Tootfinder

Automated Energy-Aware Time-Series Model Deployment on Embedded FPGAs for Resilient Combined Sewer Overflow Management
Tianheng Ling, Vipin Singh, Chao Qian, Felix Biessmann, Gregor Schiele
https://arxiv.org/abs/2508.13905

Automated Energy-Aware Time-Series Model Deployment on Embedded FPGAs for Resilient Combined Sewer Overflow Management
Extreme weather events, intensified by climate change, increasingly challenge aging combined sewer systems, raising the risk of untreated wastewater overflow. Accurate forecasting of sewer overflow basin filling levels can provide actionable insights for early intervention, helping mitigating uncontrolled discharge. In recent years, AI-based forecasting methods have offered scalable alternatives to traditional physics-based models, but their reliance on cloud computing limits their reliability …

Y'know what rubs me weird? Open Source guys who are all into competing projects. Like sure sometimes you gotta fork 'cause people's desires really are incompatible, but here we are with a system that lets us join forces for the greater good and here you are making Yet Another Thingy instead of collaborating.
I kinda fundamentally don't trust you to behave well in your project if this is the foundation.
There's reasons for forks and alternatives but come on

Music writer, producer, and podcaster Dylan Tupper Rupert on envisioning alternatives https://thecreativeindependent.com…

Music writer, producer, and podcaster Dylan Tupper Rupert on envisioning alternatives – The Creative Independent
Music writer, producer, and podcaster Dylan Tupper Rupert discusses growing up in the Seattle arts scene, dealing with music industry hierarchy, and imagining the ideal conditions for creativity.

Measuring IIA Violations in Similarity Choices with Bayesian Models
Hugo Sales Corr\^ea, Suryanarayana Sankagiri, Daniel Ratton Figueiredo, Matthias Grossglauser
https://arxiv.org/abs/2508.14615

Measuring IIA Violations in Similarity Choices with Bayesian Models
Similarity choice data occur when humans make choices among alternatives based on their similarity to a target, e.g., in the context of information retrieval and in embedding learning settings. Classical metric-based models of similarity choice assume independence of irrelevant alternatives (IIA), a property that allows for a simpler formulation. While IIA violations have been detected in many discrete choice settings, the similarity choice setting has received scant attention. This is because …

HPD: Hybrid Projection Decomposition for Robust State Space Models on Analog CIM Hardware
Yuannuo Feng, Wenyong Zhou, Yuexi Lyu, Hanjie Liu, Zhengwu Liu, Ngai Wong, Wang Kang
https://arxiv.org/abs/2508.11935

HPD: Hybrid Projection Decomposition for Robust State Space Models on Analog CIM Hardware
State Space Models (SSMs) are efficient alternatives to traditional sequence models, excelling at processing long sequences with lower computational complexity. Their reliance on matrix multiplications makes them ideal for compute-in-memory (CIM) architectures, which improve energy efficiency by computing within memory arrays. However, device non-idealities in CIM introduce weight perturbations that can degrade inference accuracy. In this paper, we systematically analyze the robustness of SSMs …

⚡ Food Vendors Ditch Noisy Generators as City Explores Cleaner Power Options
#nyc

Food Vendors Ditch Noisy Generators as City Explores Cleaner Power Options
From halal carts to hot dog stands, sellers have long relied on noisy, polluting fossil fuel generators. Enter battery-powered alternatives — but the transition isn’t cheap or simple.

«younger generations are seeking information on social video platforms rather than the open web. This gradual shift is not unique to #Wikipedia. Many other publishers and content platforms are reporting similar shifts as users spend more time on search engines, AI chatbots, and social media to find information.»
All of those "alternatives" are facilitated through algorithmic recommendation engines designed to maximize profits, what could possible go wrong there…
https://www.404media.co/wikipedia-says-ai-is-causing-a-dangerous-decline-in-human-visitors/

On Strong and Weak Admissibility in Non-Flat Assumption-Based Argumentation
Matti Berthold, Lydia Bl\"umel, Anna Rapberger
https://arxiv.org/abs/2508.11182 https://

On Strong and Weak Admissibility in Non-Flat Assumption-Based Argumentation
In this work, we broaden the investigation of admissibility notions in the context of assumption-based argumentation (ABA). More specifically, we study two prominent alternatives to the standard notion of admissibility from abstract argumentation, namely strong and weak admissibility, and introduce the respective preferred, complete and grounded semantics for general (sometimes called non-flat) ABA. To do so, we use abstract bipolar set-based argumentation frameworks (BSAFs) as formal playgroun…

Evaluating Line Chart Strategies for Mitigating Density of Temporal Data: The Impact on Trend, Prediction, and Decision-Making
Rifat Ara Proma, Ghulam Jilani Quadri, Paul Rosen
https://arxiv.org/abs/2510.11912

Evaluating Line Chart Strategies for Mitigating Density of Temporal Data: The Impact on Trend, Prediction, and Decision-Making
Overplotted line charts can obscure trends in temporal data and hinder prediction. We conduct a user study comparing three alternatives-aggregated, trellis, and spiral line charts against standard line charts on tasks involving trend identification, making predictions, and decision-making. We found aggregated charts performed similarly to standard charts and support more accurate trend recognition and prediction; trellis and spiral charts generally lag. We also examined the impact on decision-m…

Charting GLOBs in Asymptotically Safe Gravity
Francesco Del Porro, Jonas Pfeiffer, Alessia Platania, Samuele Silveravalle
https://arxiv.org/abs/2509.14309 https://

Charting GLOBs in Asymptotically Safe Gravity
Computing the gravitational effective action provides a direct route to charting the landscape of admissible black hole spacetimes and their alternatives, which we will collectively call "gravitationally localized objects" (GLOBs). In this work, we provide a proof of principle of this idea within the framework of asymptotically safe gravity. Focusing on the Einstein-Weyl truncation, we identify the unique ultraviolet-complete trajectory emanating from the asymptotically safe fixed point and use…

Insect-Wing Structured Microfluidic System for Reservoir Computing
Jacob Clouse (School of Computing, University of Nebraska-Lincoln, Lincoln, Nebraska, USA), Thomas Ramsey (Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln, Lincoln, Nebraska, USA), Samitha Somathilaka (School of Computing, University of Nebraska-Lincoln, Lincoln, Nebraska, USA), Nicholas Kleinsasser (School of Computing, University of Nebraska-Lincoln, Lincoln, Nebraska, USA), Sangjin …

Insect-Wing Structured Microfluidic System for Reservoir Computing
As the demand for more efficient and adaptive computing grows, nature-inspired architectures offer promising alternatives to conventional electronic designs. Microfluidic platforms, drawing on biological forms and fluid dynamics, present a compelling foundation for low-power, high-resilience computing in environments where electronics are unsuitable. This study explores a hybrid reservoir computing system based on a dragonfly-wing inspired microfluidic chip, which encodes temporal input pattern…

