Tootfinder

Lorentz-Equivariance without Limitations
Luigi Favaro, Gerrit Gerhartz, Fred A. Hamprecht, Peter Lippmann, Sebastian Pitz, Tilman Plehn, Huilin Qu, Jonas Spinner
https://arxiv.org/abs/2508.14898

Lorentz-Equivariance without Limitations
Lorentz Local Canonicalization (LLoCa) ensures exact Lorentz-equivariance for arbitrary neural networks with minimal computational overhead. For the LHC, it equivariantly predicts local reference frames for each particle and propagates any-order tensorial information between them. We apply it to graph networks and transformers. We showcase its cutting-edge performance on amplitude regression, end-to-end event generation, and jet tagging. For jet tagging, we introduce a large top tagging dataset…

My wife, Collette, and I are working on Travel plans for next year. Santa Fe is on the list. Probably mid to late June. Looking at the weather, seems it’s not too hot (highs low 80s). I’m sure it's crowded at that time but we're ok with that.
I’d love a recommendation or two for something not typically on the radar of tourists. I’m specifically tagging @…, b…

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…

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…

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

Fast hydrogen atom diffraction through monocrystalline graphene
Pierre Guichard, Arnaud Dochain, Rapha\"el Marion, Pauline de Crombrugghe de Picquendaele, Nicolas Lejeune, Beno\^it Hackens, Paul-Antoine Hervieux, Xavier Urbain
https://arxiv.org/abs/2508.13175

Fast hydrogen atom diffraction through monocrystalline graphene
We report fast atom diffraction through single-layer graphene using hydrogen atoms at kinetic energies from 150 to 1200 eV. High-resolution images reveal overlapping hexagonal patterns from coexisting monocrystalline domains. Time-of-flight tagging confirms negligible energy loss, making the method suitable for matter-wave interferometry. The diffraction is well described by the eikonal approximation, with accurate modeling requiring the full 3D interaction potential from DFT. Simpler models fa…

Crosslisted article(s) found for nucl-ex. https://arxiv.org/list/nucl-ex/new
[1/1]:
- Tagging Efficiency Study of Incoherent Diffractive Vector Meson Production at the Second Interact...
Aschenauer, Bazilevsky, Jentsch, Kim, Kiselev, Page, Tu, Ullrich, Wong

😎 Edible microlasers made from food-safe materials can serve as barcodes and biosensors
#optics

Edible microlasers made from food-safe materials can serve as barcodes and biosensors
If you've ever consumed food made with olive oil, there's a good chance you've unknowingly ingested materials capable of producing lasers. Researchers have recently demonstrated edible microlasers—tiny lasers made entirely from food-safe materials—that can be used for food monitoring, product authentication and tagging. These edible microlasers are composed of droplets of oil or water–glycerol mixtures doped with natural optical gain substances, such as chlorophyll (the green pigment in l…

Deezer rolls out AI tagging system to fight streaming fraud; says up to 70% of streams from fully AI-generated tracks are fraudulent

Deezer rolls out AI tagging system to fight streaming fraud; says up to 70% of streams from fully AI-
Platform has introduced what it claims to be the world’s first AI tagging system for music streaming…

Human-in-the-Loop Systems for Adaptive Learning Using Generative AI
Bhavishya Tarun, Haoze Du, Dinesh Kannan, Edward F. Gehringer
https://arxiv.org/abs/2508.11062 https://

Human-in-the-Loop Systems for Adaptive Learning Using Generative AI
A Human-in-the-Loop (HITL) approach leverages generative AI to enhance personalized learning by directly integrating student feedback into AI-generated solutions. Students critique and modify AI responses using predefined feedback tags, fostering deeper engagement and understanding. This empowers students to actively shape their learning, with AI serving as an adaptive partner. The system uses a tagging technique and prompt engineering to personalize content, informing a Retrieval-Augmented Gen…

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

IMO, #tagging is not that intuitive as it seems.
If you do follow my guide with 10 rules, you should get much more out of #tags as you do get otherwise:

