@v_i_o_l_a@openbiblio.socialaus der reihe "warum erscheint dieses buch nicht open access?!" heute: "Information Science: History, Ideas, Applications" von Michael Seadle: https://www.facetpublishing.co.uk/page/detail/information-science/?k=9781783306947
@benb@osintua.euOpen letter to President Trump: Protect legal Ukrainian workers in US: https://benborges.xyz/2025/12/17/open-letter-to-president-trump.html
@Techmeme@techhub.socialSources: OpenAI is in advanced talks to hire OpenClaw founder Peter Steinberger and several team members; Steinberger would likely work on personal agents (Nick Wingfield/The Information)
https://www.theinformation.com/briefings/openai-advanced-talks…
@benb@osintua.euUkraine and Germany open their first joint plant to produce Ukrainian-designed AI drones, with 10,000 expected this: https://benborges.xyz/2026/02/13/ukraine-and-germany-open-their.html
@adulau@infosec.exchangeGCVE will be at hackathon.lu - April 14th and 15th, 2026
So if you want to work on all the cool stuff around vulnerability management, federated publication of vulnerability information, analytics, and anything related to vulnerabilities, join us.
#gcve #opensource
@ncoca@social.coop
@cdarwin@c.imAfter failed Freedom of Information Act (FOIA) requests to obtain video footage of ICE actions in Los Angeles and Chicago,
the "Center for Investigative Reporting" is seeking declaratory relief that these videos are public record and open to disclosure.
“To date, neither agency has complied with FOIA’s statutory deadlines,”
the Center for Investigative Reporting says in its suit.
“ICE and CBP have therefore violated the FOIA and have contravened the FOIA’s p…
@gwire@mastodon.socialAre we all done with Open Government now? There's no action plan beyond 2025.
https://www.gov.uk/government/collections/uk-national-action-plans-for-open-government
@nelson@tech.lgbtI continue to be impressed with how the LLM systems are pretty open about queerness and non-judgmental, non-homophobic. Remarkable given that so much of the training material must be hateful! Here's Gemini being cautious but helpful after I asked it about a summary of what it knows about me and asked why it didn't mention me being gay.
I do have access to information regarding your personal life and sexual orientation from our previous conversations. However, I am designed with specific safety and privacy guardrails that prevent me from storing or outputting information related to a user's sexual orientation or sensitive medical conditions in these types of summaries.
While I can remember and use those details to provide context during our active discussions—such as when we were looking into the history of queer voices or specific support resources—I cannot include them in a "permanent" distilled profile like the one above.
@Techmeme@techhub.socialAmazon files planning documents in Illinois to construct a 225,000 square foot big-box store, a return to a "Target-like" retail concept it previously shelved (Ann Gehan/The Information)
https://www.theinformation.com/briefings/amazon-plans-big-box-retail…
@iam_jfnklstrm@social.linux.pizzaEn region inför ai övers av patientsamtal som går via open ai och microsoft.
IT säk och DSO avråder, ändå kör man på eftersom man 'krypterat trafiken'? Har regionen kört okrypterat fram till nu? Nej, den som tar beslutet har bara noll teknisk kunskap 😳 och trång plånbok. Varför i he***te breddinför man det här? Lagen är tydlig med att myndigheter ska göra allt för att tillgodose att information alltid är korrekt så långt som möjligt. kolla YT undertexter och fundera på kvalitén…
@benb@osintua.euRussia’s exhaustion could open a strategic window for Ukraine in 2026, analyst says: https://benborges.xyz/2026/02/02/russias-exhaustion-could-open-a.html
@adulau@infosec.exchangeAcknowledging Reality in Vulnerability Disclosure.
Every few years, vulnerability disclosure is declared settled. We are told that the ecosystem has matured, that coordinated disclosure is the answer, and that whatever remains outside this model is either irresponsible, obsolete, or simply irrelevant.