A Time- and Energy-Efficient CNN with Dense Connections on Memristor-Based Chips
Wenyong Zhou, Yuan Ren, Jiajun Zhou, Tianshu Hou, Ngai Wong
https://arxiv.org/abs/2508.12251 htt…

A Time- and Energy-Efficient CNN with Dense Connections on Memristor-Based Chips
Designing lightweight convolutional neural network (CNN) models is an active research area in edge AI. Compute-in-memory (CIM) provides a new computing paradigm to alleviate time and energy consumption caused by data transfer in von Neumann architecture. Among competing alternatives, resistive random-access memory (RRAM) is a promising CIM device owing to its reliability and multi-bit programmability. However, classical lightweight designs such as depthwise convolution incurs under-utilization …

Mumbai-based online pharmacy Truemeds, which offers generic alternatives to branded drugs, raised $85M led by Accel at a $400M valuation, up from $110M in 2023 (Jagmeet Singh/TechCrunch)
https://techcrunch.com/2025/08/10/trueme…

Why investors just bet $85M on this Indian company's generic drug strategy | TechCrunch
Truemeds has taken a different route from other Indian online pharmacies — and it has helped the startup double its revenue.

Great thread about #Git self-hosting options:
https://jawns.club/@skyfaller/114989129643625908

Ricardo Mendes, born and raised within the Buddhist cult-like community Ogyen Kunzang Choling (OKC), describes in his testimony how this community, initially founded on ideals of spirituality, communal living, and alternatives to Western society, gradually became a sectarian organization

I'm still using Chrome and Google's built in search widget on android 12. Anyone got better alternatives I can use?
I find the widget really helpful but "AI Mode" is annoying me haha. Using proton pass btw.
#android #degoogle

Gating upconversion electroluminescence in a single molecule via adsorption-induced interaction of unpaired spin
Vibhuti N. Rai, Christof Holzer, Carsten Rockstuhl, Wulf Wulfhekel, Lukas Gerhard
https://arxiv.org/abs/2508.11501

Gating upconversion electroluminescence in a single molecule via adsorption-induced interaction of unpaired spin
Molecules with unpaired spins (radicals) offer promising alternatives to closed-shell molecules as they are less limited regarding the spin statistics in their electroluminescence. Here, we combine scanning tunneling microscopy induced luminescence and density functional theory to study single vanadyl phthalocyanine molecules, which are stable neutral radicals. Two distinct adsorption geometries of the molecule on NaCl/Au(111) lead to a difference in the interaction of the unpaired electron wit…

Anyone have any similar-shaped products to recommend (semi-structured shared documents, shared on a team, live editing, low friction)?
We have Google Docs, which will be…fiiiiiine, whatever, but I’m always interested in good alternatives.

Join us for a casual Scrappy Hour bike ride on Sunday, August 31st. 🚴‍♀️
We'll roll out from Rocket Baby just after 9am and head to the Domes... There's about four or five of us so far but we welcome anyone to join us! 🚴
https://www.instagram.com/p/DNvbxVRXHS1/

Scrappy Hour on Instagram: "It’s that time of year again! Ya, you know it! It’s Scrappy Hour BBQ BABY!!! Maybe it will be hot and we can all go swimming. Or maybe it will rain and we can all cower together. Or maybe it will be perfect and we’ll lay in the grass eating hot dogs till we have to roll us out of there. Here’s how it’s going to go down. First we’ll do a ride. We’re gonna do the Domes again, because it’s fun. Meet ups: BAY VIEW Cactus Club- meet 8:30a; wheels up 9:00a EAST SIDE/RW The Daily Bird-meet 9:00a; wheels up 9:15a TOSA Rocket Baby- meet 9:00; wheels up 9:15a Then, we SHBBQ at South Shore Park! We’ll bring some dogs and veggie alternatives. A couple sides. And a cooler of mixed bevies. We’ll bring a couple grills too. Last year our gang showed up with some really delightful offerings! There was homemade bread, and baked goods and side salads. It ruled. So feel free to bring what ever you would like to share with everyone. It will be much appreciated. Bring a baseball mitt and we’ll have a catch. Have a frisbee, bring that too. If it’s hot, good luck keeping me out of that lake, so bring your suit. If you have any questions, as always hit us up and we’ll try to answer. All our love, SH ✌️🚲🏃‍♂️☕️ #coffeeoutsidemke #scrappyhourmke"
107 likes, 8 comments - scrappyhourmke on August 24, 2025: "It’s that time of year again! Ya, you know it! It’s Scrappy Hour BBQ BABY!!! Maybe it will be hot and we can all go swimming. Or maybe it will rain and we can all cower together. Or maybe it will be perfect and we’ll lay in the grass eating hot dogs till we have to roll us out of there. Here’s how it’s going to go down. First we’ll do a ride. We’re gonna do the Domes again, because it’s fun. Meet ups: BAY VIEW …

More than nine in 10 renewable power projects globally are now cheaper than fossil fuel alternatives.
Solar power is about 41% cheaper than the lowest-cost fossil fuel alternative,
and onshore wind generation is less than half the price of fossil fuels, according to a report from the International Renewable Energy Agency.
Costs have been driven down by the increasingly widespread use of the technologies,
a huge focus on low-carbon manufacturing in China,
and bu…

Is a race or a lottery a good way to allocate subsidies, or are there better alternatives?
Yesterday, a new round of subsidies for electric heavy-duty vehicles opened in the Netherlands – and was immediately oversubscribed, just like the previous rounds.
https://www.rvo.nl/subsidies-financiering/

Optimizing Freight Rail Electrification: A Framework for Charge Station Selection and Battery Charge/Swap Scheduling
Jia Guo, Elnaz Irannezhad
https://arxiv.org/abs/2509.10157 h…

Optimizing Freight Rail Electrification: A Framework for Charge Station Selection and Battery Charge/Swap Scheduling
Battery electric freight trains are crucial for decarbonization by providing zero-emission transportation alternatives. The proper adoption of battery electric freight trains depends on an efficient battery electrification strategy, involving both infrastructure setup and charge scheduling. The study presents a comprehensive model for the optimal design of charging infrastructure and charge scheduling for each train. To provide more refueling flexibility, we allow batteries to be either charged…

Biscuit – Eclipse Biscuit is an authorization token with decentralized verification, offline attenuation and strong security policy enforcement based on a logic language
Has anyone of you ever used @… and implemented it in a web project? Can you omit this or should I stick to standards or use other alternatives?
🍪

