Tootfinder

Tags are sets. Many apps support tagging of content, but most of them (incl. Mastodon) treat tags only as singular/isolated topic filters, akin to a flat folder-based approach. But tagging can be so, so much more powerful when treating tags as sets and offering users the possibility to combine and query tagged content as sets (think Venn diagrams), i.e. allowing tags to be combined using AND/OR/NOT aka intersection/union/difference operations...
Below is a simple query engine to do jus…

visualizeus: vi.sualize.us picture tagging network
Three bipartite networks of tag-picture, user-picture, and user-tag linkages that represent the folksonomy of the picture tagging network of vi.sualize.us. The date of this snapshot is uncertain.
This network has 577437 nodes and 2298816 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph

Crossing Domains without Labels: Distant Supervision for Term Extraction
Elena Senger, Yuri Campbell, Rob van der Goot, Barbara Plank
https://arxiv.org/abs/2510.06838 https://…

Crossing Domains without Labels: Distant Supervision for Term Extraction
Automatic Term Extraction (ATE) is a critical component in downstream NLP tasks such as document tagging, ontology construction and patent analysis. Current state-of-the-art methods require expensive human annotation and struggle with domain transfer, limiting their practical deployment. This highlights the need for more robust, scalable solutions and realistic evaluation settings. To address this, we introduce a comprehensive benchmark spanning seven diverse domains, enabling performance evalu…

Tim Sweeney says it "makes no sense" for stores like Steam to label games that are made using AI, since AI "will be involved in nearly all future production" (Alex Forbes-Calvin/GamesIndustry.biz)
https://www.gamesindustry.biz/epics-sweene

Epic's Sweeney says platforms should stop tagging games made with AI
The CEO of Epic Games, Tim Sweeney, has argued that platforms like Steam should not label games that are made using AI.

visualizeus: vi.sualize.us picture tagging network
Three bipartite networks of tag-picture, user-picture, and user-tag linkages that represent the folksonomy of the picture tagging network of vi.sualize.us. The date of this snapshot is uncertain.
This network has 577437 nodes and 2298816 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph

from my link log —
ARM Memory Tagging: how it improves C/C memory safety.
https://llvm.org/devmtg/2018-10/slides/Serebryany-Stepanov-Tsyrklevich-Memory-Tagging-Slides-LLVM-2018.pdf
saved 2019-01-07

Model-Based Ranking of Source Languages for Zero-Shot Cross-Lingual Transfer
Abteen Ebrahimi, Adam Wiemerslage, Katharina von der Wense
https://arxiv.org/abs/2510.03202 https://…

Model-Based Ranking of Source Languages for Zero-Shot Cross-Lingual Transfer
We present NN-Rank, an algorithm for ranking source languages for cross-lingual transfer, which leverages hidden representations from multilingual models and unlabeled target-language data. We experiment with two pretrained multilingual models and two tasks: part-of-speech tagging (POS) and named entity recognition (NER). We consider 51 source languages and evaluate on 56 and 72 target languages for POS and NER, respectively. When using in-domain data, NN-Rank beats state-of-the-art baselines t…

After maybe a decade of "pkgbase", I doubt that the official new phrase "freebsd-base" will catch on and become more popular.
It's five syllables, plus a hyphen, which breaks tagging in (at least) Mastodon.
#pkgbase #freebsd-base

visualizeus: vi.sualize.us picture tagging network
Three bipartite networks of tag-picture, user-picture, and user-tag linkages that represent the folksonomy of the picture tagging network of vi.sualize.us. The date of this snapshot is uncertain.
This network has 577437 nodes and 2298816 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph

Seal Whisker-Inspired Sensor for Amplifying Wake-Induced Vibrations in Underwater Marine Animal Monitoring
Yuyan Wu, Sanjay Giridharan, Leixin Ma, Hae Young Noh
https://arxiv.org/abs/2510.03664

Seal Whisker-Inspired Sensor for Amplifying Wake-Induced Vibrations in Underwater Marine Animal Monitoring
Underwater marine animal monitoring is essential for assessing biodiversity, evaluating ecosystem health, and understanding the effects of offshore structures. Traditional approaches such as tagging, sonar, and camera systems are often invasive, energy-intensive, or limited by poor visibility and water turbidity. Inspired by the hydrodynamic sensing of seal whiskers, wavy whisker vibration sensors have been developed for flow velocity and angle-of-attack detection. However, most prior work has …