🔗 https://www…
@kexpmusicbot@mastodonapp.uk🇺🇦 #NowPlaying on KEXP's #AfternoonShow
Horsegirl:
🎵 Information Content
#Horsegirl
https://thisishorsegirl.bandcamp.com/track/information-content
https://open.spotify.com/track/3sunB1mnTUu0ewjrZV4SZx
Please 🔁 BOOST to share what you like
- your followers don't see if you ⭐ favourite a post
@Techmeme@techhub.socialSource: Chinese AI startup Zhipu anonymously released its new AI model on OpenRouter under the name Pony Alpha; Zhipu plans to launch GLM-5 later this week (Juro Osawa/The Information)
https://www.theinformation.com/briefings/chinas-zhipu-rolls-new-ai-mo…
@leftsidestory@mstdn.socialSickly Red IV ⭕️
病态的红 IV ⭕️
📷 Pentax MX
🎞️ CineStill 800T
If you like my work, buy me a coffee from PayPal #filmphotography …
@v_i_o_l_a@openbiblio.social"Standing out of the crowd – How can researchers be more visible?" #Forschung
@benb@osintua.euFinnish Prime Minister open to dialogue with Russia if Moscow ends war: https://benborges.xyz/2026/01/29/finnish-prime-minister-open-to.html
@penguin42@mastodon.org.uk'graphviz' is a suite of programs for drawing graphs (In the nodes/edges senses, rather than upwards and to the right sense) - and it uses a file format called 'dot'. Lots of things generate dot output (such as systemd-analyze I mentioned) and it's really easy to generate from scripts and things. 'dotty' is probably the most common program in the suite.
There are some newer formats and programs - but this one is probably the most universal.
@kexpmusicbot@mastodonapp.uk🇺🇦 #NowPlaying on KEXP's #Expansions
Dele Sosimi Afrobeat Orchestra:
🎵 Too Much Information (Laolu remix)
#DeleSosimiAfrobeatOrchestra
https://rainycitymusic.bandcamp.com/track/dele-sosimi-afrobeat-orchestra-too-much-information-jepht-guillaume-tet-kale-remix
https://open.spotify.com/track/7l2pXmSIPB5bvmIvmHrfMZ
@gray17@mastodon.socialemail "I came across your profile on LinkedIn and saw you are open to new opportunities. Are you still actively looking right now?"
um, yeah, I deleted my linkedin a year ago. I guess the lesson is, never give anyone your contact information because scraping is forever.
maybe it's time to set up unique-email-per-contact.
hm, and I could approximate unique-phone-number-per-contact with a pbx.
not sure I wanna do unique-postal-address-per-contact (middle n…
@v_i_o_l_a@openbiblio.social"Scaling ORCID Adoption: Technical and Organizational Approaches Within a Research Organization"
#ORCID iD use…
@benb@osintua.euNATO to open second Ukraine arms supply hub in January 2026: https://benborges.xyz/2025/12/22/nato-to-open-second-ukraine.html
@arXiv_csDS_bot@mastoxiv.pagePerfect Network Resilience in Polynomial Time
Matthias Bentert, Stefan Schmid
https://arxiv.org/abs/2602.03827 https://arxiv.org/pdf/2602.03827 https://arxiv.org/html/2602.03827
arXiv:2602.03827v1 Announce Type: new
Abstract: Modern communication networks support local fast rerouting mechanisms to quickly react to link failures: nodes store a set of conditional rerouting rules which define how to forward an incoming packet in case of incident link failures. The rerouting decisions at any node $v$ must rely solely on local information available at $v$: the link from which a packet arrived at $v$, the target of the packet, and the incident link failures at $v$. Ideally, such rerouting mechanisms provide perfect resilience: any packet is routed from its source to its target as long as the two are connected in the underlying graph after the link failures. Already in their seminal paper at ACM PODC '12, Feigenbaum, Godfrey, Panda, Schapira, Shenker, and Singla showed that perfect resilience cannot always be achieved. While the design of local rerouting algorithms has received much attention since then, we still lack a detailed understanding of when perfect resilience is achievable.