Biscuit

Modeling gamma-ray signatures of particle acceleration in stellar clusters from GeV to PeV
A. Inventar, S. Gabici, E. Peretti
https://arxiv.org/abs/2510.12562 https://

Modeling gamma-ray signatures of particle acceleration in stellar clusters from GeV to PeV
Young massive stellar clusters (YMSCs) have recently regained interest as PeVatron candidates, potentially accounting for the cosmic-ray (CR) knee as alternatives to isolated supernova remnants (SNRs). LHAASO's unique capability to detect photons above 0.1 PeV, hence tracing multi-PeV CRs, can provide critical constraints on galactic acceleration models when combined with H.E.S.S. and Fermi-LAT data. We investigate the transport of particles from YMSCs acceleration sites, namely wind terminatio…

Combined-distance-based score function of cognitive fuzzy sets and its application in lung cancer pain evaluation
Lisheng Jiang, Tianyu Zhang, Shiyu Yan, Ran Fang
https://arxiv.org/abs/2509.08239

Combined-distance-based score function of cognitive fuzzy sets and its application in lung cancer pain evaluation
In decision making, the cognitive fuzzy set (CFS) is a useful tool in expressing experts' complex assessments of alternatives. The distance of CFS, which plays an important role in decision analyses, is necessary when the CFS is applied in solving practical issues. However, as far as we know, the studies on the distance of CFS are few, and the current Minkowski distance of CFS ignores the hesitancy degree of CFS, which might cause errors. To fill the gap of the studies on the distance of CFS, b…

Construction of optimal tests for symmetry on the torus and their quantitative error bounds
Andreas Anastasiou, Christophe Ley, Sophia Loizidou
https://arxiv.org/abs/2510.06055 …

Construction of optimal tests for symmetry on the torus and their quantitative error bounds
In this paper, we develop optimal tests for symmetry on the hyper-dimensional torus, leveraging Le Cam's methodology. We address both scenarios where the center of symmetry is known and where it is unknown. These tests are not only valid under a given parametric hypothesis but also under a very broad class of symmetric distributions. The asymptotic behavior of the proposed tests is studied both under the null hypothesis and local alternatives, and we derive quantitative bounds on the distributi…

Smooth Reading: Bridging the Gap of Recurrent LLM to Self-Attention LLM on Long-Context Tasks
Kai Liu, Zhan Su, Peijie Dong, Fengran Mo, Jianfei Gao, ShaoTing Zhang, Kai Chen
https://arxiv.org/abs/2507.19353

Smooth Reading: Bridging the Gap of Recurrent LLM to Self-Attention LLM on Long-Context Tasks
Recently, recurrent large language models (Recurrent LLMs) with linear computational complexity have re-emerged as efficient alternatives to self-attention-based LLMs (Self-Attention LLMs), which have quadratic complexity. However, Recurrent LLMs often underperform on long-context tasks due to their limited fixed-size memory. Previous research has primarily focused on enhancing the memory capacity of Recurrent LLMs through architectural innovations, but these approaches have not yet enabled Rec…

Robust Voting Rules on the Interval Domain
Patrick Lederer
https://arxiv.org/abs/2509.04874 https://arxiv.org/pdf/2509.04874…

Robust Voting Rules on the Interval Domain
In this paper, we study voting rules on the interval domain, where the alternatives are arranged according to an externally given strict total order and voters report intervals of this order to indicate the alternatives they support. For this setting, we introduce and characterize the class of position-threshold rules, which compute a collective position of the voters with respect to every alternative and choose the left-most alternative whose collective position exceeds its threshold value. Ou…

Representations for multidimensional down-down deconvolution of ocean-bottom seismic data: theory and practical implications
Kees Wapenaar, Matteo Ravasi, Claudio Bagaini
https://arxiv.org/abs/2509.13123

Representations for multidimensional down-down deconvolution of ocean-bottom seismic data: theory and practical implications
Multidimensional up-down deconvolution effectively eliminates surface-related multiples from ocean-bottom seismic data. Recently, several down-down deconvolution methods have been introduced as attractive alternatives. Whereas multidimensional up-down deconvolution fully accounts for lateral variations of the medium parameters, the underlying theory of some of the down-down deconvolution methods is essentially based on the assumption that the medium is horizontally layered. We derive representa…

TransLink seeks feedback on Metrotown-North Shore Bus Rapid Transit
Input will help decide between two route options
TransLink is launching public engagement on the future Bus Rapid Transit (BRT) route between Metrotown and the North Shore. Members of the public are being asked to provide feedback on the project, rank features that are most important to them, and pick which of the two routes they prefer.

Enabling Multi-Species Bird Classification on Low-Power Bioacoustic Loggers
Stefano Ciapponi, Leonardo Mannini, Jarek Scanferla, Matteo Anderle, Elisabetta Farella
https://arxiv.org/abs/2509.20103

Enabling Multi-Species Bird Classification on Low-Power Bioacoustic Loggers
This paper introduces WrenNet, an efficient neural network enabling real-time multi-species bird audio classification on low-power microcontrollers for scalable biodiversity monitoring. We propose a semi-learnable spectral feature extractor that adapts to avian vocalizations, outperforming standard mel-scale and fully-learnable alternatives. On an expert-curated 70-species dataset, WrenNet achieves up to 90.8\% accuracy on acoustically distinctive species and 70.1\% on the full task. When deplo…

Blockchain-Based Decentralized Domain Name System
Guang Yang, Peter Trinh, Alma Nkemla, Amuru Serikyaku, Edward Tatchim, Osman Sharaf
https://arxiv.org/abs/2508.05655 https://…

Blockchain-Based Decentralized Domain Name System
The current Domain Name System (DNS) infrastructure faces critical vulnerabilities including poisoning attacks, censorship mechanisms, and centralized points of failure that compromise internet freedom and security. Recent incidents such as DNS poisoning attacks on ISP customers highlight the urgent need for resilient alternatives. This paper presents a novel blockchain-based Decentralized Domain Name System (DDNS). We designed a specialized Proof-of-Work blockchain to maximize support for DNS-…

Ricardo Mendes, born and raised within the Buddhist cult-like community Ogyen Kunzang Choling (OKC), describes in his testimony how this community, initially founded on ideals of spirituality, communal living, and alternatives to Western society, gradually became a sectarian organization

Re this response to @… 's thread on Apple and other US tech, I have an @… which I'm super happy with. But the OS is still android..
@… -
#buyeuropean #boycottusa
European Alternatives to Apple iPhone:
https://buy-european.net/en/alternative-to/apple-iphone

"Grillz on a hijabi": Intersectional Identities in Fostering Critical AI Literacy
Jaemarie Solyst, Chloe Fong, Faisal Nurdin, Rotem Landesman, R. Benjamin Shapiro
https://arxiv.org/abs/2510.06306