StylOch at PAN: Gradient-Boosted Trees with Frequency-Based Stylometric Features
Jeremi K. Ochab, Mateusz Matias, Tymoteusz Boba, Tomasz Walkowiak
https://arxiv.org/abs/2507.12064

StylOch at PAN: Gradient-Boosted Trees with Frequency-Based Stylometric Features
This submission to the binary AI detection task is based on a modular stylometric pipeline, where: public spaCy models are used for text preprocessing (including tokenisation, named entity recognition, dependency parsing, part-of-speech tagging, and morphology annotation) and extracting several thousand features (frequencies of n-grams of the above linguistic annotations); light-gradient boosting machines are used as the classifier. We collect a large corpus of more than 500 000 machine-generat…

#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.

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…

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.

Jet Image Tagging Using Deep Learning: An Ensemble Model
Juvenal Bassa, Vidya Manian, Sudhir Malik, Arghya Chattopadhyay
https://arxiv.org/abs/2508.10034 https://

Jet Image Tagging Using Deep Learning: An Ensemble Model
Jet classification in high-energy particle physics is important for understanding fundamental interactions and probing phenomena beyond the Standard Model. Jets originate from the fragmentation and hadronization of quarks and gluons, and pose a challenge for identification due to their complex, multidimensional structure. Traditional classification methods often fall short in capturing these intricacies, necessitating advanced machine learning approaches. In this paper, we employ two neural net…

@… welcome to mastodon and thanks for the follow! consider making an intro post and tagging it with #introduction for visibility!

Deezer rolls out AI tagging system to fight streaming fraud; says up to 70% of streams from fully AI-generated tracks are fraudulent
#AI #MusicTech #NotTrustworthy

Deezer rolls out AI tagging system to fight streaming fraud; says up to 70% of streams from fully AI-
Platform has introduced what it claims to be the world’s first AI tagging system for music streaming…

Dammit, why can't we get taggers like this in Los Angeles? JFC, if you're gonna crime, at least be creative, losers.
#LosAngeles #tagging #graffiti
From: @…

Uncle Duke (@UncleDuke1969@universeodon.com)
Attached: 1 image speak your truth

Multi-Class-Token Transformer for Multitask Self-supervised Music Information Retrieval
Yuexuan Kong, Vincent Lostanlen, Romain Hennequin, Mathieu Lagrange, Gabriel Meseguer-Brocal
https://arxiv.org/abs/2507.12996

Multi-Class-Token Transformer for Multitask Self-supervised Music Information Retrieval
Contrastive learning and equivariant learning are effective methods for self-supervised learning (SSL) for audio content analysis. Yet, their application to music information retrieval (MIR) faces a dilemma: the former is more effective on tagging (e.g., instrument recognition) but less effective on structured prediction (e.g., tonality estimation); The latter can match supervised methods on the specific task it is designed for, but it does not generalize well to other tasks. In this article, w…

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

GraSP: A Unified Graph-Based Framework for Scalable Generation, Quality Tagging, and Management of Synthetic Data for SFT and DPO
Bidyapati Pradhan, Surajit Dasgupta, Amit Kumar Saha, Omkar Anustoop, Sriram Puttagunta, Vipul Mittal, Gopal Sarda
https://arxiv.org/abs/2508.15432

GraSP: A Unified Graph-Based Framework for Scalable Generation, Quality Tagging, and Management of Synthetic Data for SFT and DPO
The advancement of large language models (LLMs) is critically dependent on the availability of high-quality datasets for Supervised Fine-Tuning (SFT), alignment tasks like Direct Preference Optimization (DPO), etc. In this work, we present a comprehensive synthetic data generation framework that facilitates scalable, configurable, and high-fidelity generation of synthetic data tailored for these training paradigms. Our approach employs a modular and configuration-based pipeline capable of model…

ADSEL: Adaptive dual self-expression learning for EEG feature selection via incomplete multi-dimensional emotional tagging
Tianze Yu, Junming Zhang, Wenjia Dong, Xueyuan Xu, Li Zhuo
https://arxiv.org/abs/2508.05229