This paper closes this gap and presents a complete characterization of when perfect resilience can be achieved. This characterization also allows us to design an $O(n)$-time algorithm to decide whether a given instance is perfectly resilient and an $O(nm)$-time algorithm to compute perfectly resilient rerouting rules whenever it is. Our algorithm is also attractive for the simple structure of the rerouting rules it uses, known as skipping in the literature: alternative links are chosen according to an ordered priority list (per in-port), where failed links are simply skipped. Intriguingly, our result also implies that in the context of perfect resilience, skipping rerouting rules are as powerful as more general rerouting rules. This partially answers a long-standing open question by Chiesa, Nikolaevskiy, Mitrovic, Gurtov, Madry, Schapira, and Shenker [IEEE/ACM Transactions on Networking, 2017] in the affirmative.
toXiv_bot_toot
@arXiv_csGR_bot@mastoxiv.pageHeatMat: Simulation of City Material Impact on Urban Heat Island Effect
Marie Reinbigler, Romain Rouffet, Peter Naylor, Mikolaj Czerkawski, Nikolaos Dionelis, Elisabeth Brunet, Catalin Fetita, Rosalie Martin
https://arxiv.org/abs/2601.22796 https://arxiv.org/pdf/2601.22796 https://arxiv.org/html/2601.22796
arXiv:2601.22796v1 Announce Type: new
Abstract: The Urban Heat Island (UHI) effect, defined as a significant increase in temperature in urban environments compared to surrounding areas, is difficult to study in real cities using sensor data (satellites or in-situ stations) due to their coarse spatial and temporal resolution. Among the factors contributing to this effect are the properties of urban materials, which differ from those in rural areas. To analyze their individual impact and to test new material configurations, a high-resolution simulation at the city scale is required. Estimating the current materials used in a city, including those on building facades, is also challenging. We propose HeatMat, an approach to analyze at high resolution the individual impact of urban materials on the UHI effect in a real city, relying only on open data. We estimate building materials using street-view images and a pre-trained vision-language model (VLM) to supplement existing OpenStreetMap data, which describes the 2D geometry and features of buildings. We further encode this information into a set of 2D maps that represent the city's vertical structure and material characteristics. These maps serve as inputs for our 2.5D simulator, which models coupled heat transfers and enables random-access surface temperature estimation at multiple resolutions, reaching an x20 speedup compared to an equivalent simulation in 3D.
toXiv_bot_toot
@BBC6MusicBot@mastodonapp.uk🇺🇦 #NowPlaying on #BBC6Music's #SteveLamacq
Dream Nails:
🎵 The Information
#DreamNails
https://open.spotify.com/track/76PRBee7ttZSf7Y4DbXD6N
@benb@osintua.euSmashed shops, no water, and cooking food on open fires: HELLISH life under Russian occupation: https://benborges.xyz/2026/01/04/smashed-shops-no-water-and.html
@Techmeme@techhub.socialOpenAI has hired 7 employees from AI coding startup Cline, including Nik Pash, who left Cline after posting "imagine the smell" on X regarding an xAI hackathon (Kevin McLaughlin/The Information)
https://www.theinformation.com/articles/op
@arXiv_csLG_bot@mastoxiv.pageCrosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[2/3]:
- Diffusion Modulation via Environment Mechanism Modeling for Planning