"Grillz on a hijabi": Intersectional Identities in Fostering Critical AI Literacy
As AI increasingly saturates our daily lives, it is crucial that youth develop skills to critically use and assess AI systems and envision better alternatives. We apply theories from culturally responsive computing to design and study a learning experience meant to support Black Muslim teen girls in developing critical literacy with generative AI (GenAI). We investigate fashion design as a culturally-rich, creative domain for youth to apply GenAI and then reflect on GenAI's socio-ethical aspect…

Additive Distributionally Robust Ranking and Selection
Zaile Li, Yuchen Wan, L. Jeff Hong
https://arxiv.org/abs/2509.06147 https://arxiv.org/pdf/2509.06147…

Additive Distributionally Robust Ranking and Selection
Ranking and selection (R&S) aims to identify the alternative with the best mean performance among $k$ simulated alternatives. The practical value of R&S depends on accurate simulation input modeling, which often suffers from the curse of input uncertainty due to limited data. Distributionally robust ranking and selection (DRR&S) addresses this challenge by modeling input uncertainty via an ambiguity set of $m > 1$ plausible input distributions, resulting in $km$ scenarios in total. Recent DRR&S…

Google releases the Gemini 2.5 Computer Use model, built on Gemini 2.5 Pro's capabilities to power agents that can interact with UIs, in preview via the API (The Keyword)
https://blog.google/technology/google-deepmind/gemini-computer-use-model/

Introducing the Gemini 2.5 Computer Use model
Today we are releasing the Gemini 2.5 Computer Use model via the API, which outperforms leading alternatives at browser and mobile tasks.

Bengals' Zac Taylor evaluating options at QB after third loss under Jake Browning https://www.nfl.com/news/bengals-zac-taylor-evaluating-options-at-qb-after-third-loss-under-jake-browning

With the upcoming changes in the next beta of #iTerm2 ("now a web browser as well", "Anthropic is now available as an AI provider") I don't feel like it's the right terminal emulator for me anymore.
Fortunately, there are alternatives: I'm on #WezTerm now. It was easi…

I've made another small contribution to the great @… website! 😍
The "alternatives to Google Maps" page now provides more details on how different websites/apps/etc. that are based on #OpenStreetMap can be used to replace many of the Google Maps functions: navigation, creating custom maps, adding businesses/amenities/POI etc. 🗺️
https://switching.software/replace/google-maps/
Did I miss any good solutions? Suggest/add them on @…!

An expanded evaluation matrix for the entropy-weight TODIM method to reduce the rank reversal probability and its application in selecting energy storage technology
Lisheng Jiang, Tianyu Zhang, Shiyu Yan, Ran Fang
https://arxiv.org/abs/2509.08236

An expanded evaluation matrix for the entropy-weight TODIM method to reduce the rank reversal probability and its application in selecting energy storage technology
The TODIM method (an acronym in Portuguese for interactive and multiple criteria decision-making) with entropy weights is influenced by rank reversal, a phenomenon where the order of two alternatives changes following the addition of another alternative. Research on rank reversal has predominantly focused on single decision-making methods. To the best of our knowledge, the reduction of rank reversal probability in hybrid methods, such as the entropy-weight TODIM method, remains an unresolved ch…

Permutation Tests Based on the Copula-Graphic Estimator and Their Use for Survival Tree Construction
Pauline Baur, Markus Pauly, Takeshi Emura
https://arxiv.org/abs/2507.20799 h…

Permutation Tests Based on the Copula-Graphic Estimator and Their Use for Survival Tree Construction
Survival trees are popular alternatives to Cox or Aalen regression models that offer both modelling flexibility and graphical interpretability. This paper introduces a new algorithm for survival trees that relaxes the assumption of independent censoring. To this end, we use the copula-graphic estimator to estimate survival functions. This allows us to flexibly specify shape and strength of the dependence of survival and censoring times within survival trees. For splitting, we present a permutat…

Randomness in Narrative Video Games: Aesthetics of Different Random Systems
https://azhdarchid.com/randomness-in-narrative-video-games-aesthetics-of-different-random-systems/
Some of these considerations & differences als…

Randomness in Narrative Video Games: Aesthetics of Different Random Systems
On virtual dice, cards, and other alternatives.

I will admit that I’m a little surprised for not getting any remarks on this. As I was under the impression that many people using Mastodon are listening to podcasts.
The alternative hypothesis is that the choice of podcast app is very strong and not many are using, or even trying, alternatives. https://hachyderm.io/@al3x/114915731025463996

An orderly algorithm for generation of Condorcet Domains
Bei Zhou, Klas Markstr\"om
https://arxiv.org/abs/2509.20865 https://arxiv.org/pdf/2509.20865

An orderly algorithm for generation of Condorcet Domains
Condorcet domains are fundamental objects in the theory of majority voting; they are sets of linear orders with the property that if every voter picks a linear order from this set, assuming that the number of voters is odd, and alternatives are ranked according to the pairwise majority ranking, then the result is a linear order on the set of all alternatives. In this paper we present an efficient orderly algorithm for the generation of all non-isomorphic maximal Condorcet domains on $n$ alterna…

UltraScatter: Ray-Based Simulation of Ultrasound Scattering
Felix Duelmer, Mohammad Farid Azampour, Nassir Navab
https://arxiv.org/abs/2510.10612 https://a…

UltraScatter: Ray-Based Simulation of Ultrasound Scattering
Traditional ultrasound simulation methods solve wave equations numerically, achieving high accuracy but at substantial computational cost. Faster alternatives based on convolution with precomputed impulse responses remain relatively slow, often requiring several minutes to generate a full B-mode image. We introduce UltraScatter, a probabilistic ray tracing framework that models ultrasound scattering efficiently and realistically. Tissue is represented as a volumetric field of scattering probabi…

A look at Russia's coordinated crackdown on foreign tech services and shift to state-backed alternatives, as it names VK's Max its national messaging app (Bloomberg)

Accretion onto Reissner-Nordstr\"{o}m naked singularities
Tomasz Krajewski, W{\l}odek Klu\'zniak
https://arxiv.org/abs/2510.10043 https://arxiv.or…

Accretion onto Reissner-Nordström naked singularities
Nearly every galactic core contains a supermassive compact object, hypothesized to be a Kerr black hole. It was only with the advent of Event Horizon Telescope observations that the predictions of this hypothesis could be observationally tested for our own Galaxy, and the nearby elliptical M87, on spatial scales comparable to the gravitational radius. At the same time it became possible to test whether alternatives such as naked singularities in general relativity, or similar objects in alterna…

