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Did you miss today’s #MediaEdClub webinar, “Privacy, Power, and Platforms?” Check out the archived / recorded video and all related links:
https://mediaeducationlab.com/events/pri…

Exploring Exponential Runge-Kutta Methods: A Survey
Alessia and\`o, Nicol\`o Cangiotti, Mattia Sensi
https://arxiv.org/abs/2507.04024 https://

Exploring Exponential Runge-Kutta Methods: A Survey
In this survey, we provide an in-depth investigation of exponential Runge-Kutta methods for the numerical integration of initial-value problems. These methods offer a valuable synthesis between classical Runge-Kutta methods, introduced more than a century ago, and exponential integrators, which date back to the 1960s. This manuscript presents both a historical analysis of the development of these methods up to the present day and several examples aimed at making the topic accessible to a broad …

Alternative digitale Infrastrukturen statt Abhängigkeit von US-Tech-Riesen: Das Fediverse und offene Mediatheken könnten laut @… zum Grundstein einer demokratischen Digitalzukunft werden. Warum gerade Unis und nicht nur die jetzt handeln müssen bei #9vor9.

Mehr als Rentnersocial: Unis und Mediatheken sollen Fediverse bekannt machen #9vor9
Während Milliarden Menschen auf Meta, X und TikTok unterwegs sind, setzen wenige auf dezentrale Alternativen wie das Fediverse. Leonhard Dobusch warnt: Die Zeit drängt, um unabhängige digitale Infr…

Reusing Trajectories in Policy Gradients Enables Fast Convergence
Alessandro Montenegro, Federico Mansutti, Marco Mussi, Matteo Papini, Alberto Maria Metelli
https://arxiv.org/abs/2506.06178

Reusing Trajectories in Policy Gradients Enables Fast Convergence
Policy gradient (PG) methods are a class of effective reinforcement learning algorithms, particularly when dealing with continuous control problems. These methods learn the parameters of parametric policies via stochastic gradient ascent, typically using on-policy trajectory data to estimate the policy gradient. However, such reliance on fresh data makes them sample-inefficient. Indeed, vanilla PG methods require $O(ε^{-2})$ trajectories to reach an $ε$-approximate stationary point. A common …

Slides for today's #MediaEdLab #MediaEdClub webinar on "Privacy, Power and Platforms"
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Privacy, Power, and Platforms - MediaEd Club (7 July 2025) by wesfryer.com
Privacy, Power, and Platforms 7 July 2025 Facilitated by Wes Fryer mediaeducationlab.com/mediaed-club/upcoming-meetings

Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safety
Seongmin Lee, Aeree Cho, Grace C. Kim, ShengYun Peng, Mansi Phute, Duen Horng Chau
https://arxiv.org/abs/2506.05451

Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safety
As large language models (LLMs) see wider real-world use, understanding and mitigating their unsafe behaviors is critical. Interpretation techniques can reveal causes of unsafe outputs and guide safety, but such connections with safety are often overlooked in prior surveys. We present the first survey that bridges this gap, introducing a unified framework that connects safety-focused interpretation methods, the safety enhancements they inform, and the tools that operationalize them. Our novel t…

What Shapes User Trust in ChatGPT? A Mixed-Methods Study of User Attributes, Trust Dimensions, Task Context, and Societal Perceptions among University Students
Kadija Bouyzourn, Alexandra Birch
https://arxiv.org/abs/2507.05046

What Shapes User Trust in ChatGPT? A Mixed-Methods Study of User Attributes, Trust Dimensions, Task Context, and Societal Perceptions among University Students
This mixed-methods inquiry examined four domains that shape university students' trust in ChatGPT: user attributes, seven delineated trust dimensions, task context, and perceived societal impact. Data were collected through a survey of 115 UK undergraduate and postgraduate students and four complementary semi-structured interviews. Behavioural engagement outweighed demographics: frequent use increased trust, whereas self-reported understanding of large-language-model mechanics reduced it. Among…

Adaptive Multiquadratic Radial Basis Function-based Explicit Runge--Kutta Methods
Rajesh Yadav, Deepak Kumar Yadav, Alpesh Kumar
https://arxiv.org/abs/2507.04261

Adaptive Multiquadratic Radial Basis Function-based Explicit Runge--Kutta Methods
Runge--Kutta (RK) methods are widely used techniques for solving a class of initial value problems. In this article, we introduce an adaptive multiquadratic (MQ) radial basis function (RBF)-based method to develop enhanced explicit RK methods. These methods achieve a higher order of convergence than the corresponding classical RK methods. To improve the local convergence of the numerical solution, we optimize the free parameters (shape functions) involved in the RBFs by forcing the local trunca…

Entropy stable high-order discontinuous Galerkin spectral-element methods on curvilinear, hybrid meshes
Jens Keim, Anna Schwarz, Patrick Kopper, Marcel Blind, Christian Rohde, Andrea Beck
https://arxiv.org/abs/2507.04334

Entropy stable high-order discontinuous Galerkin spectral-element methods on curvilinear, hybrid meshes
Hyperbolic-parabolic partial differential equations are widely used for the modeling of complex, multiscale problems. High-order methods such as the discontinuous Galerkin (DG) scheme are attractive candidates for their numerical approximation. However, high-order methods are prone to instabilities in the presence of underresolved flow features. A popular counter measure to stabilize DG methods is the use of entropy-stable formulations based on summation-by-parts (SBP) operators. The present pa…

Paired Explicit Relaxation Runge-Kutta Methods: Entropy-Conservative and Entropy-Stable High-Order Optimized Multirate Time Integration
Daniel Doehring, Hendrik Ranocha, Manuel Torrilhon
https://arxiv.org/abs/2507.04991

Paired Explicit Relaxation Runge-Kutta Methods: Entropy-Conservative and Entropy-Stable High-Order Optimized Multirate Time Integration
We present novel entropy-conservative and entropy-stable multirate Runge-Kutta methods based on Paired Explicit Runge-Kutta (P-ERK) with relaxation for conservation laws and related systems of partial differential equations. Optimized schemes up to fourth-order of accuracy are derived and validated in terms of order of consistency, conservation of linear invariants, and entropy conservation/stability. We demonstrate the effectiveness of these P-ERRK methods when combined with a high-order, entr…