Deep chemical tagging - Identifying open clusters and moving groups in chemical space with graph attention networks
Lorenzo Spina, Milan Quandt Rodriguez, Laura Magrini, Leda Berni, Sara Lucatello, Marco Canducci
https://arxiv.org/abs/2509.18268

Is there some setting in #Nextcloud that would cease posting these tagging messages? As evident in the image below, while occasionally useful, most often, by a large margin, the tags are hilariously inaccurate (a tuning note A is 'rap') but as I have thousands of photos and audio files, the constant stream of these renders notifications useless,

Advancing the CMS Level-1 Trigger: Jet Tagging with DeepSets at the HL-LHC
Stella Schaefer, Christopher Brown, Duc Hoang, Sioni Summers, Sebastian Wuchterl
https://arxiv.org/abs/2509.24371

Advancing the CMS Level-1 Trigger: Jet Tagging with DeepSets at the HL-LHC
At the High Luminosity LHC, selecting important physics processes such as (di-) Higgs production will be a high priority. The Phase-2 Upgrade of the CMS Level-1 Trigger will reconstruct particle candidates and use pileup mitigation for the 200 simultaneous proton-proton interactions. A fast cone algorithm will reconstruct jets from these particles, providing access to jet constituents for the first time. We introduce a new multi-class jet tagger with a small, quantized DeepSets neural network. …

Comprehensive Evaluation of CNN-Based Audio Tagging Models on Resource-Constrained Devices
Jordi Grau-Haro, Ruben Ribes-Serrano, Javier Naranjo-Alcazar, Marta Garcia-Ballesteros, Pedro Zuccarello
https://arxiv.org/abs/2509.14049

Comprehensive Evaluation of CNN-Based Audio Tagging Models on Resource-Constrained Devices
Convolutional Neural Networks (CNNs) have demonstrated exceptional performance in audio tagging tasks. However, deploying these models on resource-constrained devices like the Raspberry Pi poses challenges related to computational efficiency and thermal management. In this paper, a comprehensive evaluation of multiple convolutional neural network (CNN) architectures for audio tagging on the Raspberry Pi is conducted, encompassing all 1D and 2D models from the Pretrained Audio Neural Networks (P…

@… I’m new to Play and I think it’s very cool! I somehow expected a way to automatically categorize videos by duration (short, medium, long) as an out-of-the box scenario.
I’m doing that now with the automatic tagging but I’d suggest that “minutes” is a more useful unit in this screen? I’m now calculating the values but would be easier to enter the minu…

visualizeus: vi.sualize.us picture tagging network
Three bipartite networks of tag-picture, user-picture, and user-tag linkages that represent the folksonomy of the picture tagging network of vi.sualize.us. The date of this snapshot is uncertain.
This network has 577437 nodes and 2298816 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph

The Pareto Frontier of Resilient Jet Tagging
Rikab Gambhir, Matt LeBlanc, Yuanchen Zhou
https://arxiv.org/abs/2509.19431 https://arxiv.org/pdf/2509.19431…

The Pareto Frontier of Resilient Jet Tagging
Classifying hadronic jets using their constituents' kinematic information is a critical task in modern high-energy collider physics. Often, classifiers are designed by targeting the best performance using metrics such as accuracy, AUC, or rejection rates. However, the use of a single metric can lead to the use of architectures that are more model-dependent than competitive alternatives, leading to potential uncertainty and bias in analysis. We explore such trade-offs and demonstrate the consequ…

visualizeus: vi.sualize.us picture tagging network
Three bipartite networks of tag-picture, user-picture, and user-tag linkages that represent the folksonomy of the picture tagging network of vi.sualize.us. The date of this snapshot is uncertain.
This network has 577437 nodes and 2298816 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph

NanoTag: Systems Support for Efficient Byte-Granular Overflow Detection on ARM MTE
Mingkai Li, Hang Ye, Joseph Devietti, Suman Jana, Tanvir Ahmed Khan
https://arxiv.org/abs/2509.22027

NanoTag: Systems Support for Efficient Byte-Granular Overflow Detection on ARM MTE
Memory safety bugs, such as buffer overflows and use-after-frees, are the leading causes of software safety issues in production. Software-based approaches, e.g., Address Sanitizer (ASAN), can detect such bugs with high precision, but with prohibitively high overhead. ARM's Memory Tagging Extension (MTE) offers a promising alternative to detect these bugs in hardware with a much lower overhead. However, in this paper, we perform a thorough investigation of Google Pixel 8, the first production i…