NeuroCLIP: A Multimodal Contrastive Learning Method for rTMS-treated Methamphetamine Addiction Analysis
Chengkai Wang, Di Wu, Yunsheng Liao, Wenyao Zheng, Ziyi Zeng, Xurong Gao, Hemmings Wu, Zhoule Zhu, Jie Yang, Lihua Zhong, Weiwei Cheng, Yun-Hsuan Chen, Mohamad Sawan
https://arxiv.org/abs/2507.20189

NeuroCLIP: A Multimodal Contrastive Learning Method for rTMS-treated Methamphetamine Addiction Analysis
Methamphetamine dependence poses a significant global health challenge, yet its assessment and the evaluation of treatments like repetitive transcranial magnetic stimulation (rTMS) frequently depend on subjective self-reports, which may introduce uncertainties. While objective neuroimaging modalities such as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) offer alternatives, their individual limitations and the reliance on conventional, often hand-crafted, feature…

Finding your MUSE: Mining Unexpected Solutions Engine
Nir Sweed, Hanit Hakim, Ben Wolfson, Hila Lifshitz, Dafna Shahaf
https://arxiv.org/abs/2509.05072 https://

Finding your MUSE: Mining Unexpected Solutions Engine
Innovators often exhibit cognitive fixation on existing solutions or nascent ideas, hindering the exploration of novel alternatives. This paper introduces a methodology for constructing Functional Concept Graphs (FCGs), interconnected representations of functional elements that support abstraction, problem reframing, and analogical inspiration. Our approach yields large-scale, high-quality FCGs with explicit abstraction relations, overcoming limitations of prior work. We further present MUSE, a…

Score Matching on Large Geometric Graphs for Cosmology Generation
Diana-Alexandra Onutu, Yue Zhao, Joaquin Vanschoren, Vlado Menkovski
https://arxiv.org/abs/2508.16990 https://

Score Matching on Large Geometric Graphs for Cosmology Generation
Generative models are a promising tool to produce cosmological simulations but face significant challenges in scalability, physical consistency, and adherence to domain symmetries, limiting their utility as alternatives to $N$-body simulations. To address these limitations, we introduce a score-based generative model with an equivariant graph neural network that simulates gravitational clustering of galaxies across cosmologies starting from an informed prior, respects periodic boundaries, and s…

ModernVBERT: Towards Smaller Visual Document Retrievers
Paul Teiletche, Quentin Mac\'e, Max Conti, Antonio Loison, Gautier Viaud, Pierre Colombo, Manuel Faysse
https://arxiv.org/abs/2510.01149

ModernVBERT: Towards Smaller Visual Document Retrievers
Multimodal embedding models are gaining prevalence, notably for document retrieval as efficient alternatives to text-only pipelines. These models are typically built by finetuning large vision-language decoders (VLMs) with contrastive losses on text-image pairs. In this work, we show that, while cost-efficient, this repurposing approach often bottlenecks retrieval performance. Through controlled experiments, we establish a principled recipe for improving visual document retrieval models. We not…

Model-Based Testing of an Intermediate Verifier Using Executable Operational Semantics
Lidia Losavio, Marco Paganoni, Carlo A. Furia
https://arxiv.org/abs/2508.17895 https://

Model-Based Testing of an Intermediate Verifier Using Executable Operational Semantics
Lightweight validation technique, such as those based on random testing, are sometimes practical alternatives to full formal verification -- providing valuable benefits, such as finding bugs, without requiring a disproportionate effort. In fact, they can be useful even for fully formally verified tools, by exercising the parts of a complex system that go beyond the reach of formal models. In this context, this paper introduces BCC: a model-based testing technique for the Boogie intermediate v…

Addressing Model Inaccuracies in Transmission Network Reconfiguration via Diverse Alternatives
Paul Bannm\"uller, P\'erine Cunat, Ali Rajaei, Jochen Cremer
https://arxiv.org/abs/2509.17865

Addressing Model Inaccuracies in Transmission Network Reconfiguration via Diverse Alternatives
The ongoing energy transition places significant pressure on the transmission network due to increasing shares of renewables and electrification. To mitigate grid congestion, transmission system operators need decision support tools to suggest remedial actions, such as transmission network reconfigurations or redispatch. However, these tools are prone to model inaccuracies and may not provide relevant suggestions with regard to important unmodeled constraints or operator preferences. We propose…

TWIN: Two window inspection for online change point detection
Patrick Bastian, Tim Kutta
https://arxiv.org/abs/2510.11348 https://arxiv.org/pdf/2510.11348

TWIN: Two window inspection for online change point detection
We propose a new class of sequential change point tests, both for changes in the mean parameter and in the overall distribution function. The methodology builds on a two-window inspection scheme (TWIN), which aggregates data into symmetric samples and applies strong weighting to enhance statistical performance. The detector yields logarithmic rather than polynomial detection delays, representing a substantial reduction compared to state-of-the-art alternatives. Delays remain short, even for lat…

MAAD: Automate Software Architecture Design through Knowledge-Driven Multi-Agent Collaboration
Ruiyin Li, Yiran Zhang, Xiyu Zhou, Peng Liang, Weisong Sun, Jifeng Xuan, Zhi Jin, Yang Liu
https://arxiv.org/abs/2507.21382

MAAD: Automate Software Architecture Design through Knowledge-Driven Multi-Agent Collaboration
Software architecture design is a critical, yet inherently complex and knowledge-intensive phase of software development. It requires deep domain expertise, development experience, architectural knowledge, careful trade-offs among competing quality attributes, and the ability to adapt to evolving requirements. Traditionally, this process is time-consuming and labor-intensive, and relies heavily on architects, often resulting in limited design alternatives, especially under the pressures of agil…

Who Leads in the Shadows? ERGM and Centrality Analysis of Congressional Democrats on Bluesky
Gordon Hew, Ian McCulloh
https://arxiv.org/abs/2507.16858 https://

Who Leads in the Shadows? ERGM and Centrality Analysis of Congressional Democrats on Bluesky
Following the 2024 U.S. presidential election, Democratic lawmakers and their supporters increasingly migrated from mainstream social media plat-forms like X (formerly Twitter) to decentralized alternatives such as Bluesky. This study investigates how Congressional Democrats use Bluesky to form networks of influence and disseminate political messaging in a platform environment that lacks algorithmic amplification. We employ a mixed-methods approach that combines social network analysis, expo-ne…

Robust Econometrics for Growth-at-Risk
Tobias Adrian, Yuya Sasaki, Yulong Wang
https://arxiv.org/abs/2508.00263 https://arxiv.org/pdf/2508.00263