ADSEL: Adaptive dual self-expression learning for EEG feature selection via incomplete multi-dimensional emotional tagging
EEG based multi-dimension emotion recognition has attracted substantial research interest in human computer interfaces. However, the high dimensionality of EEG features, coupled with limited sample sizes, frequently leads to classifier overfitting and high computational complexity. Feature selection constitutes a critical strategy for mitigating these challenges. Most existing EEG feature selection methods assume complete multi-dimensional emotion labels. In practice, open acquisition environme…

Recent results on searches with boosted Higgs bosons at CMS
Farouk Mokhtar
https://arxiv.org/abs/2507.11977 https://arxiv.org/pdf/250…

Recent results on searches with boosted Higgs bosons at CMS
The study of boosted Higgs bosons at the LHC provides a unique window to probe Higgs boson couplings at high energy scales and search for signs of physics beyond the standard model. In these proceedings, we present recent results on boosted Higgs boson searches at the CMS experiment, highlighting innovative reconstruction and tagging techniques that enhance sensitivity in this challenging regime.

Note that there’s a spammer today sending #spam tagging individuals with a plea for insulin money. It looks like the one that tagged me has been nuked by mindly.social, but more are to be expected. As Vixie said “There will always be more spam."

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…

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

Real-Time AI-Driven Pipeline for Automated Medical Study Content Generation in Low-Resource Settings: A Kenyan Case Study
Emmanuel Korir, Eugene Wechuli
https://arxiv.org/abs/2507.05212

Real-Time AI-Driven Pipeline for Automated Medical Study Content Generation in Low-Resource Settings: A Kenyan Case Study
Juvenotes is a real-time AI-driven pipeline that automates the transformation of academic documents into structured exam-style question banks, optimized for low-resource medical education settings in Kenya. The system combines Azure Document Intelligence for OCR and Azure AI Foundry (OpenAI o3-mini) for question and answer generation in a microservices architecture, with a Vue/TypeScript frontend and AdonisJS backend. Mobile-first design, bandwidth-sensitive interfaces, institutional tagging, a…

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…

Subtooting since people in the original thread wanted it to be over, but selfishly tagging @… and @… whose opinions I value...
I think that saying "we are not a supply chain" is exactly what open-source maintainers should be doing right now in response to "open source supply chain security" threads.
I can't claim to be an expert and don't maintain any important FOSS stuff, but I do release almost all of my code under open licenses, and I do use many open source libraries, and I have felt the pain of needing to replace an unmaintained library.
There's a certain small-to-mid-scale class of program, including many open-source libraries, which can be built/maintained by a single person, and which to my mind best operate on a "snake growth" model: incremental changes/fixes, punctuated by periodic "skin-shedding" phases where make rewrites or version updates happen. These projects aren't immortal either: as the whole tech landscape around them changes, they become unnecessary and/or people lose interest, so they go unmaintained and eventually break. Each time one of their dependencies breaks (or has a skin-shedding moment) there's a higher probability that they break or shed too, as maintenance needs shoot up at these junctures. Unless you're a company trying to make money from a single long-lived app, it's actually okay that software churns like this, and if you're a company trying to make money, your priorities absolutely should not factor into any decisions people making FOSS software make: we're trying (and to a huge extent succeeding) to make a better world (and/or just have fun with our own hobbies share that fun with others) that leaves behind the corrosive & planet-destroying plague which is capitalism, and you're trying to personally enrich yourself by embracing that plague. The fact that capitalism is *evil* is not an incidental thing in this discussion.
To make an imperfect analogy, imagine that the peasants of some domain have set up a really-free-market, where they provide each other with free stuff to help each other survive, sometimes doing some barter perhaps but mostly just everyone bringing their surplus. Now imagine the lord of the domain, who is the source of these peasants' immiseration, goes to this market secretly & takes some berries, which he uses as one ingredient in delicious tarts that he then sells for profit. But then the berry-bringer stops showing up to the free market, or starts bringing a different kind of fruit, or even ends up bringing rotten berries by accident. And the lord complains "I have a supply chain problem!" Like, fuck off dude! Your problem is that you *didn't* want to build a supply chain and instead thought you would build your profit-focused business in other people's free stuff. If you were paying the berry-picker, you'd have a supply chain problem, but you weren't, so you really have an "I want more free stuff" problem when you can't be arsed to give away your own stuff for free.
There can be all sorts of problems in the really-free-market, like maybe not enough people bring socks, so the peasants who can't afford socks are going barefoot, and having foot problems, and the peasants put their heads together and see if they can convince someone to start bringing socks, and maybe they can't and things are a bit sad, but the really-free-market was never supposed to solve everyone's problems 100% when they're all still being squeezed dry by their taxes: until they are able to get free of the lord & start building a lovely anarchist society, the really-free-market is a best-effort kind of deal that aims to make things better, and sometimes will fall short. When it becomes the main way goods in society are distributed, and when the people who contribute aren't constantly drained by the feudal yoke, at that point the availability of particular goods is a real problem that needs to be solved, but at that point, it's also much easier to solve. And at *no* point does someone coming into the market to take stuff only to turn around and sell it deserve anything from the market or those contributing to it. They are not a supply chain. They're trying to help each other out, but even then they're doing so freely and without obligation. They might discuss amongst themselves how to better coordinate their mutual aid, but they're not going to end up forcing anyone to bring anything or even expecting that a certain person contribute a certain amount, since the whole point is that the thing is voluntary & free, and they've all got changing life circumstances that affect their contributions. Celebrate whatever shows up at the market, express your desire for things that would be useful, but don't impose a burden on anyone else to bring a specific thing, because otherwise it's fair for them to oppose such a burden on you, and now you two are doing your own barter thing that's outside the parameters of the really-free-market.