Region-Specific Audio Tagging for Spatial Sound
Jinzheng Zhao, Yong Xu, Haohe Liu, Davide Berghi, Xinyuan Qian, Qiuqiang Kong, Junqi Zhao, Mark D. Plumbley, Wenwu Wang
https://arxiv.org/abs/2509.09526 …

Region-Specific Audio Tagging for Spatial Sound
Audio tagging aims to label sound events appearing in an audio recording. In this paper, we propose region-specific audio tagging, a new task which labels sound events in a given region for spatial audio recorded by a microphone array. The region can be specified as an angular space or a distance from the microphone. We first study the performance of different combinations of spectral, spatial, and position features. Then we extend state-of-the-art audio tagging systems such as pre-trained audi…

I think I need to clarify some shit for (white) liberals.
How many times have you wondered if someone you're talking to in an informant sent to entrap you? How many times have you or a friend of yours been hit by a car, intentionally? How many friends have been hit, or almost hit? Ever been stabbed? Know anyone who has? Has the FBI ever knocked on a friend's door? Have police ever kicked down your door? Have you ever been arrested? Pepper sprayed? Does the sound or smell or blast balls give you flashbacks? Do you ever wonder what all the CS exposure is doing to your body? How many times have you been shot or shot at? Do you wonder every day if this is the day they'll come to kill you? Would anyone in your social circle answer these questions differently?
When you vote, you risk nothing (big asterisk, but if I'm talking to you then it doesn't apply to you). What you get out of voting is exactly what you put into it. Direct action is the same.
If you aren't worried about someone murdering you, then you probably aren't actually threatening the system. That's the difference between voting, and doing something useful. If they had to murder all the liberals in order to keep going, fascism would end. If they're only murdering radicals and marginalized people, then you're just like all the "good Germans" who hated Hitler but did essentially nothing.
It's already that bad for some people. How much are you willing to risk? How many people are you willing to sacrifice for your comfort? These are the questions we're all thinking about every time you tell us to vote.
(I'm tagging this #USPol so it's easy for folks to filter out if they're already well acquaintaned with the horror. I'm not CW, because USPol is just expected to be triggering.)

#NowPlaying this new record by Marquette, Michigan's LIQUID MIKE and this is some really solid powerpop like Superdrag or Weezer or some of the things I was listening to in the early 2000s (The Cells, the Kicks, Ash, Fountains of Wayne, etc). Maybe Cheap Trick vibes too (obviously). Some really cool, punchy, catchy stuff. Tagging a few of you.

@… I respect that, I’m aware of your opinions on parasocial relationships and the use of social media. I hope people aren’t explicitly tagging you to… I won’t even finish that though, someone probably is.
Simultaneously it can be true that there are people out there who need some sort of outlet for their frustrations, and for whatever reason, this is that place for …

Social media ‘trust’/’distrust’ buttons could reduce spread of misinformation | UCL News - UCL – University College London
@… & @… I am tagging you, although maybe you already knew hehe

visualizeus: vi.sualize.us picture tagging network
Three bipartite networks of tag-picture, user-picture, and user-tag linkages that represent the folksonomy of the picture tagging network of vi.sualize.us. The date of this snapshot is uncertain.
This network has 577437 nodes and 2298816 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph

Crosslisted article(s) found for astro-ph.SR. https://arxiv.org/list/astro-ph.SR/new
[1/1]:
- Deep chemical tagging - Identifying open clusters and moving groups in chemical space with graph ...
Lorenzo Spina, Milan Quandt Rodriguez, Laura Magrini, Leda Berni, Sara Lucatello, Marco Ca…

Electromagnetic moments of ground and excited states calculated in heavy odd-N open-shell nuclei
J. Dobaczewski, A. E. Stuchbery, G. Danneaux, A. Nagpal, P. L. Sassarini, H. Wibowo
https://arxiv.org/abs/2509.26549

Electromagnetic moments of ground and excited states calculated in heavy odd-N open-shell nuclei
Within nuclear DFT, we calculated spectroscopic magnetic dipole and electric quadrupole moments in various quasiparticle configurations of odd-$N$, even-$Z$, $83\leq{}N\leq125$ nuclei ranging from gadolinium to osmium. By tagging the blocked quasiparticles with single-particle states of semi-magic dysprosium isotope, we efficiently calculated 22 prolate and 22 oblate states in each of the 154 nuclei, and we tracked them across the entire major neutron shell. We compared this extensive set of th…