Robust Econometrics for Growth-at-Risk
The Growth-at-Risk (GaR) framework has garnered attention in recent econometric literature, yet current approaches implicitly assume a constant Pareto exponent. We introduce novel and robust econometrics to estimate the tails of GaR based on a rigorous theoretical framework and establish validity and effectiveness. Simulations demonstrate consistent outperformance relative to existing alternatives in terms of predictive accuracy. We perform a long-term GaR analysis that provides accurate and in…

4-Swap: Achieving Grief-Free and Bribery-Safe Atomic Swaps Using Four Transactions
Kirti Singh (Indian Institute of Technology Bombay, India, Institute for Development and Research in Banking Technology, Hyderabad, India), Vinay J. Ribeiro (Indian Institute of Technology Bombay, India), Susmita Mandal (Institute for Development and Research in Banking Technology, Hyderabad, India)

4-Swap: Achieving Grief-Free and Bribery-Safe Atomic Swaps Using Four Transactions
Cross-chain asset exchange is crucial for blockchain interoperability. Existing solutions rely on trusted third parties and risk asset loss, or use decentralized alternatives like atomic swaps, which suffer from grief attacks. Griefing occurs when a party prematurely exits, locking the counterparty's assets until a timelock expires. Hedged Atomic Swaps mitigate griefing by introducing a penalty premium; however, they increase the number of transactions from four (as in Tier Nolan's swap) to six…

Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization
Yuchen Zhu, Wei Guo, Jaemoo Choi, Petr Molodyk, Bo Yuan, Molei Tao, Yongxin Chen
https://arxiv.org/abs/2510.08233

Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization
Diffusion large language models (dLLMs) are promising alternatives to autoregressive large language models (AR-LLMs), as they potentially allow higher inference throughput. Reinforcement learning (RL) is a crucial component for dLLMs to achieve comparable performance with AR-LLMs on important tasks, such as reasoning. However, RL algorithms that are well-suited for dLLMs' unique characteristics have yet to be developed. This paper proposes Distribution Matching Policy Optimization (DMPO), a pri…

Travel Regrets: 10 European Destinations I Won't Ever Visit Again & Where To Go Instead https://www.wanderluststorytellers.com/tra

Travel Regrets: 10 European Destinations I Won't Ever Visit Again & Where To Go Instead
Read our honest take on 10 European destinations that didn't live up to the hype – and the nearby alternatives that stole our hearts.

A Node on the Constellation: The Role of Feminist Makerspaces in Building and Sustaining Alternative Cultures of Technology Production
Erin Gatz, Yasmine Kotturi, Andrea Afua Kwamya, Sarah Fox
https://arxiv.org/abs/2507.22329

A Node on the Constellation: The Role of Feminist Makerspaces in Building and Sustaining Alternative Cultures of Technology Production
Feminist makerspaces offer community led alternatives to dominant tech cultures by centering care, mutual aid, and collective knowledge production. While prior CSCW research has explored their inclusive practices, less is known about how these spaces sustain themselves over time. Drawing on interviews with 18 founders and members across 8 U.S. feminist makerspaces as well as autoethnographic reflection, we examine the organizational and relational practices that support long-term endurance. We …

Network Traffic Classification Using Self-Supervised Learning and Confident Learning
Ehsan Eslami, Walaa Hamouda
https://arxiv.org/abs/2509.23522 https://a…

Network Traffic Classification Using Self-Supervised Learning and Confident Learning
Network traffic classification (NTC) is vital for efficient network management, security, and performance optimization, particularly with 5G/6G technologies. Traditional methods, such as deep packet inspection (DPI) and port-based identification, struggle with the rise of encrypted traffic and dynamic port allocations. Supervised learning methods provide viable alternatives but rely on large labeled datasets, which are difficult to acquire given the diversity and volume of network traffic. Mean…

Linear Risk Sharing on Networks
Arthur Charpentier, Philipp Ratz
https://arxiv.org/abs/2509.21411 https://arxiv.org/pdf/2509.21411

Linear Risk Sharing on Networks
Over the past decade alternatives to traditional insurance and banking have grown in popularity. The desire to encourage local participation has lead products such as peer-to-peer insurance, reciprocal contracts, and decentralized finance platforms to increasingly rely on network structures to redistribute risk among participants. In this paper, we develop a comprehensive framework for linear risk sharing (LRS), where random losses are reallocated through nonnegative linear operators which can …

Growth Optimization of MoSi Thin Film and Measurement of Transport Critical Current Density of its Meander Structure
Shekhar Chandra Pandey Shilpam Sharma, M. K. Chattopadhyay
https://arxiv.org/abs/2509.25797

Growth Optimization of MoSi Thin Film and Measurement of Transport Critical Current Density of its Meander Structure
Amorphous thin film superconductors are promising alternatives for the development of superconducting radiation detectors, especially superconducting nanowire single photon detectors (SNSPDs) and superconducting microwire single photon detectors (SWSPDs), due to their homogeneous nature, ease of deposition, and superconducting parameters comparable to the materials currently being used. A study on the optimization of the growth technology and superconducting transition temperature (TC) of MoSi …

Sextupole reduction via chaos suppression at the National Synchrotron Light Source II
Yongjun Li, Minghao Song, Yoshiteru Hidaka, Victor Smaluk, Timur Shaftan
https://arxiv.org/abs/2510.07224

Sextupole reduction via chaos suppression at the National Synchrotron Light Source II
We revisit the nonlinear lattice design approach for the National Synchrotron Light Source II (NSLS-II) storage ring. By suppressing chaos, we identify alternative sextupole configurations to the original design, which relied on the conventional strategy of simultaneously minimizing Resonance Driving Terms (RDTs) and Amplitude-Dependent Detuning (ADD). These alternatives achieve comparable performance while requiring fewer sextupoles. A detailed comparison of two representative solutions is pre…

A Comparison of Low and high-Order Methods for the Simulation of Supersonic Jet Flows
D. F. Abreu, C. Junqueira-Junior, E. T. V. Dauricio, J. L. F. Azevedo
https://arxiv.org/abs/2509.17725

A Comparison of Low and high-Order Methods for the Simulation of Supersonic Jet Flows
The present work compares results for different numerical methods in search of alternatives to improve the quality of large-eddy simulations for the problem of supersonic turbulent jet flows. Previous work has analyzed supersonic jet flows using a second-order, finite difference solver based on structured meshes, and the results indicated a shorter potential core of the jet and different levels of velocity fluctuations. In the present work, the results of previous simulations are compared to ne…

Terrorism & Democracy in Burkina-Faso
P Carmel Marie Zagre
https://arxiv.org/abs/2509.23046 https://arxiv.org/pdf/2509.23046

