Tootfinder

🤩 The latest Safari 26 Beta does not disappoint in terms of #CSS features:
⚓️ Anchor Positioning!
🪄 Scroll-driven animations!
🌯 text-wrap: pretty!
🌈 contrast-color()!
⏲️ progress()!
and more!
And this sentence: “We value the principles of progressive enhancement and separation of concerns.” 😉
Great work, @…

News from WWDC25: WebKit in Safari 26 beta
Welcome to WWDC25!

#PhantastikPrompts 10.06.:
Wie hältst du es mit geschlechtergerechter Sprache?
Wer bei mir mitliest, dürfte gesehen haben, dass ich nach Möglichkeit neutrale Formen verwende (und wo es sich absolut nicht ausgeht damit, den Stern verwende). Bis hin dazu, dass ich sowohl für den Eigengebrauch, als auch für den Fremdgebrauch und die Romanwelt ein paar Neologismen geschaffen ha…

This https://arxiv.org/abs/2506.05678 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Numerical Investigation of Sequence Modeling Theory using Controllable Memory Functions
The evolution of sequence modeling architectures, from recurrent neural networks and convolutional models to Transformers and structured state-space models, reflects ongoing efforts to address the diverse temporal dependencies inherent in sequential data. Despite this progress, systematically characterizing the strengths and limitations of these architectures remains a fundamental challenge.In this work, we propose a synthetic benchmarking framework to evaluate how effectively different sequenc…

This https://arxiv.org/abs/2404.08578 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Classification and nonexistence for $t$-structures on derived categories of schemes
This work establishes new results on the classification of $t$-structures for many subcategories of the derived category of quasi-coherent sheaves on a Noetherian scheme. Our work makes progress in two different directions. On one hand, we provide an improvement of a result of Takahashi on $t$-structures, generalizing it to the case of the bounded derived category of coherent sheaves on a quasi-compact CM-excellent scheme of finite Krull dimension. On the other hand, via independent techniques,…

Slow progress the last couple days because I've been going into the office for work and the commute is eating up my time I'd otherwise spend on such things.
But now it's the weekend and the switch engine board is coming together nicely.
Still have 514 nets to route - mostly the supervisor, line card management buses, and power supply but also some other odds and ends like the FPGA JTAG and part of the SPI flash.
Also I have to get the tach/PWM signals from the m…

Repeating Flares, X-ray Outbursts and Delayed Infrared Emission: A Comprehensive Compilation of Optical Tidal Disruption Events
D. A. Langis, I. Liodakis, K. I. I. Koljonen, A. Paggi, N. Globus, L. Wyrzykowski, P. J. Miko{\l}ajczyk, K. Kotysz, P. Zieli\'nski, N. Ihanec, J. Ding, D. Morshed, Z. Torres
https://arxiv.org/abs/25…

Repeating Flares, X-ray Outbursts and Delayed Infrared Emission: A Comprehensive Compilation of Optical Tidal Disruption Events
Tidal disruption events (TDEs) have been proposed as valuable laboratories for studying dormant black holes. However, progress in this field has been hampered by the limited number of observed events. In this work, we present TDECat, a comprehensive catalogue of 134 confirmed TDEs (131 optical TDEs and 3 jetted TDEs) discovered up to the end of 2024, accompanied by multi-wavelength photometry (X-ray, UV, optical, and IR) and publicly available spectra. We also study the statistical properties, …

Dyna-Think: Synergizing Reasoning, Acting, and World Model Simulation in AI Agents
Xiao Yu, Baolin Peng, Ruize Xu, Michel Galley, Hao Cheng, Suman Nath, Jianfeng Gao, Zhou Yu
https://arxiv.org/abs/2506.00320

Dyna-Think: Synergizing Reasoning, Acting, and World Model Simulation in AI Agents
Recent progress in reasoning with large language models (LLMs), such as DeepSeek-R1, demonstrates impressive capabilities in domains like mathematics and coding, by exhibiting complex cognitive behaviors such as verification, goal decomposition, and self-reflection. However, it is unclear what behavior is effective and what behavior is missing for long-horizon AI agents tasks. In this work, we propose Dyna-Think, a thinking framework that integrates planning with an internal world model with re…

This https://arxiv.org/abs/2405.08719 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Addressing Misspecification in Simulation-based Inference through Data-driven Calibration
Driven by steady progress in deep generative modeling, simulation-based inference (SBI) has emerged as the workhorse for inferring the parameters of stochastic simulators. However, recent work has demonstrated that model misspecification can compromise the reliability of SBI, preventing its adoption in important applications where only misspecified simulators are available. This work introduces robust posterior estimation~(RoPE), a framework that overcomes model misspecification with a small re…

Pride progress? As gay pro athletes consider coming out, each announcement makes a mark https://www.nytimes.com/athletic/6396179/2025/06/03/pride-month-gay-pro-athletes-evolution/

What is the difference between Microsoft Copilot and a Microsoft Copilot laptop??
This article is useful in light of yesterday's news about them bringing back Recall on Copilot hardware:
https://www.wired.com/story/what-is-copilot-plus-pc/
There a…

During work (no technical hanky panky)

I mean, I don't usually write happy songs, but this looks good so far, right?

This https://arxiv.org/abs/2503.09532 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability
Sparse autoencoders (SAEs) are a popular technique for interpreting language model activations, and there is extensive recent work on improving SAE effectiveness. However, most prior work evaluates progress using unsupervised proxy metrics with unclear practical relevance. We introduce SAEBench, a comprehensive evaluation suite that measures SAE performance across eight diverse metrics, spanning interpretability, feature disentanglement and practical applications like unlearning. To enable syst…

Done some more work with the VR animation engine today.
Seems to now be working that I can lay in the path that the character will walk, and then puppet their limbs as they walk it.
Done more work to standardize how all the slapdash episode structure is so now there's also a #wip #starshipsd #gamedev

Oh hey, it's #ScreenshotSaturday , here's the latest mockup from the video game adaptation of Battle of Tarot I'm working on with some lovely people.
Everything is still a work-in-progress and not final at all, but trying to get the visual style nailed down.
#GameDev

Work-in-Progress: Multi-Deadline DAG Scheduling Model for Autonomous Driving Systems
Atsushi Yano, Takuya Azumi
https://arxiv.org/abs/2505.06780 https://…

Work-in-Progress: Multi-Deadline DAG Scheduling Model for Autonomous Driving Systems
Autoware is an autonomous driving system implemented on Robot Operation System (ROS) 2, where an end-to-end timing guarantee is crucial to ensure safety. However, existing ROS 2 cause-effect chain models for analyzing end-to-end latency struggle to accurately represent the complexities of Autoware, particularly regarding sync callbacks, queue consumption patterns, and feedback loops. To address these problems, we propose a new scheduling model that decomposes the end-to-end timing constraints o…

This https://arxiv.org/abs/2505.06780 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csOS_…

Work-in-Progress: Multi-Deadline DAG Scheduling Model for Autonomous Driving Systems
Autoware is an autonomous driving system implemented on Robot Operation System (ROS) 2, where an end-to-end timing guarantee is crucial to ensure safety. However, existing ROS 2 cause-effect chain models for analyzing end-to-end latency struggle to accurately represent the complexities of Autoware, particularly regarding sync callbacks, queue consumption patterns, and feedback loops. To address these problems, we propose a new scheduling model that decomposes the end-to-end timing constraints o…