Day 19 (a bit late): Alice Oseman
As I said I've got 14 authors to fit into two days. Probably just going to extend to 30? But Oseman gets this spot as an absolute legend of queer fiction in both novel & graphic novel form, and an excellent example of the many truths queer writers have to share with non-queer people that can make everyone's lives better. Her writing is very kind, despite in many instances dealing with some dark stuff.
I started out on Heartstopper, which is just so lovely and fun to read, and then made my way through several of her novels. The one I'll highlight here which I think it's her greatest triumph is "Loveless", which is semi-autobiographical and was at least my first (but no longer only) experience with the "platonic romance" sub-genre. It not only helped me work through some crufty internal doubts about aro/ace identities that I'd never really examined, but in the process helped improve my understanding of friendship, period. Heck, it's probably a nice novel for anyone questioning any sort of identity or dealing with loneliness, and it's just super-enjoyable as a story regardless of the philosophical value.
To cheat a bit more here on my author count, I recently read "Dear Wendy" by Ann Zhao, which shouts out "Loveless" and offers a more expository exploration of aro/ace identities, but "Loveless" is a book with more heart and better writing overall, including the neat plotting and great pacing. I think there are also parallels with Becky Albertalli's work, though I think I like Oseman slightly more. Certainly both excel at writing queer romance (and romance-adjacent) stuff with happy endings (#OwnVoices wins again with all three authors).
In any case, Oseman is excellent and if you're not up for reading a novel, Heartstopper is a graphic novel series that's easy to jump into and very kind to its adorable main characters.
I think I've now decided to continue to 30, which is a relief, so I'm tagging this (and the next post that rounds out 20) two ways.
#20AuthorsNoMen
#30AuthorsNoMen

visualizeus: vi.sualize.us picture tagging network
Three bipartite networks of tag-picture, user-picture, and user-tag linkages that represent the folksonomy of the picture tagging network of vi.sualize.us. The date of this snapshot is uncertain.
This network has 577437 nodes and 2298816 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph

TrackCore-F: Deploying Transformer-Based Subatomic Particle Tracking on FPGAs
Arjan Blankestijn, Uraz Odyurt, Amirreza Yousefzadeh
https://arxiv.org/abs/2509.26335 https://

TrackCore-F: Deploying Transformer-Based Subatomic Particle Tracking on FPGAs
The Transformer Machine Learning (ML) architecture has been gaining considerable momentum in recent years. In particular, computational High-Energy Physics tasks such as jet tagging and particle track reconstruction (tracking), have either achieved proper solutions, or reached considerable milestones using Transformers. On the other hand, the use of specialised hardware accelerators, especially FPGAs, is an effective method to achieve online, or pseudo-online latencies. The development and inte…

Real-Time Motion Correction in Magnetic Resonance Spectroscopy: AI solution inspired by fundamental science
Benedetta Argiento, Alberto Annovi, Silvia Capuani, Matteo Cacioppo, Andrea Ciardiello, Roberto Coccurello, Stefano Giagu, Federico Giove, Alessandro Lonardo, Francesca Lo Cicero, Alessandra Maiuro, Carlo Mancini Terracciano, Mario Merola, Marco Montuori, Emilia Nistic\`o, Pierpaolo Perticaroli, Biagio Rossi, Cristian Rossi, Elvira Rossi, Francesco Simula, Cecilia Voena

Real-Time Motion Correction in Magnetic Resonance Spectroscopy: AI solution inspired by fundamental science
Magnetic Resonance Spectroscopy (MRS) is a powerful non-invasive tool for metabolic tissue analysis but is often degraded by patient motion, limiting clinical utility. The RECENTRE project (REal-time motion CorrEctioN in magneTic Resonance) presents an AI-driven, real-time motion correction pipeline based on optimized GRU networks, inspired by tagging and fast-trigger algorithms from high-energy physics. Models evaluated on held-out test sets achieve good predictive performance and overall posi…

Apple says the iPhone 17 lineup and iPhone Air come with Memory Integrity Enforcement, which provides "industry-first, always-on memory safety protection" (Richard Lawler/The Verge)
https://www.theverge.com/news/775234/iphone-17-air-…

Apple says the iPhone 17 comes with a massive security upgrade
Apple explains iPhone 17 Memory Integrity Enforcement and Enhanced Memory Tagging Extension security updates.