Terrorism & Democracy in Burkina-Faso
This article examines the political consequences of terrorism in Burkina Faso. Using a dataset combining geolocated terrorist events from ACLED (from 2015 to 2024) with public opinion data from Afrobarometer, I compare the effect of successful terrorist attacks on public support for democracy and authoritarian alternatives. The results reveal that successful terrorist attacks significantly increase support for military regimes, one man regimes, and one party systems, while decreasing support fo…

FluidFormer: Transformer with Continuous Convolution for Particle-based Fluid Simulation
Nianyi Wang, Yu Chen, Shuai Zheng
https://arxiv.org/abs/2508.01537 https://

FluidFormer: Transformer with Continuous Convolution for Particle-based Fluid Simulation
Learning-based fluid simulation networks have been proven as viable alternatives to traditional numerical solvers for the Navier-Stokes equations. Existing neural methods follow Smoothed Particle Hydrodynamics (SPH) frameworks, which inherently rely only on local inter-particle interactions. However, we emphasize that global context integration is also essential for learning-based methods to stabilize complex fluid simulations. We propose the first Fluid Attention Block (FAB) with a local-globa…

Bayesian Network Propensity Score to Evaluate Treatment Effects in Observational Studies
Clelia Di Serio, Federica Cugnata, Pier Luigi Conti, Alberto Briganti, Fulvia Mecatti, Paola Vicard, Paola Maria Vittoria Rancoita
https://arxiv.org/abs/2509.03194

Bayesian Network Propensity Score to Evaluate Treatment Effects in Observational Studies
This paper focuses on the Bayesian Network Propensity Score (BNPS), a novel approach for estimating treatment effects in observational studies characterized by unknown (and likely unbalanced) designs and complex dependency structures among covariates. Traditional methods, such as logistic regression, often impose rigid parametric assumptions that may lead to misspecification errors, compromising causal inference. Recent classical and machine learning alternatives, such as boosted CART, random f…

On the formation of gravastars
Daniel Jampolski, Luciano Rezzolla
https://arxiv.org/abs/2509.15302 https://arxiv.org/pdf/2509.15302

On the formation of gravastars
Regular black holes and horizonless black-hole mimickers offer mathematically consistent alternatives to address the challenges posed by standard black holes. However, the formation mechanism of these alternative objects is still largely unclear and constitutes a significant open problem since understanding their dynamical formation represents a first step to assess their existence. We here investigate, for the first time and without invoking deviations from general relativity, the dynamical fo…

Canadians who are interested in passenger rail should take a look at what is happening in Mexico right now. They have a National Railway Plan to build 3400km of passenger rail track alongside existing private freight.
CPKC (the merged Canadian Pacific, Kansas City Southern railway) is front and centre.
"CPKC is actively collaborating with the Mexican government to support implementation specifically for the Mexico City – Queretaro and the Saltillo – Nuevo Laredo segments,” the Class I told Vantuono. “CPKC is making steady progress, actively and closely working with Mexican authorities on technical review of project segments. That includes providing detailed assessments and alternatives to facilitate decision-making, and mutual agreements. We are working toward clear agreements that minimize shared infrastructure usage between passenger and freight services. Where interactions are unavoidable, CPKC has proposed infrastructure solutions and operational adjustments, ensuring that the impacts on freight operations and growth remains minimal.””
#Transportation #Railway #Canada #CanPoli #ClimateChange #ClimateAction #EndFossilFuels

The Flood Complex: Large-Scale Persistent Homology on Millions of Points
Florian Graf, Paolo Pellizzoni, Martin Uray, Stefan Huber, Roland Kwitt
https://arxiv.org/abs/2509.22432

The Flood Complex: Large-Scale Persistent Homology on Millions of Points
We consider the problem of computing persistent homology (PH) for large-scale Euclidean point cloud data, aimed at downstream machine learning tasks, where the exponential growth of the most widely-used Vietoris-Rips complex imposes serious computational limitations. Although more scalable alternatives such as the Alpha complex or sparse Rips approximations exist, they often still result in a prohibitively large number of simplices. This poses challenges in the complex construction and in the s…

Entropy-Guided Loop: Achieving Reasoning through Uncertainty-Aware Generation
Andrew G. A. Correa, Ana C. H de Matos
https://arxiv.org/abs/2509.00079 https://

Entropy-Guided Loop: Achieving Reasoning through Uncertainty-Aware Generation
Reasoning models often outperform smaller models but at 3--5$\times$ higher cost and added latency. We present entropy-guided refinement: a lightweight, test-time loop that uses token-level uncertainty to trigger a single, targeted refinement pass. We extract logprobs, compute Shannon entropy on top-$k$ alternatives, and apply a simple OR-logic trigger over perplexity, maximum token entropy, and low-confidence-token count. Unlike approaches that use entropy only for measurement or decoding, we …

DeepMech: A Machine Learning Framework for Chemical Reaction Mechanism Prediction
Manajit Das, Ajnabiul Hoque, Mayank Baranwal, Raghavan B. Sunoj
https://arxiv.org/abs/2509.15872

DeepMech: A Machine Learning Framework for Chemical Reaction Mechanism Prediction
Prediction of complete step-by-step chemical reaction mechanisms (CRMs) remains a major challenge. Whereas the traditional approaches in CRM tasks rely on expert-driven experiments or costly quantum chemical computations, contemporary deep learning (DL) alternatives ignore key intermediates and mechanistic steps and often suffer from hallucinations. We present DeepMech, an interpretable graph-based DL framework employing atom- and bond-level attention, guided by generalized templates of mechani…

Transferring the driveshaft inertia to the grid via the DC-link in MV drive systems
Catalin Arghir, Pieder J\"org, Silvia Mastellone
https://arxiv.org/abs/2508.21760 https:…

Transferring the driveshaft inertia to the grid via the DC-link in MV drive systems
This paper investigates a control approach that renders the driveshaft inertia completely available on the grid side and enhances the fault ride-through behavior of medium-voltage (MV) drive systems. Two main contributions are presented. First, we show how the rotational inertia of the driveline shaft can be synchronously coupled to the grid through a modification of the speed control reference signal and through an adapted DC-link control strategy. For the latter, we pursue two alternatives: o…

Fast prediction of the hydrodynamic QGP evolution in ultra-relativistic heavy-ion collisions using Fourier Neural Operators
David Stewart, Joern Putschke
https://arxiv.org/abs/2507.23598

Fast prediction of the hydrodynamic QGP evolution in ultra-relativistic heavy-ion collisions using Fourier Neural Operators
Recent research in machine learning has employed neural networks to learn mappings between function spaces on bounded domains termed ``neural operators''. As such, these operators can provide alternatives to standard numerical methods for partial differential equation (PDE) solutions. In particular, the Fourier Neural Operator (FNO) has been shown to map solutions for classical fluid flow problems with accuracy competitive with traditional PDE solvers and with much greater computing speed. This…