Flow-dependent tagging of $^{214}$Pb decays in the LZ dark matter detector
J. Aalbers, D. S. Akerib, A. K. Al Musalhi, F. Alder, C. S. Amarasinghe, A. Ames, T. J. Anderson, N. Angelides, H. M. Ara\'ujo, J. E. Armstrong, M. Arthurs, A. Baker, S. Balashov, J. Bang, J. W. Bargemann, E. E. Barillier, K. Beattie, T. Benson, A. Bhatti, T. P. Biesiadzinski, H. J. Birch, E. Bishop, G. M. Blockinger, B. Boxer, C. A. J. Brew, P. Br\'as, S. Burdin, M. C. Carmona-Benitez, M. Carter, A. Cha…

Flow-dependent tagging of $^{214}$Pb decays in the LZ dark matter detector
The LUX-ZEPLIN (LZ) experiment is searching for dark matter interactions in a liquid xenon time projection chamber (LXe-TPC). This article demonstrates how control of the flow state in the LXe-TPC enables the identification of pairs of sequential alpha-decays, which are used to map fluid flow and ion drift in the liquid target. The resulting transport model is used to tag $^{214}$Pb beta-decays, a leading background to dark matter signals in LZ. Temporally evolving volume selections, at a cost …

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

Measurements of semileptonic and leptonic beauty meson decays at Belle II
Tommy Martinov (on behalf of the Belle II collaboration)
https://arxiv.org/abs/2508.08197 https://

Measurements of semileptonic and leptonic beauty meson decays at Belle II
Three recent measurements of leptonic and semileptonic decays of $B$ mesons are presented here. All results use the full Belle II Run 1 $e^+e^- \to Υ(4S) \to B\bar{B}$ dataset of 365 fb$^{-1}$. We present one leptonic $B$ decay result: a measurement of the $B^+ \to τν$ branching fraction with a hadronic tagging method; and two semileptonic $B$ decay results: a determination of $|V_{cb}|$ using $B \to D \ell ν$ decays with an inclusive tagging method and a test of lepton flavour un…

Memoirs of mass accretion: probing the edges of intracluster light in simulated galaxy clusters
Tara Dacunha, Phil Mansfield, Risa Wechsler
https://arxiv.org/abs/2508.02837 http…

