Tootfinder

Im heutigen dritten Teil der Serie habe ich einen ungewöhnlichen Trick ausprobiert, um regelmäßig eine neue Wegwerf-Handynummer zu haben: Das Portierungskarussel
https://www.kuketz-blog.de/das-portierungskarussell-wegwerfnummern-teil-3/
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Das Portierungskarussell – Wegwerfnummern Teil 3
Ein Trick, wie man regelmäßig eine Nummer zwischen zwei SIM-Karten weitergeben kann, um dadurch einfach und kostenlos eine neue Nummer zu erhalten.

I don't think I'll read anything funnier today. https://www.theguardian.com/uk-news/2025/aug/13/over-46000-public-bodies-spurned-offer-of-free-king-charles-portrait

LIA-X: Interpretable Latent Portrait Animator
Yaohui Wang, Di Yang, Xinyuan Chen, Francois Bremond, Yu Qiao, Antitza Dantcheva
https://arxiv.org/abs/2508.09959 https://

LIA-X: Interpretable Latent Portrait Animator
We introduce LIA-X, a novel interpretable portrait animator designed to transfer facial dynamics from a driving video to a source portrait with fine-grained control. LIA-X is an autoencoder that models motion transfer as a linear navigation of motion codes in latent space. Crucially, it incorporates a novel Sparse Motion Dictionary that enables the model to disentangle facial dynamics into interpretable factors. Deviating from previous 'warp-render' approaches, the interpretability of the Spars…

Memory Decoder: A Pretrained, Plug-and-Play Memory for Large Language Models
Jiaqi Cao, Jiarui Wang, Rubin Wei, Qipeng Guo, Kai Chen, Bowen Zhou, Zhouhan Lin
https://arxiv.org/abs/2508.09874

Memory Decoder: A Pretrained, Plug-and-Play Memory for Large Language Models
Large Language Models (LLMs) have shown strong abilities in general language tasks, yet adapting them to specific domains remains a challenge. Current method like Domain Adaptive Pretraining (DAPT) requires costly full-parameter training and suffers from catastrophic forgetting. Meanwhile, Retrieval-Augmented Generation (RAG) introduces substantial inference latency due to expensive nearest-neighbor searches and longer context. This paper introduces Memory Decoder, a plug-and-play pretrained me…

Convergent perturbative series via finite path integral limits: application to energy at strong coupling of the anharmonic oscillator
Ariel Edery
https://arxiv.org/abs/2507.08782 …

Convergent perturbative series via finite path integral limits: application to energy at strong coupling of the anharmonic oscillator
Solving quantum field theories at strong coupling remains a challenging task. The main issue is that the usual perturbative series are asymptotic series which can be useful at weak coupling but break down completely at strong coupling. In this work, we show that if the limits of integration in the path integral are finite, the perturbative series is remarkably an absolutely convergent series which works well at strong coupling. For now, we apply this perturbative approach to $λ\,ϕ^4$ theory i…

Smithsonian Museum Director Trump Said He Fired Decides to Step Down (New York Times)
https://www.nytimes.com/2025/06/13/arts/design/kim-sajet-resigns-smithsonian-national-portrait-gallery.html
http://www.memeorandum.com/250614/p7#a250614p7

No Free Lunch from Audio Pretraining in Bioacoustics: A Benchmark Study of Embeddings
Chenggang Chen, Zhiyu Yang
https://arxiv.org/abs/2508.10230 https://a…

No Free Lunch from Audio Pretraining in Bioacoustics: A Benchmark Study of Embeddings
Bioacoustics, the study of animal sounds, offers a non-invasive method to monitor ecosystems. Extracting embeddings from audio-pretrained deep learning (DL) models without fine-tuning has become popular for obtaining bioacoustic features for tasks. However, a recent benchmark study reveals that while fine-tuned audio-pretrained VGG and transformer models achieve state-of-the-art performance in some tasks, they fail in others. This study benchmarks 11 DL models on the same tasks by reducing thei…