Tootfinder

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Lou Ragland:
🎵 Understand Each Other
#LouRagland
https://louragland.bandcamp.com/album/is-the-conveyor-understand-each-other
https://open.spotify.com/track/5l0ALYNkNb6BBgc782NyDz

Raiders' success largely depends on unproven offensive line https://www.foxsports.com/articles/nfl/raiders-success-largely-depends-on-unproven-offensive-line

Damn, this is a treasure trove!
(Also no clue where this was, but DZPK suggests #LowerSilesia. 2017.)
#Poland #Engrish

🇺🇦 #NowPlaying on BBCRadio3's #LateJunction
Lori Goldston:
🎵 Still Standing Round
#LoriGoldston
https://open.spotify.com/track/6lXpWOBmXYoXxYgWuiBDgU

Updated 10 posts on my site, largely linking to these:
• Joe’s underlines: https://www.joedolson.com/2025/10/why-wordpress-themes-require-underlines-on-links/
• Alice’s treatise:

Why WordPress Themes Require Underlines on Links - Joe Dolson Web Accessibility
Jeff Chandler posted a link in the Post Status Slack yesterday leading to an article complaining about the underlined link requirement for WordPress

I like to play around as an anonymous commenter in online newspaper columns. If you point out the biases of #AI systems, the comment gets deleted because it is considered too polemical.
The comment was addressing an article about AI in public service and the use in refugee applications 🫣

It's fascinating that we largely went from a network of personal computers processing data locally that could access an open hypertext system linking together millions of websites…
…to phones with proprietary closed apps that often largely are little more than little windows to timesharing mainframes.

Panthers quarterback Bryce Young ruled out vs. Jets with ankle injury https://www.nytimes.com/athletic/6731324/2025/10/19/bryce-young-panthers-ankle-injury-update/

Adversarial Generation and Collaborative Evolution of Safety-Critical Scenarios for Autonomous Vehicles
Jiangfan Liu, Yongkang Guo, Fangzhi Zhong, Tianyuan Zhang, Zonglei Jing, Siyuan Liang, Jiakai Wang, Mingchuan Zhang, Aishan Liu, Xianglong Liu
https://arxiv.org/abs/2508.14527

Adversarial Generation and Collaborative Evolution of Safety-Critical Scenarios for Autonomous Vehicles
The generation of safety-critical scenarios in simulation has become increasingly crucial for safety evaluation in autonomous vehicles prior to road deployment in society. However, current approaches largely rely on predefined threat patterns or rule-based strategies, which limit their ability to expose diverse and unforeseen failure modes. To overcome these, we propose ScenGE, a framework that can generate plentiful safety-critical scenarios by reasoning novel adversarial cases and then amplif…

SMTrack: End-to-End Trained Spiking Neural Networks for Multi-Object Tracking in RGB Videos
Pengzhi Zhong, Xinzhe Wang, Dan Zeng, Qihua Zhou, Feixiang He, Shuiwang Li
https://arxiv.org/abs/2508.14607

SMTrack: End-to-End Trained Spiking Neural Networks for Multi-Object Tracking in RGB Videos
Brain-inspired Spiking Neural Networks (SNNs) exhibit significant potential for low-power computation, yet their application in visual tasks remains largely confined to image classification, object detection, and event-based tracking. In contrast, real-world vision systems still widely use conventional RGB video streams, where the potential of directly-trained SNNs for complex temporal tasks such as multi-object tracking (MOT) remains underexplored. To address this challenge, we propose SMTrack…