Hanping Zhang, Yuhong Guo
https://arxiv.org/abs/2602.20422 https://mastoxiv.page/@arXiv_csAI_bot/116130110576555049
- Heterogeneity-Aware Client Selection Methodology For Efficient Federated Learning
Nihal Balivada, Shrey Gupta, Shashank Shreedhar Bhatt, Suyash Gupta
https://arxiv.org/abs/2602.20450 https://mastoxiv.page/@arXiv_csDC_bot/116130191233002036
- Prior-Agnostic Incentive-Compatible Exploration
Ramya Ramalingam, Osbert Bastani, Aaron Roth
https://arxiv.org/abs/2602.20465 https://mastoxiv.page/@arXiv_csGT_bot/116130245628406144
- PhyGHT: Physics-Guided HyperGraph Transformer for Signal Purification at the HL-LHC
Mohammed Rakib, Luke Vaughan, Shivang Patel, Flera Rizatdinova, Alexander Khanov, Atriya Sen
https://arxiv.org/abs/2602.20475 https://mastoxiv.page/@arXiv_hepex_bot/116130242350426528
- ActionEngine: From Reactive to Programmatic GUI Agents via State Machine Memory
Zhong, Faisal, Fran\c{c}a, Leesatapornwongsa, Szekeres, Rong, Nath
https://arxiv.org/abs/2602.20502 https://mastoxiv.page/@arXiv_csAI_bot/116130180718734838
- Inner Speech as Behavior Guides: Steerable Imitation of Diverse Behaviors for Human-AI coordination
Rakshit Trivedi, Kartik Sharma, David C Parkes
https://arxiv.org/abs/2602.20517 https://mastoxiv.page/@arXiv_csAI_bot/116130223344095649
- Stop-Think-AutoRegress: Language Modeling with Latent Diffusion Planning
Lovelace, Belardi, Zalouk, Polavaram, Kundurthy, Weinberger
https://arxiv.org/abs/2602.20528 https://mastoxiv.page/@arXiv_csCL_bot/116130628998822849
- Standard Transformers Achieve the Minimax Rate in Nonparametric Regression with $C^{s,\lambda}$ T...
Yanming Lai, Defeng Sun
https://arxiv.org/abs/2602.20555 https://mastoxiv.page/@arXiv_statML_bot/116130512372759166
- Personal Information Parroting in Language Models
Nishant Subramani, Kshitish Ghate, Mona Diab
https://arxiv.org/abs/2602.20580 https://mastoxiv.page/@arXiv_csCL_bot/116130630309564204
- Characterizing Online and Private Learnability under Distributional Constraints via Generalized S...
Mo\"ise Blanchard, Abhishek Shetty, Alexander Rakhlin
https://arxiv.org/abs/2602.20585 https://mastoxiv.page/@arXiv_statML_bot/116130525452248337
- Amortized Bayesian inference for actigraph time sheet data from mobile devices
Daniel Zhou, Sudipto Banerjee
https://arxiv.org/abs/2602.20611 https://mastoxiv.page/@arXiv_statML_bot/116130543144314661
- Knowing the Unknown: Interpretable Open-World Object Detection via Concept Decomposition Model
Xueqiang Lv, Shizhou Zhang, Yinghui Xing, Di Xu, Peng Wang, Yanning Zhang
https://arxiv.org/abs/2602.20616 https://mastoxiv.page/@arXiv_csCV_bot/116130795466851481
- On the Convergence of Stochastic Gradient Descent with Perturbed Forward-Backward Passes
Boao Kong, Hengrui Zhang, Kun Yuan
https://arxiv.org/abs/2602.20646 https://mastoxiv.page/@arXiv_mathOC_bot/116130476952419594
- DANCE: Doubly Adaptive Neighborhood Conformal Estimation
Feng, Reich, Beaglehole, Luo, Park, Yoo, Huang, Mao, Boz, Kim
https://arxiv.org/abs/2602.20652 https://mastoxiv.page/@arXiv_statML_bot/116130551664144143
- Vision-Language Models for Ergonomic Assessment of Manual Lifting Tasks: Estimating Horizontal an...
Mohammad Sadra Rajabi, Aanuoluwapo Ojelade, Sunwook Kim, Maury A. Nussbaum
https://arxiv.org/abs/2602.20658 https://mastoxiv.page/@arXiv_csCV_bot/116130809228818544
- F10.7 Index Prediction: A Multiscale Decomposition Strategy with Wavelet Transform for Performanc...
