Tootfinder

Wer Trumps Rede in Davos gehört hat, wer ihn regelmäßig in den USA hört, der fragt sich unwillkürlich, ob Trump noch normal ist. Doch viele seiner Aussagen werden von den Medien „vernünftig gewaschen“. Was heißt das? Sie ziehen Aussagen heraus und präsentieren diese “vernünftig“ in journalistischem Stil. So erscheint #Trump in der Berichterstattung normaler, als er wirklich ist. | mehr bei Johanne…

"Sanewashing" im US-Wahlkampf: Wie der seriöse Journalismus Trumps Irrsinn normalisiert
Viele Medien stellen Donald Trump vernünftiger dar, als er ist. Kolumnist Johannes Franzen erklärt: Das liegt daran, dass sie sich an Regeln halten – und Trump nicht.

10 tracks randomly chosen from a list of 2112:
1. Judas Priest, “Crossfire”
2. Royal Blood, “Figure It Out”
3. Disturbed, “Down with the Sickness”
4. The Smiths, “Ask (Remix)”
5. Stone Temple Pilots, “Plush”
6. Smashing Pumpkins, “Tonight, Tonight”
7. Queen, “Princes of the Universe”
8. Hoodoo Gurus, “Like Wow—Wipeout!”
9. Dave Graney & the Coral Snakes, “You”re Just Too Hip, Baby”
10. Stone Temple Pilots, “Dead & Bloated”
…and…

🇺🇦 #NowPlaying on BBCRadio3's #NightTracks
Claude Debussy & Seong‐Jin Cho:
🎵 Children's Corner: The Little Shepherd
#ClaudeDebussy #SeongJinCho
https://open.spotify.com/track/25GVGBxjEFOgp3ulpytoWx

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[2/5]:
- The Diffusion Duality
Sahoo, Deschenaux, Gokaslan, Wang, Chiu, Kuleshov
https://arxiv.org/abs/2506.10892 https://mastoxiv.page/@arXiv_csLG_bot/114675526577078472
- Multimodal Representation Learning and Fusion
Jin, Ge, Xie, Luo, Song, Bi, Liang, Guan, Yeong, Song, Hao
https://arxiv.org/abs/2506.20494 https://mastoxiv.page/@arXiv_csLG_bot/114749113025183688
- The kernel of graph indices for vector search
Mariano Tepper, Ted Willke
https://arxiv.org/abs/2506.20584 https://mastoxiv.page/@arXiv_csLG_bot/114749118923266356
- OptScale: Probabilistic Optimality for Inference-time Scaling
Youkang Wang, Jian Wang, Rubing Chen, Xiao-Yong Wei
https://arxiv.org/abs/2506.22376 https://mastoxiv.page/@arXiv_csLG_bot/114771735361664528
- Boosting Revisited: Benchmarking and Advancing LP-Based Ensemble Methods
Fabian Akkerman, Julien Ferry, Christian Artigues, Emmanuel Hebrard, Thibaut Vidal
https://arxiv.org/abs/2507.18242 https://mastoxiv.page/@arXiv_csLG_bot/114913322736512937
- MolMark: Safeguarding Molecular Structures through Learnable Atom-Level Watermarking
Runwen Hu, Peilin Chen, Keyan Ding, Shiqi Wang
https://arxiv.org/abs/2508.17702 https://mastoxiv.page/@arXiv_csLG_bot/115095014405732247
- Dual-Distilled Heterogeneous Federated Learning with Adaptive Margins for Trainable Global Protot...
Fatema Siddika, Md Anwar Hossen, Wensheng Zhang, Anuj Sharma, Juan Pablo Mu\~noz, Ali Jannesari
https://arxiv.org/abs/2508.19009 https://mastoxiv.page/@arXiv_csLG_bot/115100269482762688
- STDiff: A State Transition Diffusion Framework for Time Series Imputation in Industrial Systems
Gary Simethy, Daniel Ortiz-Arroyo, Petar Durdevic
https://arxiv.org/abs/2508.19011 https://mastoxiv.page/@arXiv_csLG_bot/115100270137397046
- EEGDM: Learning EEG Representation with Latent Diffusion Model
Shaocong Wang, Tong Liu, Yihan Li, Ming Li, Kairui Wen, Pei Yang, Wenqi Ji, Minjing Yu, Yong-Jin Liu
https://arxiv.org/abs/2508.20705 https://mastoxiv.page/@arXiv_csLG_bot/115111565155687451
- Data-Free Continual Learning of Server Models in Model-Heterogeneous Cloud-Device Collaboration
Xiao Zhang, Zengzhe Chen, Yuan Yuan, Yifei Zou, Fuzhen Zhuang, Wenyu Jiao, Yuke Wang, Dongxiao Yu
https://arxiv.org/abs/2509.25977 https://mastoxiv.page/@arXiv_csLG_bot/115298721327100391
- Fine-Tuning Masked Diffusion for Provable Self-Correction
Jaeyeon Kim, Seunggeun Kim, Taekyun Lee, David Z. Pan, Hyeji Kim, Sham Kakade, Sitan Chen
https://arxiv.org/abs/2510.01384 https://mastoxiv.page/@arXiv_csLG_bot/115309690976554356
- A Generic Machine Learning Framework for Radio Frequency Fingerprinting
Alex Hiles, Bashar I. Ahmad
https://arxiv.org/abs/2510.09775 https://mastoxiv.page/@arXiv_csLG_bot/115372387779061015
- ASecond-Order SpikingSSM for Wearables
Kartikay Agrawal, Abhijeet Vikram, Vedant Sharma, Vaishnavi Nagabhushana, Ayon Borthakur
https://arxiv.org/abs/2510.14386 https://mastoxiv.page/@arXiv_csLG_bot/115389079527543821
- Utility-Diversity Aware Online Batch Selection for LLM Supervised Fine-tuning
Heming Zou, Yixiu Mao, Yun Qu, Qi Wang, Xiangyang Ji
https://arxiv.org/abs/2510.16882 https://mastoxiv.page/@arXiv_csLG_bot/115412243355962887
- Seeing Structural Failure Before it Happens: An Image-Based Physics-Informed Neural Network (PINN...
Omer Jauhar Khan, Sudais Khan, Hafeez Anwar, Shahzeb Khan, Shams Ul Arifeen
https://arxiv.org/abs/2510.23117 https://mastoxiv.page/@arXiv_csLG_bot/115451891042176876
- Training Deep Physics-Informed Kolmogorov-Arnold Networks
Spyros Rigas, Fotios Anagnostopoulos, Michalis Papachristou, Georgios Alexandridis
https://arxiv.org/abs/2510.23501 https://mastoxiv.page/@arXiv_csLG_bot/115451942159737549
- Semi-Supervised Preference Optimization with Limited Feedback
Seonggyun Lee, Sungjun Lim, Seojin Park, Soeun Cheon, Kyungwoo Song
https://arxiv.org/abs/2511.00040 https://mastoxiv.page/@arXiv_csLG_bot/115490555013124989
- Towards Causal Market Simulators
Dennis Thumm, Luis Ontaneda Mijares
https://arxiv.org/abs/2511.04469 https://mastoxiv.page/@arXiv_csLG_bot/115507943827841017
- Incremental Generation is Necessary and Sufficient for Universality in Flow-Based Modelling
Hossein Rouhvarzi, Anastasis Kratsios
https://arxiv.org/abs/2511.09902 https://mastoxiv.page/@arXiv_csLG_bot/115547587245365920
- Optimizing Mixture of Block Attention
Guangxuan Xiao, Junxian Guo, Kasra Mazaheri, Song Han
https://arxiv.org/abs/2511.11571 https://mastoxiv.page/@arXiv_csLG_bot/115564541392410174
- Assessing Automated Fact-Checking for Medical LLM Responses with Knowledge Graphs
Shasha Zhou, Mingyu Huang, Jack Cole, Charles Britton, Ming Yin, Jan Wolber, Ke Li
https://arxiv.org/abs/2511.12817 https://mastoxiv.page/@arXiv_csLG_bot/115570877730326947
toXiv_bot_toot

