Tootfinder

Okej, to teraz to, co udało mi się wygrzebać w kwestii honorowania kart #PKP #InterCity.
Arriva: honorują od lutego 2025
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Robot can reduce superior's dominance in group discussions with human social hierarchy
Kazuki Komura, Kumi Ozaki, Seiji Yamada
https://arxiv.org/abs/2508.08767 https://

Robot can reduce superior's dominance in group discussions with human social hierarchy
This study investigated whether robotic agents that deal with social hierarchical relationships can reduce the dominance of superiors and equalize participation among participants in discussions with hierarchical structures. Thirty doctors and students having hierarchical relationship were gathered as participants, and an intervention experiment was conducted using a robot that can encourage participants to speak depending on social hierarchy. These were compared with strategies that intervened…

Chern insulators and topological flat bands in cavity-embedded kagome systems
Hikaru Goto, Ryo Okugawa, Takami Tohyama
https://arxiv.org/abs/2510.09150 https://

Chern insulators and topological flat bands in cavity-embedded kagome systems
We investigate topological band structures of a kagome system coupled to a circularly polarized cavity mode, using a model based on a muffin-tin potential and quantum light-matter interaction. We show that Chern insulating phases emerge in the cavity-embedded kagome system due to the light-matter interaction that breaks time-reversal symmetry. We also find that a nearly flat band can be topologically nontrivial with a nonzero Chern number. By varying the light-matter interaction, we also reveal…

Gerade habe ich mir die Zusammenfassung sowie die Interviews nach dem Spiel #BMGKOE angeschaut. Während des Interviews mit Rocco ist mir ein kleines Detail aufgefallen, das mich beeindruckt hat. Rechts neben dem Interviewer kam Eugen Polanksi ins Bild, und einer unserer japanischen Spieler kam ihm entgegen. Eugen machte die Ojigi, statt ihn wie mit den anderen Spielern abzuklatschen. Damit hat unser T…

Feature Space Analysis by Guided Diffusion Model
Kimiaki Shirahama, Miki Yanobu, Kaduki Yamashita, Miho Ohsaki
https://arxiv.org/abs/2509.07936 https://arx…

Feature Space Analysis by Guided Diffusion Model
One of the key issues in Deep Neural Networks (DNNs) is the black-box nature of their internal feature extraction process. Targeting vision-related domains, this paper focuses on analysing the feature space of a DNN by proposing a decoder that can generate images whose features are guaranteed to closely match a user-specified feature. Owing to this guarantee that is missed in past studies, our decoder allows us to evidence which of various attributes in an image are encoded into a feature by th…

Interview with Lovable CEO Anton Osika on competition, staying in Europe, and more; the company now has 2.3M active users, including 180K paying subscribers (Dominic-Madori Davis/TechCrunch)
https://techcrunch.com/2025/09/01/lovables-ceo-is…

Lovable's CEO isn't too worried about the vibe-coding competition | TechCrunch
Lovable specializes in helping people build apps and websites, especially people with no coding experience. It's one of the standouts in the popular AI category known as vibe-coding, which lets users guide AI models as they produce code, websites, or whole applications.

Failure Prediction Is a Better Performance Proxy for Early-Exit Networks Than Calibration
Piotr Kubaty, Filip Szatkowski, Metod Jazbec, Bartosz W\'ojcik
https://arxiv.org/abs/2508.21495

Failure Prediction Is a Better Performance Proxy for Early-Exit Networks Than Calibration
Early-exit models speed up inference by attaching internal classifiers to intermediate layers of the model and allowing computation to stop once a prediction satisfies an exit criterion. Most early-exit methods rely on confidence-based exit strategies, which motivated some works to calibrate intermediate classifiers to improve the performance of the entire model. In this paper, we show that calibration measures can be misleading indicators of the performance of multi-exit models: a well-calibra…

Simple explanation of apparent Bell nonlocality of unentangled photons
Antoni W\'ojcik, Jan W\'ojcik
https://arxiv.org/abs/2509.03127 https://arxiv…

Simple explanation of apparent Bell nonlocality of unentangled photons
Wang et al. [Science Advances, 1 Aug 2025 Vol 11, Issue 31] recently reported an experiment that they interpret as demonstrating a violation of Bell's inequality using unentangled photons. Such a claim is highly controversial, since it is well established that product states cannot surpass the bounds set by local hidden variable models. In this manuscript, we analyze the essential features of the experiment through simplified, idealized scenarios. Our analysis shows that the apparent violation …

🌾 Barley's mosaic origin traced to five wild populations and millennia of human involvement
https://phys.org/news/2025-09-barley-mosaic-wild-populations-millennia.html

Barley's mosaic origin traced to five wild populations and millennia of human involvement
Barley is one of the world's oldest cultivated plants, farmed for more than 10,000 years. Scientists have long believed it was domesticated in just one location. An international research team led by the IPK Leibniz Institute has revealed that modern barley has a "mosaic origin," meaning it stems from several wild populations across the Fertile Crescent. The paper is published in the journal Nature.

OASIS: Harnessing Diffusion Adversarial Network for Ocean Salinity Imputation using Sparse Drifter Trajectories
Bo Li, Yingqi Feng, Ming Jin, Xin Zheng, Yufei Tang, Laurent Cherubin, Alan Wee-Chung Liew, Can Wang, Qinghua Lu, Jingwei Yao, Shirui Pan, Hong Zhang, Xingquan Zhu
https://arxiv.org/abs/2508.21570…

OASIS: Harnessing Diffusion Adversarial Network for Ocean Salinity Imputation using Sparse Drifter Trajectories
Ocean salinity plays a vital role in circulation, climate, and marine ecosystems, yet its measurement is often sparse, irregular, and noisy, especially in drifter-based datasets. Traditional approaches, such as remote sensing and optimal interpolation, rely on linearity and stationarity, and are limited by cloud cover, sensor drift, and low satellite revisit rates. While machine learning models offer flexibility, they often fail under severe sparsity and lack principled ways to incorporate phys…