Tootfinder

https://front-end.social/@robinwhittleton/114732299673251508
I saw “violated” in scare quotes and decided this was not a serious question so I moved on with my day. Glad to see Pat is holding down the fort.

Robin Whittleton (@robinwhittleton@front-end.social)
Attached: 1 image Wisdom from @patrick_h_lauke@mastodon.social as per usual.

The Hitchhiker's Guide to Efficient, End-to-End, and Tight DP Auditing
Meenatchi Sundaram Muthu Selva Annamalai, Borja Balle, Jamie Hayes, Georgios Kaissis, Emiliano De Cristofaro
https://arxiv.org/abs/2506.16666

The Hitchhiker's Guide to Efficient, End-to-End, and Tight DP Auditing
This paper systematizes research on auditing Differential Privacy (DP) techniques, aiming to identify key insights into the current state of the art and open challenges. First, we introduce a comprehensive framework for reviewing work in the field and establish three cross-contextual desiderata that DP audits should target--namely, efficiency, end-to-end-ness, and tightness. Then, we systematize the modes of operation of state-of-the-art DP auditing techniques, including threat models, attacks,…

Tight End Battle: 2025 Cowboys Could See a Shake-Up https://insidethestar.com/tight-end-battle-2025-cowboys-could-see-a-shake-up

Republicans in Congress illegally vote to end clean air rules they can't actually end | Electrek https://electrek.co/2025/05/22/republicans-in-congress-illegally-vote-to-end-clean-air-rules-they-cant-actually-end/

LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical Images
Chenyue Song, Chen Hui, Qing Lin, Wei Zhang, Siqiao Li, Shengping Zhang, Haiqi Zhu, Zhixuan Li, Shaohui Liu, Feng Jiang, Xiang Li
https://arxiv.org/abs/2506.17983

LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical Images
Autoregressive Initial Bits is a framework that integrates sub-image autoregression and latent variable modeling, demonstrating its advantages in lossless medical image compression. However, in existing methods, the image segmentation process leads to an even distribution of latent variable information across each sub-image, which in turn causes posterior collapse and inefficient utilization of latent variables. To deal with these issues, we propose a prediction-based end-to-end lossless medica…

Trump Administration To End Protections for 58 Million Acres of National Forests | Portside
https://portside.org/2025-06-23/trump-administration-end-protections-58-million-acres-national-forests

Trump Administration to End Protections for 58 Million Acres of National Forests (Lisa Friedman/New York Times)
https://www.nytimes.com/2025/06/23/climate/trump-end-protections-for-58-million-acres-of-national-forests.html
http://www.memeorandum.com/250623/p160#a250623p160

Ende des Liveblogs
Wir beenden den Liveblog für heute. Vielen Dank für die Aufmerksamkeit.
📑 https://www.tagesschau.de/newsticker/liveblog-ukraine-mittwoch-516.html?at_medium=mastodon&at_cam…

Ukraine-Liveblog: ++ Kiew und Moskau vereinbaren Gefangenenaustausch ++
Unterhändler aus Kiew und Moskau haben bei ihren Gesprächen in der Türkei offenbar einen weiteren Gefangenenaustausch vereinbart. Israel und die Ukraine wollen gemeinsam gegen die Bedrohung aus dem Iran vorgehen. Der Liveblog vom Mittwoch zum Nachlesen.

Fully analog end-to-end online training with real-time adaptibility on integrated photonic platform
Zhimu Guo, A. Aadhi, Adam N. McCaughan, Alexander N. Tait, Nathan Youngblood, Sonia M. Buckley, Bhavin J. Shastri
https://arxiv.org/abs/2506.18041

Fully analog end-to-end online training with real-time adaptibility on integrated photonic platform
Analog neuromorphic photonic processors are uniquely positioned to harness the ultrafast bandwidth and inherent parallelism of light, enabling scalability, on-chip integration and significant improvement in computational performance. However, major challenges remain unresolved especially in achieving real-time online training, efficient end-to-end anolog systems, and adaptive learning for dynamical environmental changes. Here, we demonstrate an on-chip photonic analog end-to-end adaptive learni…

TCDiff : An End-to-end Trajectory-Controllable Diffusion Model for Harmonious Music-Driven Group Choreography
Yuqin Dai, Wanlu Zhu, Ronghui Li, Xiu Li, Zhenyu Zhang, Jun Li, Jian Yang
https://arxiv.org/abs/2506.18671

TCDiff++: An End-to-end Trajectory-Controllable Diffusion Model for Harmonious Music-Driven Group Choreography
Music-driven dance generation has garnered significant attention due to its wide range of industrial applications, particularly in the creation of group choreography. During the group dance generation process, however, most existing methods still face three primary issues: multi-dancer collisions, single-dancer foot sliding and abrupt swapping in the generation of long group dance. In this paper, we propose TCDiff++, a music-driven end-to-end framework designed to generate harmonious group danc…