Tootfinder

Here’s the real actual definition of “artificial intelligence,” the true technical meaning in research and engineering circles when it’s not being used as marketing hype.
Artificial intelligence is anything that
1. humans are generally good at, and
2. computers were recently bad at.
That’s it. That’s all it means. You’ll hear people refine it and dress it up, but that’s the heart of the definition. (Check Wikipedia!)
3/

trec_web: TREC WT10g (2003)
A web graph network originally constructed in 2003 as a testbed for information-retrieval techniques, including web search engines. Distributed by University of Glasgow.
This network has 1601787 nodes and 8063026 edges.
Tags: Informational, Web graph, Unweighted
https://networks.skewed.de/net…

Optical Emission-Line Properties of eROSITA-selected SDSS-V Galaxies
Nadiia G. Pulatova, Evgenii Rubtsov, Igor V. Chilingarian, Hans-Walter Rix, Mariia Demianenko, Kirill A. Grishin, Ivan Yu. Katkov, Donald P. Schneider, Catarina Aydar, Johannes Buchner, Mara Salvato, Andrea Merloni, Anton M. Koekemoer, Roberto J. Assef, Claudio Ricci, Dominika Wylezalek, Damir Gasymov, William Nielsen Brandt, Castalia Alenka Negrete Pe\~naloza, Sean Morrison, Scott F. Anderson, Franz E. Bauer, Hector …

Optical Emission-Line Properties of eROSITA-selected SDSS-V Galaxies
We present and discuss optical emission line properties obtained from the analysis of Sloan Digital Sky Survey (SDSS) spectra for an X-ray selected sample of 3684 galaxies (0.002 < z < 0.55), drawn from the eRASS1 catalog. We modeled SDSS-V DR19 spectra using the NBursts full spectrum fitting technique with E-MILES simple stellar populations (SSP) models and emission line templates to decompose broad and narrow emission line components for correlation with X-ray properties. We place the galaxie…

TPDE: A Fast Adaptable Compiler Back-End Framework
Tobias Schwarz (Technical University of Munich), Tobias Kamm (Technical University of Munich), Alexis Engelke (Technical University of Munich)
https://arxiv.org/abs/2505.22610

TPDE: A Fast Adaptable Compiler Back-End Framework
Fast machine code generation is especially important for fast start-up just-in-time compilation, where the compilation time is part of the end-to-end latency. However, widely used compiler frameworks like LLVM do not prioritize fast compilation and require an extra IR translation step increasing latency even further; and rolling a custom code generator is a substantial engineering effort, especially when targeting multiple architectures. Therefore, in this paper, we present TPDE, a compiler b…

Here’s the real actual definition of “artificial intelligence,” the true technical meaning in research and engineering circles when it’s not being used as marketing hype.
Artificial intelligence is anything that
1. humans are generally good at, and
2. computers were recently bad at.
That’s it. That’s all it means. You’ll hear people refine it and dress it up, but that’s the heart of the definition. (Check Wikipedia!)
3/

This https://arxiv.org/abs/2411.04869 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Modelling of the atomic lines' emission of fast moving pulsar nebulae
Bow shocks generated by pulsars moving through weakly ionized interstellar medium (ISM) produce emission dominated by non-equilibrium atomic transitions. These bow shocks are primarily observed as H$_α$ nebulae. We developed a package, named Shu, that calculates non-LTE intensity maps in more than 150 spectral lines, taking into account geometrical properties of the pulsars' motion and lines of sight. We argue here that atomic (CI, NI, OI) and ionic (SII, NII, OIII, NeIV) transitions can be us…

OpenAI is expanding its consulting-like service to refine its models and build bespoke apps for large enterprise and government clients spending at least $10M (The Information)
https://www.theinformation.com/articles/openai-takes-page…

OpenAI Takes a Page From Palantir, Doubles Down on Consulting Services
As OpenAI pitches its artificial intelligence to big companies and government agencies, it’s taking a page from the playbook of many software firms by offeringin-house researchers and software engineers to customize AI for customers. OpenAI is adding staff and resources for a consulting-like ...

Advanced System Engineering Approaches to Emerging Challenges in Planetary and Deep-Space Exploration
J. de Curt\`o, Cristina LiCalzi, Julien Tubiana Warin, Jack Gehlert, Brian Langbein, Alexandre Gamboa, Chris Sixbey, William Maguire, Santiago Fern\'andez, \'Alvaro Maestroarena, Alex Brenchley, Logan Maroclo, Philemon Mercado, Joshua DeJohn, Cesar Velez, Ethan Dahmus, Taylor Steinys, David Fritz, I. de Zarz\`a

Advanced System Engineering Approaches to Emerging Challenges in Planetary and Deep-Space Exploration
This paper presents innovative solutions to critical challenges in planetary and deep-space exploration electronics. We synthesize findings across diverse mission profiles, highlighting advances in: (1) MARTIAN positioning systems with dual-frequency transmission to achieve $\pm$1m horizontal accuracy; (2) artificial reef platforms for Titan's hydrocarbon seas utilizing specialized sensor arrays and multi-stage communication chains; (3) precision orbital rendezvous techniques demonstrating nove…

Feature Engineering for Wireless Communications and Networking: Concepts, Methodologies, and Applications
Jiacheng Wang, Changyuan Zhao, Zehui Xiong, Tao Xiang, Dusit Niyato, Xianbin Wang, Shiwen Mao, Dong In Kim
https://arxiv.org/abs/2507.19837

Feature Engineering for Wireless Communications and Networking: Concepts, Methodologies, and Applications
AI-enabled wireless communications have attracted tremendous research interest in recent years, particularly with the rise of novel paradigms such as low-altitude integrated sensing and communication (ISAC) networks. Within these systems, feature engineering plays a pivotal role by transforming raw wireless data into structured representations suitable for AI models. Hence, this paper offers a comprehensive investigation of feature engineering techniques in AI-driven wireless communications. Sp…

trec_web: TREC WT10g (2003)
A web graph network originally constructed in 2003 as a testbed for information-retrieval techniques, including web search engines. Distributed by University of Glasgow.
This network has 1601787 nodes and 8063026 edges.
Tags: Informational, Web graph, Unweighted
https://networks.skewed.de/net…