Support Vector Machines Classification on Bendable RISC-V
Polykarpos Vergos, Theofanis Vergos, Florentia Afentaki, Konstantinos Balaskas, Georgios Zervakis
https://arxiv.org/abs/2508.19656

Support Vector Machines Classification on Bendable RISC-V
Flexible Electronics (FE) technology offers uniquecharacteristics in electronic manufacturing, providing ultra-low-cost, lightweight, and environmentally-friendly alternatives totraditional rigid electronics. These characteristics enable a rangeof applications that were previously constrained by the costand rigidity of conventional silicon technology. Machine learning (ML) is essential for enabling autonomous, real-time intelligenceon devices with smart sensing capabilities in everyday objects.…

The Invisible Mentor: Inferring User Actions from Screen Recordings to Recommend Better Workflows
Litao Yan, Andrew Head, Ken Milne, Vu Le, Sumit Gulwani, Chris Parnin, Emerson Murphy-Hill
https://arxiv.org/abs/2509.26557

The Invisible Mentor: Inferring User Actions from Screen Recordings to Recommend Better Workflows
Many users struggle to notice when a more efficient workflow exists in feature-rich tools like Excel. Existing AI assistants offer help only after users describe their goals or problems, which can be effortful and imprecise. We present InvisibleMentor, a system that turns screen recordings of task completion into vision-grounded reflections on tasks. It detects issues such as repetitive edits and recommends more efficient alternatives based on observed behavior. Unlike prior systems that rely o…

Efficient and Accessible Discrete Choice Experiments: The DCEtool Package for R
Daniel P\'erez-Troncoso
https://arxiv.org/abs/2509.15326 https://arxiv.…

Efficient and Accessible Discrete Choice Experiments: The DCEtool Package for R
Discrete Choice Experiments (DCEs) are widely used to elicit preferences for products or services by analyzing choices among alternatives described by their attributes. The quality of the insights obtained from a DCE heavily depends on the properties of its experimental design. While early DCEs often relied on linear criteria such as orthogonality, these approaches were later found to be inappropriate for discrete choice models, which are inherently non-linear. As a result, statistically effici…

Uncovering the Spectral Bias in Diagonal State Space Models
Ruben Solozabal, Velibor Bojkovic, Hilal AlQuabeh, Kentaro Inui, Martin Tak\'a\v{c}
https://arxiv.org/abs/2508.20441

Uncovering the Spectral Bias in Diagonal State Space Models
Current methods for initializing state space models (SSMs) parameters mainly rely on the \textit{HiPPO framework}, which is based on an online approximation of orthogonal polynomials. Recently, diagonal alternatives have shown to reach a similar level of performance while being significantly more efficient due to the simplification in the kernel computation. However, the \textit{HiPPO framework} does not explicitly study the role of its diagonal variants. In this paper, we take a further step t…

Analyzing Internal Activity and Robustness of SNNs Across Neuron Parameter Space
Szymon Mazurek, Jakub Caputa, Maciej Wielgosz
https://arxiv.org/abs/2507.14757

Analyzing Internal Activity and Robustness of SNNs Across Neuron Parameter Space
Spiking Neural Networks (SNNs) offer energy-efficient and biologically plausible alternatives to traditional artificial neural networks, but their performance depends critically on the tuning of neuron model parameters. In this work, we identify and characterize an operational space - a constrained region in the neuron hyperparameter domain (specifically membrane time constant tau and voltage threshold vth) - within which the network exhibits meaningful activity and functional behavior. Operati…

Transition Models: Rethinking the Generative Learning Objective
Zidong Wang, Yiyuan Zhang, Xiaoyu Yue, Xiangyu Yue, Yangguang Li, Wanli Ouyang, Lei Bai
https://arxiv.org/abs/2509.04394

Transition Models: Rethinking the Generative Learning Objective
A fundamental dilemma in generative modeling persists: iterative diffusion models achieve outstanding fidelity, but at a significant computational cost, while efficient few-step alternatives are constrained by a hard quality ceiling. This conflict between generation steps and output quality arises from restrictive training objectives that focus exclusively on either infinitesimal dynamics (PF-ODEs) or direct endpoint prediction. We address this challenge by introducing an exact, continuous-time…

Would you be interested on a European #coop alternative to #Github for your private/for-profit projects (paid service)?
I welcome comments elaborating on why you said "yes", "maybe" or "no" .
Note: I'm aware of other alternatives like Gitlab, Bitbucket, Gitea, Codeberg... None of those match what I'm asking about for one or more reasons.
#EU #SovereignTech #SovereignCloud #privacy #GDPR #cooperatives
No
Maybe
Yes

Preventing Singularity Problem in $f(R)$ Dark Energy Models
Romy Hanang Setya Budhi, Nehla Shobcha, Norma Sidik Risdianto
https://arxiv.org/abs/2508.20430 https://

Preventing Singularity Problem in $f(R)$ Dark Energy Models
The curvature singularity problem in $f(R)$ dark energy models poses a significant challenge to their viability as alternatives to the $Λ$CDM paradigm. In this work, we investigate the possibility of resolving this issue by incorporating higher-order corrections that are compatible with the inflationary phase. We analyze the effects of adding $R^2$, $R^{\frac{m+2}{m+1}}$ and $α$-attractor representation in $f(R)$ gravity terms to types of dark energy $f(R)$ models, focusing on their ability t…

ACT: Bridging the Gap in Code Translation through Synthetic Data Generation & Adaptive Training
Shreya Saxena, Siva Prasad, Zishan Ahmad, Vishal Vaddina
https://arxiv.org/abs/2507.16478

ACT: Bridging the Gap in Code Translation through Synthetic Data Generation & Adaptive Training
Code translation is a crucial process in software development and migration projects, enabling interoperability between different programming languages and enhancing software adaptability and thus longevity. Traditional automated translation methods rely heavily on handcrafted transformation rules, which often lack flexibility and scalability. Meanwhile, advanced language models present promising alternatives but are often limited by proprietary, API-based implementations that raise concerns ov…

xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
Maximilian Beck, Kajetan Schweighofer, Sebastian B\"ock, Sebastian Lehner, Sepp Hochreiter
https://arxiv.org/abs/2510.02228 …

xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
Scaling laws play a central role in the success of Large Language Models (LLMs), enabling the prediction of model performance relative to compute budgets prior to training. While Transformers have been the dominant architecture, recent alternatives such as xLSTM offer linear complexity with respect to context length while remaining competitive in the billion-parameter regime. We conduct a comparative investigation on the scaling behavior of Transformers and xLSTM along the following lines, prov…