Memoirs of mass accretion: probing the edges of intracluster light in simulated galaxy clusters
The diffuse starlight extending throughout massive galaxy clusters, known as intracluster light (ICL), has the potential to be read as a memoir of mass accretion: informative, individual, and yet imperfect. Here, we combine dark matter-only zoom-in simulations from the Symphony suite with the Nimbus "star-tagging" model of the stellar halo to assess how much information about the mass assembly of an individual galaxy cluster can be gleaned from idealized measurements of ICL outskirts. We show t…

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

User Location Disclosure Fails to Deter Overseas Criticism but Amplifies Regional Divisions on Chinese Social Media
Leo Yang Yang, Yiqing Xu
https://arxiv.org/abs/2507.03238

User Location Disclosure Fails to Deter Overseas Criticism but Amplifies Regional Divisions on Chinese Social Media
We examine the behavioral impact of a user location disclosure policy implemented on Sina Weibo, China's largest microblogging platform, using a high-frequency, real-time dataset of uncensored user engagement with 165 leading government and media accounts. Leveraging a natural experiment result from the platform's sudden rollout of location tagging on April 28, 2022, we compare millions of time-stamped observations of user behavior in the comment sections of these accounts before and after the …

Review of the Higgs boson production via vector boson fusion and its decay into bottom quarks in $pp$ collisions at $\sqrt{s}=8,13$ TeV
Fikriye C I Kaya, Ibrahim Mirza
https://arxiv.org/abs/2507.22765 …

Review of the Higgs boson production via vector boson fusion and its decay into bottom quarks in $pp$ collisions at $\sqrt{s}=8,13$ TeV
We present a comprehensive overview of the vector boson fusion production and the following decay of the Higgs boson to two bottom quarks (\(H\!\to\! b\bar{b}\)), which dominates the Higgs total width yet remains experimentally challenging because of substantial QCD multijet backgrounds. We overview the use of boosted decision trees, which advance jet reconstruction and flavour tagging by including boosted topologies and deep-learning-based \(b\)-tagging and which improve sensitivity in associa…

TAPS: Tool-Augmented Personalisation via Structured Tagging
Ekaterina Taktasheva, Jeff Dalton
https://arxiv.org/abs/2506.20409 https://

TAPS: Tool-Augmented Personalisation via Structured Tagging
Recent advancements in tool-augmented large language models have enabled them to interact with external tools, enhancing their ability to perform complex user tasks. However, existing approaches overlook the role of personalisation in guiding tool use. This work investigates how user preferences can be effectively integrated into goal-oriented dialogue agents. Through extensive analysis, we identify key weaknesses in the ability of LLMs to personalise tool use. To this end, we introduce \name, …

From Large-scale Audio Tagging to Real-Time Explainable Emergency Vehicle Sirens Detection
Stefano Giacomelli, Marco Giordano, Claudia Rinaldi, Fabio Graziosi
https://arxiv.org/abs/2506.23437

From Large-scale Audio Tagging to Real-Time Explainable Emergency Vehicle Sirens Detection
Accurate recognition of Emergency Vehicle (EV) sirens is critical for the integration of intelligent transportation systems, smart city monitoring systems, and autonomous driving technologies. Modern automatic solutions are limited by the lack of large scale, curated datasets and by the computational demands of state of the art sound event detection models. This work introduces E2PANNs (Efficient Emergency Pre trained Audio Neural Networks), a lightweight Convolutional Neural Network architectu…

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 hep-ex. https://arxiv.org/list/hep-ex/new
[1/1]:
- Jet Image Tagging Using Deep Learning: An Ensemble Model
Juvenal Bassa, Vidya Manian, Sudhir Malik, Arghya Chattopadhyay

Investigation of the performance of a GNN-based b-jet tagging method in heavy-ion collisions
Changhwan Choi, Sanghoon Lim
https://arxiv.org/abs/2506.22691 …

Investigation of the performance of a GNN-based b-jet tagging method in heavy-ion collisions
Beauty-tagged jets (b-jets)-collimated sprays of particles originating from the fragmentation of beauty quarks produced in the initial hard scatterings-provide a unique probe of parton dynamics in the quark-gluon plasma (QGP) created in ultrarelativistic heavy-ion collisions. In particular, energy loss patterns of low-$p_T$ b-jets traversing the QGP offer valuable insight into the strong interaction in its nonperturbative regime. CMS and ATLAS Collaborations at the LHC have studied b-jet produc…

