Tootfinder

A look at the Chile-led Latam-GPT project, which involves 30 Latin American and Caribbean institutions collaborating to release an open-source LLM in September (Cristišn Vera-Cruz/Rest of World)
https://restofworld.org/2025/chatgpt-latin-america-alternative-latamgpt…

Fed up with ChatGPT, Latin America is building its own
Dozens of organizations in the region have partnered to develop a large language model that better understands Latin America’s cultural and linguistic nuances.

Data Movement Model for the Vera C. Rubin Observatory
Fabio Hernandez (CC-IN2P3/CNRS), Mark G. Beckett (Institute for Astronomy, University of Edinburgh), Andrew Hanushevsky (SLAC National Accelerator Laboratory), Tim Jenness (Vera C. Rubin Observatory Project Office), Kian-Tat Lim (SLAC National Accelerator Laboratory), Peter Love (Lancaster University), Timothy Noble (Rutherford Appleton Laboratory, Science and Technology Facilities Council), Stephen R. Pietrowicz (National Center fo…

Data Movement Model for the Vera C. Rubin Observatory
The sky images captured nightly by the camera on the Vera C. Rubin Observatory's telescope will be processed across facilities on three continents. Data acquisition will occur at the observatory's location on Cerro Pachón in the Andes mountains of Chile. A first copy of the raw image data set is stored at the summit and immediately transmitted via dedicated network links to the archive center within the US Data Facility at SLAC National Accelerator Laboratory in California, USA and from there …

RiemannLoRA: A Unified Riemannian Framework for Ambiguity-Free LoRA Optimization
Vladimir Bogachev, Vladimir Aletov, Alexander Molozhavenko, Denis Bobkov, Vera Soboleva, Aibek Alanov, Maxim Rakhuba
https://arxiv.org/abs/2507.12142

RiemannLoRA: A Unified Riemannian Framework for Ambiguity-Free LoRA Optimization
Low-Rank Adaptation (LoRA) has become a widely adopted standard for parameter-efficient fine-tuning of large language models (LLMs), significantly reducing memory and computational demands. However, challenges remain, including finding optimal initialization strategies or mitigating overparametrization in low-rank matrix factorization. In this work, we propose a novel approach that addresses both of the challenges simultaneously within a unified framework. Our method treats a set of fixed-rank …

First critical field in the pinned three dimensional Ginzburg-Landau model of superconductivity
Mat\'ias D\'iaz-Vera, Carlos Rom\'an
https://arxiv.org/abs/2507.10915

First critical field in the pinned three dimensional Ginzburg-Landau model of superconductivity
We study extreme type-II superconductors described by the three dimensional magnetic Ginzburg-Landau functional incorporating a pinning term $a_\varepsilon(x)$, which we assume to be a bounded measurable function satisfying $b\leq a_\varepsilon(x)\leq 1$ for some constant $b>0$. A hallmark of such materials is the formation of vortex filaments, which emerge when the applied magnetic field exceeds the first critical field $H_{c_1}$. In this work, we provide a lower bound for this critical field …

Homothetic expansion of polyhedra in the two-vertex model: emergence of FLRW
I\~naki Garay, Sergio Rodr\'iguez-Gonz\'alez, Ra\"ul Vera
https://arxiv.org/abs/2507.06951

Homothetic expansion of polyhedra in the two-vertex model: emergence of FLRW
The cosmological behavior associated to a U(N)-symmetry reduced sector of the loop-quantum-gravity truncation known as the two-vertex model is further explored in this work. We construct convenient frame bases that encode the whole classical phase space of the twisted geometry associated to the graph. We show that the polyhedra of the twisted geometry suffer under evolution an homothetic expansion, which strengthens the correspondence to the Robertson-Walker geometry.

Regression modeling for cure factors on uterine cancer data using the reparametrized defective generalized Gompertz distribution
Dionisio Silva Neto, Francisco Louzada Neto, Vera Lucia Tomazella
https://arxiv.org/abs/2507.10902

Regression modeling for cure factors on uterine cancer data using the reparametrized defective generalized Gompertz distribution
Recent advances in medical research have improved survival outcomes for patients with life-threatening diseases. As a result, the existence of long-term survivors from these illnesses is becoming common. However, conventional models in survival analysis assume that all individuals remain at risk of death after the follow-up, disregarding the presence of a cured subpopulation. An important methodological advancement in this context is the use of defective distributions. In the defective models, …

Tug-of-war between idiom's figurative and literal meanings in LLMs
Soyoung Oh, Xinting Huang, Mathis Pink, Michael Hahn, Vera Demberg
https://arxiv.org/abs/2506.01723

Tug-of-war between idiom's figurative and literal meanings in LLMs
Idioms present a unique challenge for language models due to their non-compositional figurative meanings, which often strongly diverge from the idiom's literal interpretation. This duality requires a model to learn representing and deciding between the two meanings to interpret an idiom in a figurative sense, or literally. In this paper, we employ tools from mechanistic interpretability to trace how a large pretrained causal transformer (LLama3.2-1B-base) deals with this ambiguity. We localize …

Embedding-based Retrieval in Multimodal Content Moderation
Hanzhong Liang, Jinghao Shi, Xiang Shen, Zixuan Wang, Vera Wen, Ardalan Mehrani, Zhiqian Chen, Yifan Wu, Zhixin Zhang
https://arxiv.org/abs/2507.01066

Embedding-based Retrieval in Multimodal Content Moderation
Video understanding plays a fundamental role for content moderation on short video platforms, enabling the detection of inappropriate content. While classification remains the dominant approach for content moderation, it often struggles in scenarios requiring rapid and cost-efficient responses, such as trend adaptation and urgent escalations. To address this issue, we introduce an Embedding-Based Retrieval (EBR) method designed to complement traditional classification approaches. We first lever…

Chromatic activity window of periodic FRBs: FRB 20121102A and FRB 20180916B
M. C. Espinoza-Dupouy, M. Cruces, T. Cassanelli, C. A. Braga, E. Berm\'udez, J. Vera-Casanova
https://arxiv.org/abs/2507.04609

Chromatic activity window of periodic FRBs: FRB 20121102A and FRB 20180916B
Two fast radio bursts, FRB 20121102A and FRB 20180916B, show periodic activity with cycles of 159.3 and 16.33 days, respectively. These cycles consist of active and inactive windows, with peak activity centered within the active phase. For FRB 20180916B, studies have reported a frequency-dependent-or ``chromatic''-behaviour, where the activity window starts earlier and becomes narrower at higher frequencies. The activity across frequencies is typically modeled with a power law. In this work, we…

Analyzing Line-of-sight selection biases in galaxy-scale strong lensing with external convergence and shear
Xianzhe TZ Tang, Simon Birrer, Anowar J. Shajib, Narayan Khadka, the LSST Strong Gravitational Lensing Science Collaboration, the LSST Dark Energy Science Collaboration
https://arxiv.org/abs/2506.04201

Analyzing Line-of-sight selection biases in galaxy-scale strong lensing with external convergence and shear
The upcoming Vera Rubin Observatory Legacy Survey of Space and Time (LSST) will dramatically increase the number of strong gravitational lensing systems, requiring precise modeling of line-of-sight (LOS) effects to mitigate biases in lensing observations and cosmological inferences. We develop a method to construct joint distributions of external convergence ($κ_{\mathrm{ext}}$) and shear ($γ_{\mathrm{ext}}$) for strong lensing LOS by aggregating large-scale structure simulations with high-re…