks in Taurus
We present new observations that densely sample the microwave (4-360 GHz) continuum spectra from eight young systems in the Taurus region. Multi-component, empirical model prescriptions were used to disentangle the contributions from their dust disks and other emission mechanisms. We found partially optically thick, free-free emission in all these systems, with positive spectral indices (median $α_{\rm c} \approx 1$ at 10 GHz) and contributing 5-50% of the 43 GHz fluxes. There is no evidence f…

This https://arxiv.org/abs/2410.03614 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Proudfoot-Speyer degenerations of scattering equations
We study scattering equations of hyperplane arrangements from the perspective of combinatorial commutative algebra and numerical algebraic geometry. We formulate the problem as linear equations on a reciprocal linear space and develop a degeneration-based homotopy algorithm for solving them. We investigate the Hilbert regularity of the corresponding homogeneous ideal and apply our methods to CHY scattering equations.

TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Tracker
Qi Li, Shaheer U. Saeed, Yuliang Huang, Mingyuan Luo, Zhongnuo Yan, Jiongquan Chen, Xin Yang, Dong Ni, Nektarios Winter, Phuc Nguyen, Lucas Steinberger, Caelan Haney, Yuan Zhao, Mingjie Jiang, Bowen Ren, SiYeoul Lee, Seonho Kim, MinKyung Seo, MinWoo Kim, Yimeng Dou, Zhiwei Zhang, Yin Li, Tomy Varghese, Dean C. Barratt, Matthew J. Clarkson, Tom Vercauteren, Yipeng Hu

TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Tracker
Trackerless freehand ultrasound reconstruction aims to reconstruct 3D volumes from sequences of 2D ultrasound images without relying on external tracking systems, offering a low-cost, portable, and widely deployable alternative for volumetric imaging. However, it presents significant challenges, including accurate inter-frame motion estimation, minimisation of drift accumulation over long sequences, and generalisability across scanning protocols. The TUS-REC2024 Challenge was established to ben…

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions
Licai Sun, Xingxun Jiang, Haoyu Chen, Yante Li, Zheng Lian, Biu Liu, Yuan Zong, Wenming Zheng, Jukka M. Lepp\"anen, Guoying Zhao
https://arxiv.org/abs/2507.21015

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions
Current facial emotion recognition systems are predominately trained to predict a fixed set of predefined categories or abstract dimensional values. This constrained form of supervision hinders generalization and applicability, as it reduces the rich and nuanced spectrum of emotions into oversimplified labels or scales. In contrast, natural language provides a more flexible, expressive, and interpretable way to represent emotions, offering a much broader source of supervision. Yet, leveraging s…

This https://arxiv.org/abs/2408.09955 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMA_…

MegaAgent: A Large-Scale Autonomous LLM-based Multi-Agent System Without Predefined SOPs
LLM-based multi-agent systems (MAS) have shown promise in tackling complex tasks. However, existing solutions often suffer from limited agent coordination and heavy reliance on predefined Standard Operating Procedures (SOPs), which demand extensive human input. To address these limitations, we propose MegaAgent, a large-scale autonomous LLM-based multi-agent system. MegaAgent generates agents based on task complexity and enables dynamic task decomposition, parallel execution, efficient communic…

Deep reinforcement learning for efficient exploration of combinatorial structural design spaces
Chloe S. H. Hong, Keith J. Lee, Caitlin T. Mueller
https://arxiv.org/abs/2507.22804

Deep reinforcement learning for efficient exploration of combinatorial structural design spaces
This paper proposes a reinforcement learning framework for performance-driven structural design that combines bottom-up design generation with learned strategies to efficiently search large combinatorial design spaces. Motivated by the limitations of conventional top-down approaches such as optimization, the framework instead models structures as compositions of predefined elements, aligning form finding with practical constraints like constructability and component reuse. With the formulation …

This https://arxiv.org/abs/2501.05440 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Enabling GPU Portability into the Numba-JITed Monte Carlo Particle Transport Code MC/DC
The Center for Exascale Monte Carlo Neutron Transport is developing Monte Carlo / Dynamic Code (MC/DC) as a portable Monte Carlo neutron transport package for rapid numerical methods exploration on CPU- and GPU-based high-performance computers. In this paper, we describe MC/DC's current event-based GPU algorithm as well as the just-in-time (JIT) compilation scheme we use to enable GPU operability on Nvidia and AMD GPUs from MC/DC's Python source. To analyze performance, we conduct runtime tests…

Global Descent Method for Non-convex Multi-objective Optimization Problems
Bikram Adhikary, Md Abu Talhamainuddin Ansary, Savin Treanta
https://arxiv.org/abs/2507.22390 https://…

Global Descent Method for Non-convex Multi-objective Optimization Problems
In this paper, we develop a global descent method for non-convex multi-objective optimization problems. The proposed approach builds upon foundational concepts from single-objective global descent techniques while removing the need for predefined scalars or ordering information of objective functions. Initially, the proposed method identifies a local weak efficient solution using any suitable descent algorithm, then applies an auxiliary function termed the multi-objective global descent functio…

That shithead Palmer Luckey is considering making fully US-made laptops and wants to know if people would spend 20% more for an American made laptop. Sure, Palmer. But not for your racist ass. I'd never give you a cent https…

Palmer Luckey considering entering laptop market with fully US-made model, wants to know if you'd spend 20% more for an American-made PC
It seems Luckey's military technology startup is considering a product slightly different from its current portfolio.

ReXGroundingCT: A 3D Chest CT Dataset for Segmentation of Findings from Free-Text Reports
Mohammed Baharoon, Luyang Luo, Michael Moritz, Abhinav Kumar, Sung Eun Kim, Xiaoman Zhang, Miao Zhu, Mahmoud Hussain Alabbad, Maha Sbayel Alhazmi, Neel P. Mistry, Kent Ryan Kleinschmidt, Brady Chrisler, Sathvik Suryadevara, Sri Sai Dinesh Jaliparthi, Noah Michael Prudlo, Mark David Marino, Jeremy Palacio, Rithvik Akula, Hong-Yu Zhou, Ibrahim Ethem Hamamci, Scott J. Adams, Hassan Rayhan AlOmaish, P…

ReXGroundingCT: A 3D Chest CT Dataset for Segmentation of Findings from Free-Text Reports
We present ReXGroundingCT, the first publicly available dataset to link free-text radiology findings with pixel-level segmentations in 3D chest CT scans that is manually annotated. While prior datasets have relied on structured labels or predefined categories, ReXGroundingCT captures the full expressiveness of clinical language represented in free text and grounds it to spatially localized 3D segmentation annotations in volumetric imaging. This addresses a critical gap in medical AI: the abilit…