Tootfinder

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/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.

from my link log —
Parsing protobuf like never before.
https://mcyoung.xyz/2025/07/16/hyperpb/
saved 2025-07-24 https://

Swedish television is broadcasting live from Budapest Pride.
https://www.svtplay.se/video/ed66A3X/svt-nyheter-direkt/pride-rekordmanga-trotsar-forbudet

SVT Nyheter Direkt – Pride - rekordmånga trotsar förbudet
Ungerns premiärminister har infört ett nytt förbud mot dagens Prideparad i Budapest. Trots risken för höga böter väntas rekordmånga delta. SVTs utsända rapporterar från paraden.

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…

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…

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…

Building crypto portfolios with agentic AI
Antonino Castelli, Paolo Giudici, Alessandro Piergallini
https://arxiv.org/abs/2507.20468 https://arxiv.org/pdf/…

Building crypto portfolios with agentic AI
The rapid growth of crypto markets has opened new opportunities for investors, but at the same time exposed them to high volatility. To address the challenge of managing dynamic portfolios in such an environment, this paper presents a practical application of a multi-agent system designed to autonomously construct and evaluate crypto-asset allocations. Using data on daily frequencies of the ten most capitalized cryptocurrencies from 2020 to 2025, we compare two automated investment strategies. …

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…

Dependency Network-Based Portfolio Design with Forecasting and VaR Constraints
Zihan Lin, Haojie Liu, Randall R. Rojas
https://arxiv.org/abs/2507.20039 https://

Dependency Network-Based Portfolio Design with Forecasting and VaR Constraints
This study proposes a novel portfolio optimization framework that integrates statistical social network analysis with time series forecasting and risk management. Using daily stock data from the S&P 500 (2020-2024), we construct dependency networks via Vector Autoregression (VAR) and Forecast Error Variance Decomposition (FEVD), transforming influence relationships into a cost-based network. Specifically, FEVD breaks down the VAR's forecast error variance to quantify how much each stock's shock…