Searching for top-philic heavy resonances in boosted four-top final states
Luc Darm\'e, Benjamin Fuks, Hao-Lin Li, Matteo Maltoni, Julien Touch\`eque
https://arxiv.org/abs/2507.05334

Searching for top-philic heavy resonances in boosted four-top final states
New heavy resonances with sizeable couplings to top quarks can be probed through searches for beyond-the-Standard-Model effects in four-top production at the LHC. In this work, we present the first next-to-leading-order QCD predictions for the full on-shell and off-shell production of four-top events via new physics contributions, along with dedicated analysis strategies based on the reconstruction and tagging of all final-state top quarks. We develop a detector-level simulation incorporating r…

Taggus: An Automated Pipeline for the Extraction of Characters' Social Networks from Portuguese Fiction Literature
Tiago G Can\'ario, Catarina Duarte, Fl\'avio L. Pinheiro, Jo\~ao L. M. Pereira
https://arxiv.org/abs/2508.03358

Taggus: An Automated Pipeline for the Extraction of Characters' Social Networks from Portuguese Fiction Literature
Automatically identifying characters and their interactions from fiction books is, arguably, a complex task that requires pipelines that leverage multiple Natural Language Processing (NLP) methods, such as Named Entity Recognition (NER) and Part-of-speech (POS) tagging. However, these methods are not optimized for the task that leads to the construction of Social Networks of Characters. Indeed, the currently available methods tend to underperform, especially in less-represented languages, due t…

JEDI-linear: Fast and Efficient Graph Neural Networks for Jet Tagging on FPGAs
Zhiqiang Que, Chang Sun, Sudarshan Paramesvaran, Emyr Clement, Katerina Karakoulaki, Christopher Brown, Lauri Laatu, Arianna Cox, Alexander Tapper, Wayne Luk, Maria Spiropulu
https://arxiv.org/abs/2508.15468

JEDI-linear: Fast and Efficient Graph Neural Networks for Jet Tagging on FPGAs
Graph Neural Networks (GNNs), particularly Interaction Networks (INs), have shown exceptional performance for jet tagging at the CERN High-Luminosity Large Hadron Collider (HL-LHC). However, their computational complexity and irregular memory access patterns pose significant challenges for deployment on FPGAs in hardware trigger systems, where strict latency and resource constraints apply. In this work, we propose JEDI-linear, a novel GNN architecture with linear computational complexity that e…

On $\tau$ Spin Use with KKMCee
J. M. John, Ananya Tapadar, Zbigniew Was
https://arxiv.org/abs/2509.04400 https://arxiv.org/pdf/2509.04400

On $τ$ Spin Use with KKMCee
Spin of $τ$ represents an interesting phenomenology data point in both its production from $e^+ e^-$ collision and its subsequent decay. In precision applications such as Belle-II or FCC, where precision tagging is comparable or better than $0.1 \%$ Monte Carlo applications are usually necessary. \texttt{KKMCee}, the precision Monte Carlo program, is assuring such high precision in a broad energy range. But so far, spin effects were not easy to grasp. We introduce into \texttt{KKMCee}, \texttt…

Emergent musical properties of a transformer under contrastive self-supervised learning
Yuexuan Kong, Gabriel Meseguer-Brocal, Vincent Lostanlen, Mathieu Lagrange, Romain Hennequin
https://arxiv.org/abs/2506.23873

Emergent musical properties of a transformer under contrastive self-supervised learning
In music information retrieval (MIR), contrastive self-supervised learning for general-purpose representation models is effective for global tasks such as automatic tagging. However, for local tasks such as chord estimation, it is widely assumed that contrastively trained general-purpose self-supervised models are inadequate and that more sophisticated SSL is necessary; e.g., masked modeling. Our paper challenges this assumption by revealing the potential of contrastive SSL paired with a transf…