Xuran Ma, et al.
https://arxiv.org/abs/2602.20712 https://mastoxiv.page/@arXiv_astrophIM_bot/116130530693731576
- Communication-Inspired Tokenization for Structured Image Representations
Davtyan, Sahin, Haghighi, Stapf, Acuaviva, Alahi, Favaro
https://arxiv.org/abs/2602.20731 https://mastoxiv.page/@arXiv_csCV_bot/116130824303022936
- SibylSense: Adaptive Rubric Learning via Memory Tuning and Adversarial Probing
Yifei Xu, et al.
https://arxiv.org/abs/2602.20751 https://mastoxiv.page/@arXiv_csCL_bot/116130739757479992
- Assessing the Impact of Speaker Identity in Speech Spoofing Detection
Anh-Tuan Dao, Driss Matrouf, Nicholas Evans
https://arxiv.org/abs/2602.20805 https://mastoxiv.page/@arXiv_csSD_bot/116130218074059060
- Don't Ignore the Tail: Decoupling top-K Probabilities for Efficient Language Model Distillation
Sayantan Dasgupta, Trevor Cohn, Timothy Baldwin
https://arxiv.org/abs/2602.20816 https://mastoxiv.page/@arXiv_csCL_bot/116130753521420972
- DRESS: A Continuous Framework for Structural Graph Refinement
Eduar Castrillo Velilla
https://arxiv.org/abs/2602.20833 https://mastoxiv.page/@arXiv_csDS_bot/116130545112457981
toXiv_bot_toot
@v_i_o_l_a@openbiblio.socialAlle acht bisherigen Vorträge der Reihe „Open Divide – Critical Studies on Open Access“ (weitere werden folgen) sind in der Mediathek der TIB verfügbar:
#OpenAccess
@arXiv_csLG_bot@mastoxiv.pageCrosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[2/3]:
- Sharp Structure-Agnostic Lower Bounds for General Functional Estimation
Jikai Jin, Vasilis Syrgkanis
https://arxiv.org/abs/2512.17341 https://mastoxiv.page/@arXiv_statML_bot/115762312049963700
- Timely Information Updating for Mobile Devices Without and With ML Advice
Yu-Pin Hsu, Yi-Hsuan Tseng
https://arxiv.org/abs/2512.17381 https://mastoxiv.page/@arXiv_csNI_bot/115762180316858485
- SWE-Bench : A Framework for the Scalable Generation of Software Engineering Benchmarks from Open...
Wang, Ramalho, Celestino, Pham, Liu, Sinha, Portillo, Osunwa, Maduekwe
https://arxiv.org/abs/2512.17419 https://mastoxiv.page/@arXiv_csSE_bot/115762487015279852
- Perfect reconstruction of sparse signals using nonconvexity control and one-step RSB message passing
Xiaosi Gu, Ayaka Sakata, Tomoyuki Obuchi
https://arxiv.org/abs/2512.17426 https://mastoxiv.page/@arXiv_statML_bot/115762346108219997
- MULTIAQUA: A multimodal maritime dataset and robust training strategies for multimodal semantic s...
Jon Muhovi\v{c}, Janez Per\v{s}
https://arxiv.org/abs/2512.17450 https://mastoxiv.page/@arXiv_csCV_bot/115762717053353674
- When Data Quality Issues Collide: A Large-Scale Empirical Study of Co-Occurring Data Quality Issu...
