Tootfinder

Några tänkvärda poänger av Guillou, särskilt det där med ammunitionen. https://www.aftonbladet.se/nyheter/kolumnister/a/EyrW8G/polisen-i-orebro-ville-ha-ett-opolitiskt-massmord

Polisen i Örebro ville ha ett opolitiskt massmord
Utredningen av Rickard Anderssons, 35, massmord på Campus Risbergska i Örebro är klar. Den kan därmed läggas till handlingarna och glömskan med polisens diffusa

🇺🇦 #NowPlaying on KEXP's #MiddayShow
Adamski:
🎵 Killer (Radio Edit)
#Adamski
https://opaledit.bandcamp.com/track/adamski-killer-opal-remix
https://open.spotify.com/track/5jhDeobWatA1XAHWKOWPh2

🇺🇦 Auf radioeins läuft...
Bruce Springsteen:
🎵 Streets Of Philadelphia
#NowPlaying #BruceSpringsteen
https://opaledit.bandcamp.com/track/bruce-springsteen-streets-of-philadelphia-opal-fx-remix
https://open.spotify.com/track/6WgBIPHwkQhCqMNnR5hQCN

LOMS.cz: A computational platform for high-throughput Classical and Combinatorial Judd-Ofelt analysis and rare-earth spectroscopy
Jan Hrabovsk\'y, Petr Va\v{r}\'ak, Robin Kry\v{s}t\r{u}fek
https://arxiv.org/abs/2507.01218

LOMS.cz: A computational platform for high-throughput Classical and Combinatorial Judd-Ofelt analysis and rare-earth spectroscopy
We present LOMS.cz (Luminescence, Optical and Magneto-optical Software), an open-source computational platform that addresses the long-standing challenge of standardizing Judd-Ofelt (JO) calculations in rare-earth spectroscopy. Despite JO theory's six-decade history as the fundamental framework for understanding $4f\leftrightarrow4f$ transitions, the field lacks standardized computational methodologies for precise and reproducible parameter determination. LOMS integrates three key innovations: …

Replaced article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- To Offload or Not To Offload: Model-driven Comparison of Edge-native and On-device Processing
Nathan Ng, David Irwin, Ananthram Swami, Don Towsley, Prashant Shenoy

Robust Task Offloading for UAV-enabled Secure MEC Against Aerial Eavesdropper
Can Cui, ZIye Jia, Chao Dong, Qihui Wu
https://arxiv.org/abs/2507.00710 https…

Robust Task Offloading for UAV-enabled Secure MEC Against Aerial Eavesdropper
Unmanned aerial vehicles (UAVs) are recognized as a promising candidate for the multi-access edge computing (MEC) in the future sixth generation communication networks. However, the aerial eavesdropping UAVs (EUAVs) pose a significant security threat to the data offloading. In this paper, we investigate a robust MEC scenario with multiple service UAVs (SUAVs) towards the potential eavesdropping from the EUAV, in which the random parameters such as task complexities are considered in the practic…

Linux 6.16: Entspannt zu mehr Leistung
Linux 6.16 steht im Zeichen der Optimierung und Leistungssteigerung. USB Audio Offloading, Intel TDX und einige weitere Features liefert der Kernel aber auch.
https://www.

DIY-MKG: An LLM-Based Polyglot Language Learning System
Kenan Tang, Yanhong Li, Yao Qin
https://arxiv.org/abs/2507.01872 https://arxi…

DIY-MKG: An LLM-Based Polyglot Language Learning System
Existing language learning tools, even those powered by Large Language Models (LLMs), often lack support for polyglot learners to build linguistic connections across vocabularies in multiple languages, provide limited customization for individual learning paces or needs, and suffer from detrimental cognitive offloading. To address these limitations, we design Do-It-Yourself Multilingual Knowledge Graph (DIY-MKG), an open-source system that supports polyglot language learning. DIY-MKG allows the…

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Strafe:
🎵 Set It Off
#Strafe
https://opaledit.bandcamp.com/track/strafe-set-it-off-opal-edit
https://open.spotify.com/track/1AWdTY4hPU1U5q5ceJ26yg

This https://arxiv.org/abs/2407.00066 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
Fine-tuning large language models (LLMs) with low-rank adaptations (LoRAs) has become common practice, often yielding numerous copies of the same LLM differing only in their LoRA updates. This paradigm presents challenges for systems that serve real-time responses to queries that each involve a different LoRA. Prior works optimize the design of such systems but still require continuous loading and offloading of LoRAs, as it is infeasible to store thousands of LoRAs in GPU memory. To mitigate th…