Tootfinder

Early Emission from Double Detonation Type Ia Supernovae
Anthony L. Piro, Ehud Nakar
https://arxiv.org/abs/2507.14290 https://arxiv.o…

Early Emission from Double Detonation Type Ia Supernovae
A popular model for Type Ia supernovae (SNe Ia) is the detonation of a CO white dwarf (WD) that is triggered by the prior detonation of a thin surface layer of helium, known as a double detonation (DD). We explore the unique early electromagnetic signatures that are expected from collision of the CO detonation with the He detonation. The three features are (1) a shock breakout flash, (2) a stage of planar shock breakout cooling, and finally (3) shock cooling emission from the thermal energy rel…

Arrested phase separation and chiral symmetry breaking in active dumbbells under shear
Lucio Mauro Carenza, Giuseppe Negro, Pasquale Digregorio, Antonio Suma, Giuseppe Gonnella
https://arxiv.org/abs/2509.17229

Arrested phase separation and chiral symmetry breaking in active dumbbells under shear
Through molecular dynamics simulations, we investigate the phase separation and aggregation dynamics of active dumbbell particles in two-dimensions subjected to shear. We find that the growth of the phase-separated region is arrested when shear is applied, with the average clusters size plateauing towards a value $R_s$ that remains constant over time. While activity enhances the resilience of clusters against shear-induced breakup, $R_s$ decreases with growing shear rate $\dotγ$, with an int…

MS-CLR: Multi-Skeleton Contrastive Learning for Human Action Recognition
Mert Kiray, Alvaro Ritter, Nassir Navab, Benjamin Busam
https://arxiv.org/abs/2508.14889 https://…

MS-CLR: Multi-Skeleton Contrastive Learning for Human Action Recognition
Contrastive learning has gained significant attention in skeleton-based action recognition for its ability to learn robust representations from unlabeled data. However, existing methods rely on a single skeleton convention, which limits their ability to generalize across datasets with diverse joint structures and anatomical coverage. We propose Multi-Skeleton Contrastive Learning (MS-CLR), a general self-supervised framework that aligns pose representations across multiple skeleton conventions …

People talk about how politics shouldn't be like sports. I think it depends a lot on what sports though.
Like, imagine if politicians had to wear the logos of every company they worked stock in and every company that donated to their campaigns like they're driving NASCAR. Of all sports, almost no one wants anything to be more like NASCAR... And yet, when you think about it, there actually *are* some hints we could take from it.
#USPol

Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
Alejandro Hern\'andez-Cano, Alexander H\"agele, Allen Hao Huang, Angelika Romanou, Antoni-Joan Solergibert, Barna Pasztor, Bettina Messmer, Dhia Garbaya, Eduard Frank \v{D}urech, Ido Hakimi, Juan Garc\'ia Giraldo, Mete Ismayilzada, Negar Foroutan, Skander Moalla, Tiancheng Chen, Vinko Sabol\v{c}ec, Yixuan Xu, Michael Aerni, Badr AlKhamissi, Ines Altemir Marinas, Mohammad Hossein Amani, Matin An…

Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
We present Apertus, a fully open suite of large language models (LLMs) designed to address two systemic shortcomings in today's open model ecosystem: data compliance and multilingual representation. Unlike many prior models that release weights without reproducible data pipelines or regard for content-owner rights, Apertus models are pretrained exclusively on openly available data, retroactively respecting robots.txt exclusions and filtering for non-permissive, toxic, and personally identifiabl…

GitChameleon: Evaluating AI Code Generation Against Python Library Version Incompatibilities
Diganta Misra, Nizar Islah, Victor May, Brice Rauby, Zihan Wang, Justine Gehring, Antonio Orvieto, Muawiz Chaudhary, Eilif B. Muller, Irina Rish, Samira Ebrahimi Kahou, Massimo Caccia
https://arxiv.org/abs/2507.12367

GitChameleon: Evaluating AI Code Generation Against Python Library Version Incompatibilities
The rapid evolution of software libraries poses a considerable hurdle for code generation, necessitating continuous adaptation to frequent version updates while preserving backward compatibility. While existing code evolution benchmarks provide valuable insights, they typically lack execution-based evaluation for generating code compliant with specific library versions. To address this, we introduce GitChameleon, a novel, meticulously curated dataset comprising 328 Python code completion proble…

Facts look different in different contexts...
Nigeria, Libya, Caspian Sea, and other oil patches in impoverished places are effectively without the concept of environmental regulation. They flare whatever wherever they want. In Nigeria the rampant theft of unrefined oil and "fire pit refining" is beyond anything done by regulated refiners in TX.
Not that we want to emulate Nigeria or Azerbaijan or Libya...

Af en eller anden årsag kom jeg lige i tanke om de Castus frugtstænger som jeg sidst spiste for ~20 år siden.
Hold kæft hvor kunne jeg godt spise sådan en lige nu.
#DanskerTrut

On the Men's Long Hair Hyperboard, Jesus met Anthony and discussed shipbuilding!!
http://www.mlhh.org/

CLAPS: A CLIP-Unified Auto-Prompt Segmentation for Multi-Modal Retinal Imaging
Zhihao Zhao, Yinzheng Zhao, Junjie Yang, Xiangtong Yao, Quanmin Liang, Shahrooz Faghihroohi, Kai Huang, Nassir Navab, M. Ali Nasseri
https://arxiv.org/abs/2509.08618

CLAPS: A CLIP-Unified Auto-Prompt Segmentation for Multi-Modal Retinal Imaging
Recent advancements in foundation models, such as the Segment Anything Model (SAM), have significantly impacted medical image segmentation, especially in retinal imaging, where precise segmentation is vital for diagnosis. Despite this progress, current methods face critical challenges: 1) modality ambiguity in textual disease descriptions, 2) a continued reliance on manual prompting for SAM-based workflows, and 3) a lack of a unified framework, with most methods being modality- and task-specifi…