#konkurssit ja Orvon hiljaisuus

Ashley St. Clair, mother of one of Elon Musk's children, sues xAI, alleging Grok refused to stop making sexualized deepfakes of her, amid custody disputes (Peter Senzamici/New York Post)
https://nypost.com/2026/01/15/us-news/elon-musks-baby-…

Elon Musk’s baby mama Ashley St. Clair sues X for AI sex deepfakes: 'like this nightmare will never stop'
Elon Musk baby mama Ashley St. Clair is suing his AI platform, Grok, for refusing to stop making sexually explicit deepfake images of her — including phony pictures of her as a nude child — and the…

went thru my bookmarks and found BOOTED HARLEYDUDE. whyd i never go thru this kings site before???
http://bootedman.com/

TIL:
If you have your Samsung T7 Touch SSD encrypted with a password (and maybe a fingerprint) ..and you want to remove the encryption (or delete/change password/fingerprint).... Your device (MS Win) has to be connected to the internet. Otherwise the neccessary software just hangs after unlocking the SSD.
WTAF Samsung. For real.
This lead me to two questions:
1. What are the odds that passwords and fingerprints are casually transfered to some Samsung service? (Rhetor…

(LinkedIn) Job position: #Paradromics is looking for a heterogeneous integration engineer https://www.linkedin.com/feed/update/urn:li:activity:7415473562809102337/

#bci #mems #neurotechnology #semiconductor #packaging #integration #goblue | Dongxiao Yan
🚀 We’re Hiring: Senior Scientist / Engineer – Heterogeneous Integration Engineer 📍 Austin, TX (On-site) 💸 $1,000 referral bonus (NOT applicable to recruiters or agencies.) We’re looking for an exceptional scientist/engineer to bridge microfabrication and medical device packaging. This role owns the development and optimization of the critical interfaces between micromachined components (produced by precise micromachining, semiconductor fab, and/or MEMS fab) where performance is o…

My Samsung Android phone has a new, very annoying, 'feature' I'd like to turn off: if Bluetooth is on but no device connected, playing any audio media now immediately connects to the nearest paired device (which might be in another room). I would rather that _I_ choose when to connect what to _my_ phone. 😩