Tootfinder

“Spain's Prime Minister Pedro Sanchez said on Wednesday he will join Italy in sending a military warship to protect an international flotilla seeking to deliver aid to Gaza after it was attacked by drones off Greece.”
Finally! Thank you!
This is what we need. This is the only language Israel understands.
Now, let’s start talking about a UN peacekeeping mission to Palestine. Or, if the UN is no longer fit for purpose, a coalition of countries that will use military inter…

Hello Fedi tech support desk, I wonder if you can help.
Next week I will need to join a Teams meeting from my Linux laptop.
How well does this work using the Teams web interface? Will I need to run Chrome or will Firefox or (at worst) Chromium do the job?
And do I need to sign in to Microsoft dot com first, or can I just rock up with the Teams call details and enter a name and things will just work?
#Teams #Linux #Microsoft

Instruction Boundary: Quantifying Biases in LLM Reasoning under Various Coverage
Zipeng Ling, Yuehao Tang, Chen Huang, Shuliang Liu, Gaoyang Jiang, Shenghong Fu, Junqi Yang, Yao Wan, Jiawan Zhang, Kejia Huang, Xuming Hu
https://arxiv.org/abs/2509.20278

Instruction Boundary: Quantifying Biases in LLM Reasoning under Various Coverage
Large-language-model (LLM) reasoning has long been regarded as a powerful tool for problem solving across domains, providing non-experts with valuable advice. However, their limitations - especially those stemming from prompt design - remain underexplored. Because users may supply biased or incomplete prompts - often unintentionally - LLMs can be misled, undermining reliability and creating risks. We refer to this vulnerability as the Instruction Boundary. To investigate the phenomenon, we dist…

@…
©️: I’m mistakenly under the impression that the date attached to this thing should be updated every Jan 1st, despite the work being from sometime in the past.
™️: I came up with a really clever word/phrase and I’d hate for you to use it.
®️: I’m a pompous corporation and my lawyers tell me to put this everywhere I go.

SADA: Stability-guided Adaptive Diffusion Acceleration
Ting Jiang, Yixiao Wang, Hancheng Ye, Zishan Shao, Jingwei Sun, Jingyang Zhang, Zekai Chen, Jianyi Zhang, Yiran Chen, Hai Li
https://arxiv.org/abs/2507.17135

SADA: Stability-guided Adaptive Diffusion Acceleration
Diffusion models have achieved remarkable success in generative tasks but suffer from high computational costs due to their iterative sampling process and quadratic attention costs. Existing training-free acceleration strategies that reduce per-step computation cost, while effectively reducing sampling time, demonstrate low faithfulness compared to the original baseline. We hypothesize that this fidelity gap arises because (a) different prompts correspond to varying denoising trajectory, and (b…

#EroticMusings 17: Do you show off most of what you make, or often practice your craft on things that never get seen by anyone else?
I show most of what I make. I'm too tired and have too little energy for creative endeavours that are not meant to be shared with the public at some point.
My test readers and a couple of artists get to see the WIP including the ugly stages. C…

Generating Cylindrical Vector {\gamma} Rays via Beam-Target Interactions: Towards Structured Light at High Energies
Yue Cao, Kun Xue, Si-Man Liu, Zhong-Peng Li, Li-Xiang Hu, Xin-Yu Liu, Zhen-Ke Dou, Feng Wan, Qian Zhao, Tong-Pu Yu, Jian-Xing Li
https://arxiv.org/abs/2508.16220

Generating Cylindrical Vector γ Rays via Beam-Target Interactions: Towards Structured Light at High Energies
Structured γ rays, particularly cylindrical vector γ rays, offer promising tools for sub-nuclear imaging and polarization-sensitive probes in fundamental research and applications, but conventional optical methods face great challenges at such photon energy. Here, we put forward a novel method generating such γ rays through relativistic beam-target interactions. For instance, radially polarized γ rays can be generated by using a dense electron beam striking a multifoil target. We find that …

Eva-VLA: Evaluating Vision-Language-Action Models' Robustness Under Real-World Physical Variations
Hanqing Liu, Jiahuan Long, Junqi Wu, Jiacheng Hou, Huili Tang, Tingsong Jiang, Weien Zhou, Wen Yao
https://arxiv.org/abs/2509.18953

Analysis of the Under-Sampling Effect for AI-based Dynamic Gravimeter
Wen-Zhang Wang, Xi Chen, Jin-ting Li, Dan-fang Zhang, Wei-hao Xu, Jia-yi Wei, Jia-qi Zhong, Biao Tang, Lin Zhou, Jin Wang, Ming-Sheng Zhan
https://arxiv.org/abs/2508.17765