Performance improvement of spatial semantic segmentation with enriched audio features and agent-based error correction for DCASE 2025 Challenge Task 4
Jongyeon Park, Joonhee Lee, Do-Hyeon Lim, Hong Kook Kim, Hyeongcheol Geum, Jeong Eun Lim
https://arxiv.org/abs/2506.21174

Performance improvement of spatial semantic segmentation with enriched audio features and agent-based error correction for DCASE 2025 Challenge Task 4
This technical report presents submission systems for Task 4 of the DCASE 2025 Challenge. This model incorporates additional audio features (spectral roll-off and chroma features) into the embedding feature extracted from the mel-spectral feature to im-prove the classification capabilities of an audio-tagging model in the spatial semantic segmentation of sound scenes (S5) system. This approach is motivated by the fact that mixed audio often contains subtle cues that are difficult to capture wit…

Measurement of Born Cross Sections and Effective Form Factors of $e^ e^-\to \Omega^{-}\bar{\Omega}^{ }$ from$\sqrt{s}$ = 3.7 to 4.7 GeV
BESIII Collaboration, et al.
https://arxiv.org/abs/2508.01359

Measurement of Born Cross Sections and Effective Form Factors of $e^+e^-\to Ω^{-}\barΩ^{+}$ from$\sqrt{s}$ = 3.7 to 4.7 GeV
Using $e^+e^-$ collision data corresponding to an integrated luminosity of 22.7 fb$^{-1}$, collected at center-of-mass energies between 3.7 and 4.7 GeV with the BESIII detector at the BEPCII storage ring, we measure the energy-dependent Born cross sections of $e^+e^-\to Ω^{-}\barΩ^+$ and the effective form factors of the $Ω^-$ baryon. The analysis employs a single baryon tagging method, and the results are consistent with theoretical predictions, providing critical constraints on the electro…

On Temporal Guidance and Iterative Refinement in Audio Source Separation
Tobias Morocutti, Jonathan Greif, Paul Primus, Florian Schmid, Gerhard Widmer
https://arxiv.org/abs/2507.17297

On Temporal Guidance and Iterative Refinement in Audio Source Separation
Spatial semantic segmentation of sound scenes (S5) involves the accurate identification of active sound classes and the precise separation of their sources from complex acoustic mixtures. Conventional systems rely on a two-stage pipeline - audio tagging followed by label-conditioned source separation - but are often constrained by the absence of fine-grained temporal information critical for effective separation. In this work, we address this limitation by introducing a novel approach for S5 th…

Replaced article(s) found for hep-ex. https://arxiv.org/list/hep-ex/new
[1/1]:
- Machine learning opportunities for online and offline tagging of photo-induced and diffractive ev...
Simone Ragoni, Janet Seger, Christopher Anson, David Tlusty

Search for the lepton-flavor-violating $\tau^{-} \rightarrow e^{\mp} \ell^{\pm} \ell^{\mp}$ decays at Belle II
Collaboration, Adachi, Aggarwal, Ahmed, Ahn, Aihara, Akopov, Alghamdi, Alhakami, Aloisio, Althubiti, Amos, Angelsmark, Ky, Antonioli, Asner, Atmacan, Aushev, Aversano, Ayad, Babu, Bae, Baghel, Bahinipati, Bambade, Banerjee, Bansal, Barrett, Bartl, Baudot, Baur, Beaubien, Becherer, Becker, Bennett, Bernlochner, Bertacchi, Bertemes, Bertholet, Bessner, Bettarini, Bhardwaj, Bhuya…

Search for the lepton-flavor-violating $τ^{-} \rightarrow e^{\mp} \ell^{\pm} \ell^{\mp}$ decays at Belle II
We present the result of a search for the charged-lepton-flavor violating decays $τ^- \rightarrow e^\mp \ell^\pm \ell^-$, where $\ell$ is a muon or an electron, using a data sample with an integrated luminosity of 428 fb$^{-1}$ recorded by the Belle II experiment at the SuperKEKB $e^+e^-$ collider. The selection of $e^+e^- \toτ^+τ^-$ events containing a signal candidate is based on an inclusive-tagging reconstruction and on a boosted decision tree to suppress background. Upper limits on the …