Tootfinder

@… following up on our chat at #SDSL2025, I finally found some time to see how a #QGIS Processing Algorithm Provider plugin can be unit tested. Here's what I've …

trajectools/tests/test_run_algs.py at main
trajectools - Trajectools - trajectory data analysis tools for the QGIS Processing toolbox | Previous home: https://github.com/movingpandas/qgis-trajectools

When Instructions Multiply: Measuring and Estimating LLM Capabilities of Multiple Instructions Following
Keno Harada, Yudai Yamazaki, Masachika Taniguchi, Edison Marrese-Taylor, Takeshi Kojima, Yusuke Iwasawa, Yutaka Matsuo
https://arxiv.org/abs/2509.21051

When Instructions Multiply: Measuring and Estimating LLM Capabilities of Multiple Instructions Following
As large language models (LLMs) are increasingly applied to real-world scenarios, it becomes crucial to understand their ability to follow multiple instructions simultaneously. To systematically evaluate these capabilities, we introduce two specialized benchmarks for fundamental domains where multiple instructions following is important: Many Instruction-Following Eval (ManyIFEval) for text generation with up to ten instructions, and Style-aware Mostly Basic Programming Problems (StyleMBPP) for…

Abuse in Buddhism: The Law of Silence https://openbuddhism.org/library/videos/2022/elodie-emery-wandrille-lanos-present-buddhism-the-unspeakable-truth/

‘Abuse in Buddhism: The Law of Silence’
In a brief video in English, the French filmmakers Élodie Emery and Wandrille Lanos introduce their documentary ‘Abuse in Buddhism: The Law of Silence’ (Arte, 2022). It can be watched here.

Optimal Robust Recourse with $L^p$-Bounded Model Change
Phone Kyaw, Kshitij Kayastha, Shahin Jabbari
https://arxiv.org/abs/2509.21293 https://arxiv.org/pdf…

Optimal Robust Recourse with $L^p$-Bounded Model Change
Recourse provides individuals who received undesirable labels (e.g., denied a loan) from algorithmic decision-making systems with a minimum-cost improvement suggestion to achieve the desired outcome. However, in practice, models often get updated to reflect changes in the data distribution or environment, invalidating the recourse recommendations (i.e., following the recourse will not lead to the desirable outcome). The robust recourse literature addresses this issue by providing a framework fo…

'Bigger, hotter, faster': Extreme blazes drive rise in CO₂ fire emissions #environment

'Bigger, hotter, faster': Extreme blazes drive rise in CO₂ fire emissions
Rampant wildfires in the Americas drove a jump in global greenhouse gas emissions from fires in the year to February, new research found Thursday, warning that climate change was fanning the flames.

The Unwinnable Arms Race of AI Image Detection
Till Aczel, Lorenzo Vettor, Andreas Plesner, Roger Wattenhofer
https://arxiv.org/abs/2509.21135 https://arxi…

The Unwinnable Arms Race of AI Image Detection
The rapid progress of image generative AI has blurred the boundary between synthetic and real images, fueling an arms race between generators and discriminators. This paper investigates the conditions under which discriminators are most disadvantaged in this competition. We analyze two key factors: data dimensionality and data complexity. While increased dimensionality often strengthens the discriminators ability to detect subtle inconsistencies, complexity introduces a more nuanced effect. Usi…

Georgia court filing organization warns of outages after ransomware allegations https://therecord.media/georgia-court-filing-org-ransomware-warning

Niners WR Jauan Jennings strikes Panther safety Tre'Von Moehrig postgame following in-game low blow https://www.nfl.com/news/niners-wr-jauan-jennings-strikes-panther-safety-tre-von-moehrig-postgame-following-in-game-l…

NewtonGen: Physics-Consistent and Controllable Text-to-Video Generation via Neural Newtonian Dynamics
Yu Yuan, Xijun Wang, Tharindu Wickremasinghe, Zeeshan Nadir, Bole Ma, Stanley H. Chan
https://arxiv.org/abs/2509.21309

NewtonGen: Physics-Consistent and Controllable Text-to-Video Generation via Neural Newtonian Dynamics
A primary bottleneck in large-scale text-to-video generation today is physical consistency and controllability. Despite recent advances, state-of-the-art models often produce unrealistic motions, such as objects falling upward, or abrupt changes in velocity and direction. Moreover, these models lack precise parameter control, struggling to generate physically consistent dynamics under different initial conditions. We argue that this fundamental limitation stems from current models learning moti…