Tootfinder

Generative AI as a catalyst for democratic Innovation: Enhancing citizen engagement in participatory budgeting
Italo Alberto do Nascimento Sousa, Jorge Machado, Jose Carlos Vaz
https://arxiv.org/abs/2509.19497

Generative AI as a catalyst for democratic Innovation: Enhancing citizen engagement in participatory budgeting
This research examines the role of Generative Artificial Intelligence (AI) in enhancing citizen engagement in participatory budgeting. In response to challenges like declining civic participation and increased societal polarization, the study explores how online political participation can strengthen democracy and promote social equity. By integrating Generative AI into public consultation platforms, the research aims to improve citizen proposal formulation and foster effective dialogue between…

Podcast : La Secte OKC : ils racontent leur vie dans la secte bouddhiste belge
Presque 15 ans d'écart entre nos deux protagonistes et pourtant tellement de point commun quoi qu'en dise "l'évolution de l'éducation des enfants" selon la OKC
https://

Security Evaluation of Android apps in budget African Mobile Devices
Alioune Diallo, Anta Diop, Abdoul Kader Kabore, Jordan Samhi, Aleksandr Pilgun, Tegawend\'e F. Bissyande, Jacque Klein
https://arxiv.org/abs/2509.18800

AnchDrive: Bootstrapping Diffusion Policies with Hybrid Trajectory Anchors for End-to-End Driving
Jinhao Chai, Anqing Jiang, Hao Jiang, Shiyi Mu, Zichong Gu, Shugong Xu
https://arxiv.org/abs/2509.20253

AnchDrive: Bootstrapping Diffusion Policies with Hybrid Trajectory Anchors for End-to-End Driving
End-to-end multi-modal planning has become a transformative paradigm in autonomous driving, effectively addressing behavioral multi-modality and the generalization challenge in long-tail scenarios. We propose AnchDrive, a framework for end-to-end driving that effectively bootstraps a diffusion policy to mitigate the high computational cost of traditional generative models. Rather than denoising from pure noise, AnchDrive initializes its planner with a rich set of hybrid trajectory anchors. Thes…

You Only Measure Once: On Designing Single-Shot Quantum Machine Learning Models
Chen-Yu Liu, Leonardo Placidi, Kuan-Cheng Chen, Samuel Yen-Chi Chen, Gabriel Matos
https://arxiv.org/abs/2509.20090

You Only Measure Once: On Designing Single-Shot Quantum Machine Learning Models
Quantum machine learning (QML) models conventionally rely on repeated measurements (shots) of observables to obtain reliable predictions. This dependence on large shot budgets leads to high inference cost and time overhead, which is particularly problematic as quantum hardware access is typically priced proportionally to the number of shots. In this work we propose You Only Measure Once (Yomo), a simple yet effective design that achieves accurate inference with dramatically fewer measurements, …

Voedselrest recycling als het ware.
NoPalm Ingredients tovert voedselresten om tot olie https://www.volkskrant.nl/economie/dit-wageningse-bedrijf-tovert-op-wonderlijke-wijze-voedselresten-om-tot-olie~bff0b215/

Dit Wageningse bedrijf tovert op wonderlijke wijze voedselresten om tot olie
Supermarktschappen liggen vol producten met palmolie, waar tropisch regenwoud voor wordt gekapt. In Wageningen heeft een bedrijf een alternatief bedacht. De enige benodigdheden: een grote berg voedselresten en een gist.

A look at the collapse of narrative podcasts, facing high production costs and limited ad revenue, despite overall podcast listenership reaching all-time highs (Eric Benson/Rolling Stone)
https://www.rollingstone.com/culture/cultu

Who Killed the Narrative Podcast?
Podcasts like 'Serial,' 'The Shrink Next Door,' and 'Over My Dead Body' were once a booming industry. But times — and budgets — have changed.

A look at the collapse of narrative podcasts, facing high production costs and limited ad revenue, despite overall podcast listenership reaching all-time highs (Eric Benson/Rolling Stone)
https://www.rollingstone.com/culture/cultu

Who Killed the Narrative Podcast?
Podcasts like 'Serial,' 'The Shrink Next Door,' and 'Over My Dead Body' were once a booming industry. But times — and budgets — have changed.

Verification and Synthesis of Discrete-Time Control Barrier Functions
Erfan Shakhesi, W. P. M. H. Heemels, Alexander Katriniok
https://arxiv.org/abs/2509.18685 https://

Verification and Synthesis of Discrete-Time Control Barrier Functions
Discrete-time Control Barrier Functions (DTCBFs) have recently attracted interest for guaranteeing safety and synthesizing safe controllers for discrete-time dynamical systems. This paper addresses the open challenges of verifying candidate DTCBFs and synthesizing DTCBFs for general nonlinear discrete-time systems with input constraints and arbitrary safe sets. In particular, we propose a branch-and-bound method, inspired by the $α$BB algorithm, for the verification of candidate DTCBFs in both…

Budgeted Adversarial Attack against Graph-Based Anomaly Detection in Sensor Networks
Sanju Xaviar, Omid Ardakanian
https://arxiv.org/abs/2509.17987 https://

Budgeted Adversarial Attack against Graph-Based Anomaly Detection in Sensor Networks
Graph Neural Networks (GNNs) have emerged as powerful models for anomaly detection in sensor networks, particularly when analyzing multivariate time series. In this work, we introduce BETA, a novel grey-box evasion attack targeting such GNN-based detectors, where the attacker is constrained to perturb sensor readings from a limited set of nodes, excluding the target sensor, with the goal of either suppressing a true anomaly or triggering a false alarm at the target node. BETA identifies the sen…