Tootfinder

Austin's Surge of New Housing Construction Drove Down Rents (The Pew Charitable Trusts)
https://www.pew.org/en/research-and-analysis/articles/2026/03/18/austins-surge-of-new-housing-construction-drove-down-rents
http://www.memeorandum.com/260318/p58#a260318p58

"Pesticides from flea treatments and sheep dips found at damaging levels in Welsh rivers"
#UK #UnitedKingdom #Wales

Pesticides from flea treatments and sheep dips found at damaging levels in Welsh rivers
Pesticides used in pet flea treatments occur widely in Welsh rivers and were detected in over three quarters of river water samples, finds new research by Cardiff University and Natural Resources Wales. The study found that two pesticides from flea treatments, imidacloprid and fipronil, exceeded safe levels in almost half of the samples from urban locations.

Crosslisted 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

Another wonderful* example of how some economies grow thanks to a Creative Class (new smart business models around EV charging), while Germany gets bogged down by petty lawyers.
* wonderful here only applies to the German word “wirrwarr”, not on the petty nitpicking by lawyers
https://www…

Rückerstattung für Dienstwagen-Ladekosten: Wirrwarr um neue Regeln - electrive.net
Das Bundesfinanzministerium hat zum 1. Januar 2026 die Regeln für die Rückerstattung von Stromkosten für zu Hause aufgeladene Dienstwagen geändert. Doch

Ambitious climate action could save 1.32 million lives a year by 2040 #climate

Ambitious climate action could save 1.32 million lives a year by 2040
Ambitious climate action to improve global air quality could save up to 1.32 million lives per year by 2040, according to a new study. The research, led by Cardiff University, shows how developing countries rely heavily on international cooperation to see these benefits, because much of their pollution originates outside their borders. The first-of-its-kind study analyzed these cross-border pollution "exchanges" for nearly every country—168 in total.

"Science Ltd. – Research Enterprise in the Age of Machines"
https://www.routledge.com/Science-Ltd-Research-Enterprise-in-the-Age-of-Machines/Borghini-Severini/p/book/9781041131069
[erscheint (wen…

If you're in #tech and struggling to figure out what your career look like now — this piece is my answer. You've heard "it's here to stay" or "it's better than nothing."
Reject these frames.
Look at the system being built around you. Manufacturing validation for "inevitable" success. Rewriting our roles from human-centered creative to featu…

See what is happening, not what is supposed to happen
The stories we are telling around user research and LLMs have locked us into a doomed framing. Reject the very notion that it is "better than nothing."

This group "The Library of Babel" is confronting the invasion of #genAI into everything we do, seems interesting:
"a nascent, international coalition of educators confronting and resisting the incursion of surveillance, automation and datafication into spaces of teaching, learning, research, and creative expression. "

Worth repeating: Claims of "AI" democratizing anything (coding, creative endeavors, etc) are always BS. The thing locking out people from doing that is not having the time/resources.
You want to democratize coding/art/creativity? Give people paid time off to do it and access to infrastructure. Easy.

Lazy web request:
I’m trying to find back pain management advice that is based on scientific and medical research, rather than quackery.
I have seen that “The Back Book” from NHS exists, but it’s from 2005.
Anyone have an up-to-date, credible resource on back pain management to recommend? Thanks.