Emmanuel Charleson Dapaah, Jens Grabowski
https://arxiv.org/abs/2512.17460 https://mastoxiv.page/@arXiv_csSE_bot/115762500123147574
- Behavioural Effects of Agentic Messaging: A Case Study on a Financial Service Application
Olivier Jeunen, Schaun Wheeler
https://arxiv.org/abs/2512.17462 https://mastoxiv.page/@arXiv_csIR_bot/115762430673347625
- Linear Attention for Joint Power Optimization and User-Centric Clustering in Cell-Free Networks
Irched Chafaa, Giacomo Bacci, Luca Sanguinetti
https://arxiv.org/abs/2512.17466 https://mastoxiv.page/@arXiv_eessSY_bot/115762336277179643
- Translating the Rashomon Effect to Sequential Decision-Making Tasks
Dennis Gross, J{\o}rn Eirik Betten, Helge Spieker
https://arxiv.org/abs/2512.17470 https://mastoxiv.page/@arXiv_csAI_bot/115762556506696539
- Alternating Direction Method of Multipliers for Nonlinear Matrix Decompositions
Atharva Awari, Nicolas Gillis, Arnaud Vandaele
https://arxiv.org/abs/2512.17473 https://mastoxiv.page/@arXiv_eessSP_bot/115762580078964235
- TwinSegNet: A Digital Twin-Enabled Federated Learning Framework for Brain Tumor Analysis
Almustapha A. Wakili, Adamu Hussaini, Abubakar A. Musa, Woosub Jung, Wei Yu
https://arxiv.org/abs/2512.17488 https://mastoxiv.page/@arXiv_csCV_bot/115762726884307901
- Resource-efficient medical image classification for edge devices
Mahsa Lavaei, Zahra Abadi, Salar Beigzad, Alireza Maleki
https://arxiv.org/abs/2512.17515 https://mastoxiv.page/@arXiv_eessIV_bot/115762459510336799
- PathBench-MIL: A Comprehensive AutoML and Benchmarking Framework for Multiple Instance Learning i...
Brussee, Valkema, Weijer, Doeleman, Schrader, Kers
https://arxiv.org/abs/2512.17517 https://mastoxiv.page/@arXiv_csCV_bot/115762741957639051
- HydroGym: A Reinforcement Learning Platform for Fluid Dynamics
Christian Lagemann, et al.
https://arxiv.org/abs/2512.17534 https://mastoxiv.page/@arXiv_physicsfludyn_bot/115762391350754768
- When De-noising Hurts: A Systematic Study of Speech Enhancement Effects on Modern Medical ASR Sys...
Chondhekar, Murukuri, Vasani, Goyal, Badami, Rana, SN, Pandia, Katiyar, Jagadeesh, Gulati
https://arxiv.org/abs/2512.17562 https://mastoxiv.page/@arXiv_csSD_bot/115762423443170715
- Enabling Disaggregated Multi-Stage MLLM Inference via GPU-Internal Scheduling and Resource Sharing
Lingxiao Zhao, Haoran Zhou, Yuezhi Che, Dazhao Cheng
https://arxiv.org/abs/2512.17574 https://mastoxiv.page/@arXiv_csDC_bot/115762425409322293
- SkinGenBench: Generative Model and Preprocessing Effects for Synthetic Dermoscopic Augmentation i...
N. A. Adarsh Pritam, Jeba Shiney O, Sanyam Jain
https://arxiv.org/abs/2512.17585 https://mastoxiv.page/@arXiv_eessIV_bot/115762479150695610
- MAD-OOD: A Deep Learning Cluster-Driven Framework for an Out-of-Distribution Malware Detection an...
Tosin Ige, Christopher Kiekintveld, Aritran Piplai, Asif Rahman, Olukunle Kolade, Sasidhar Kunapuli
https://arxiv.org/abs/2512.17594 https://mastoxiv.page/@arXiv_csCR_bot/115762509298207765
- Confidence-Credibility Aware Weighted Ensembles of Small LLMs Outperform Large LLMs in Emotion De...
Menna Elgabry, Ali Hamdi
https://arxiv.org/abs/2512.17630 https://mastoxiv.page/@arXiv_csCL_bot/115762575512981257
- Generative Multi-Objective Bayesian Optimization with Scalable Batch Evaluations for Sample-Effic...
Madhav R. Muthyala, Farshud Sorourifar, Tianhong Tan, You Peng, Joel A. Paulson
https://arxiv.org/abs/2512.17659 https://mastoxiv.page/@arXiv_statML_bot/115762554519447500
toXiv_bot_toot
