Tootfinder

Chili och apelsin fungerar mycket bra ihop med bacon, överväg att göra två per person. Det är inte alls omöjligt att det går åt:
Lägg minutfiléer med skinnsidan nedåt. Krydda med chiliflakes, grillkrydda, svartpeppar och salt.
1 apelsinklyfta på smalaste änden. Rulla ihop till en tjock rulle. Ta flera remsor bacon och linda runt.
Hetta upp en stekpanna med smör i. Bryn rullarna runt om och flytta över dem till en ugnsfast form.
Låt rullarna gå färdigt i 200°C ugn i cirka…

CALL FOR APPLICATIONS | 21st Singapore Graduate Forum on Southeast Asian Studies #acrel https://networks.h-net.org/group/announcem…

CALL FOR APPLICATIONS | 21st Singapore Graduate Forum on Southeast Asian Studies
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FailSafe: Reasoning and Recovery from Failures in Vision-Language-Action Models
Zijun Lin, Jiafei Duan, Haoquan Fang, Dieter Fox, Ranjay Krishna, Cheston Tan, Bihan Wen
https://arxiv.org/abs/2510.01642

FailSafe: Reasoning and Recovery from Failures in Vision-Language-Action Models
Recent advances in robotic manipulation have integrated low-level robotic control into Vision-Language Models (VLMs), extending them into Vision-Language-Action (VLA) models. Although state-of-the-art VLAs achieve strong performance in downstream robotic applications, supported by large-scale crowd-sourced robot training data, they still inevitably encounter failures during execution. Enabling robots to reason about and recover from unpredictable and abrupt failures remains a critical challenge…

The LCLStream Ecosystem for Multi-Institutional Dataset Exploration
David Rogers, Valerio Mariani, Cong Wang, Ryan Coffee, Wilko Kroeger, Murali Shankar, Hans Thorsten Schwander, Tom Beck, Fr\'ed\'eric Poitevin, Jana Thayer
https://arxiv.org/abs/2510.04012

The LCLStream Ecosystem for Multi-Institutional Dataset Exploration
We describe a new end-to-end experimental data streaming framework designed from the ground up to support new types of applications -- AI training, extremely high-rate X-ray time-of-flight analysis, crystal structure determination with distributed processing, and custom data science applications and visualizers yet to be created. Throughout, we use design choices merging cloud microservices with traditional HPC batch execution models for security and flexibility. This project makes a unique con…

\mu DeepIQA: deep learning-based fast and robust image quality assessment with local predictions for optical microscopy
Elena Corbetta, Thomas Bocklitz
https://arxiv.org/abs/2510.04859

μDeepIQA: deep learning-based fast and robust image quality assessment with local predictions for optical microscopy
Optical microscopy is one of the most widely used techniques in research studies for life sciences and biomedicine. These applications require reliable experimental pipelines to extract valuable knowledge from the measured samples and must be supported by image quality assessment (IQA) to ensure correct processing and analysis of the image data. IQA methods are implemented with variable complexity. However, while most quality metrics have a straightforward implementation, they might be time con…

Convolution and Graph-based Deep Learning Approaches for Gamma/Hadron Separation in Imaging Atmospheric Cherenkov Telescopes
Abhay Mehta, Dan Parsons, Tim Lukas Holch, David Berge, Matthias Weidlich
https://arxiv.org/abs/2510.05736

Convolution and Graph-based Deep Learning Approaches for Gamma/Hadron Separation in Imaging Atmospheric Cherenkov Telescopes
The identification of $γ$-rays from the predominant hadronic-background is a key aspect in their ground-based detection using Imaging Atmospheric Cherenkov Telescopes (IACTs). While current methods are limited in their ability to exploit correlations in complex data, deep learning-based models offer a promising alternative by directly leveraging image-level information. However, several challenges involving the robustness and applicability of such models remain. Designing model architectures w…

CALL FOR APPLICATIONS | 21st Singapore Graduate Forum on Southeast Asian Studies
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An HPC-Inspired Blueprint for a Technology-Agnostic Quantum Middle Layer
Stefano Markidis, Gilbert Netzer, Luca Pennati, Ivy Peng
https://arxiv.org/abs/2510.07079 https://

An HPC-Inspired Blueprint for a Technology-Agnostic Quantum Middle Layer
We present a blueprint for a quantum middle layer that supports applications across various quantum technologies. Inspired by concepts and abstractions from HPC libraries and middleware, our design is backend-neutral and context-aware. A program only needs to specify its intent once as typed data and operator descriptors. It declares what the quantum registers mean and which logical transformations are required, without committing to gates, pulses, continuous-variable routines, or anneal backen…

CALL FOR APPLICATIONS | 21st Singapore Graduate Forum on Southeast Asian Studies
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via Input 4 RELCFP https://