visualizeus: vi.sualize.us picture tagging network
Three bipartite networks of tag-picture, user-picture, and user-tag linkages that represent the folksonomy of the picture tagging network of vi.sualize.us. The date of this snapshot is uncertain.
This network has 577437 nodes and 2298816 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph

Quark-Gluon tagging performance at the High-Luminosity LHC using constituent-based transformer models
F. L. Castillo, J Lev\^eque
https://arxiv.org/abs/2509.14759 https://

Quark-Gluon tagging performance at the High-Luminosity LHC using constituent-based transformer models
Jet constituents provide a more detailed description of a jet's radiation pattern than global observables. In simulations for ATLAS Run-2 data (2015-2018), transformer-based taggers trained on low-level inputs outperformed traditional methods using high-level variables with conventional neural networks for quark-gluon discrimination. With the upcoming High-Luminosity LHC (HL-LHC), which will deliver higher luminosity and energy, the ATLAS detector will be upgraded with an extended Inner Tracker…

Design and Development of a Scalable and Energy-Efficient Localization Framework Leveraging LoRa Ranging-Capable Transceivers
Hasan Albinsaid, Bodhibrata Mukhopadhyay, Mohamed-Slim Alouini
https://arxiv.org/abs/2509.08488

Design and Development of a Scalable and Energy-Efficient Localization Framework Leveraging LoRa Ranging-Capable Transceivers
Precise and energy-efficient localization is a critical requirement in many Internet of Things (IoT) applications, particularly in large-scale deployments such as asset tagging, agriculture, and smart cities, where long battery life and cost-effectiveness are crucial. The Semtech SX1280 LoRa transceiver presents a promising solution for IoT localization. It combines low cost, low power, and precise ranging capability over distances of up to 1 km. However, the ranging process requires two device…

Performance of heavy-flavour jet identification in Lorentz-boosted topologies in proton-proton collisions at $\sqrt{s}$ = 13 TeV
CMS Collaboration
https://arxiv.org/abs/2510.10228

Performance of heavy-flavour jet identification in Lorentz-boosted topologies in proton-proton collisions at $\sqrt{s}$ = 13 TeV
Measurements in the highly Lorentz-boosted regime provoke increased interest in probing the Higgs boson properties and in searching for particles beyond the standard model at the LHC. In the CMS Collaboration, various boosted-object tagging algorithms, designed to identify hadronic jets originating from a massive particle decaying to $\mathrm{b\overline{b}}$ or $\mathrm{c\overline{c}}$, have been developed and deployed across a range of physics analyses. This paper highlights their performance …

visualizeus: vi.sualize.us picture tagging network
Three bipartite networks of tag-picture, user-picture, and user-tag linkages that represent the folksonomy of the picture tagging network of vi.sualize.us. The date of this snapshot is uncertain.
This network has 577437 nodes and 2298816 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph

Hierarchical Bracketing Encodings Work for Dependency Graphs
Ana Ezquerro, Carlos G\'omez-Rodr\'iguez, David Vilares
https://arxiv.org/abs/2509.09388 https://

Hierarchical Bracketing Encodings Work for Dependency Graphs
We revisit hierarchical bracketing encodings from a practical perspective in the context of dependency graph parsing. The approach encodes graphs as sequences, enabling linear-time parsing with $n$ tagging actions, and still representing reentrancies, cycles, and empty nodes. Compared to existing graph linearizations, this representation substantially reduces the label space while preserving structural information. We evaluate it on a multilingual and multi-formalism benchmark, showing competit…

Development of BPM electronics for PIP-II at Fermilab
Shengli Liu (Fermilab, Batavia, USA), Nathan Eddy (Fermilab, Batavia, USA), A. Semenov (Fermilab, Batavia, USA), Brian Fellenz (Fermilab, Batavia, USA)
https://arxiv.org/abs/2509.15388

Development of BPM electronics for PIP-II at Fermilab
This paper presents the uTCA4.0-based BPM electronics for PIP-II, featuring four 250 MSPS ADCs and a Xilinx UltraScale+ MPSoC FPGA with 10 GbE uplink. Design elements include signal conditioning, clock, and thermal management. The FPGA performs signal processing, time tagging, digital down-conversion, and phase drift compensation. Position and phase resolution, and thermal stability - is validated through dedicated testing.

Training Flow Matching Models with Reliable Labels via Self-Purification
Hyeongju Kim, Yechan Yu, June Young Yi, Juheon Lee
https://arxiv.org/abs/2509.19091 https://