Tootfinder

[1/?]
So this happened while I was up a mountain:
https://www.joshtumath.uk/posts/2026-01-27-try-text-scaling-support-in-chrome-canary/
But the post didn’t have a demo. Last night I made one:

A deep dive into co-packaged optics, long promised to transform data center connectivity, covering benefits, challenges, architecture, key companies, and more (Dylan Patel/SemiAnalysis)
https://newsletter.semianalysis.com/p/co-packaged-optics-cpo-book-scaling…

Co Packaged Optics (CPO) – Scaling with Light for the Next Wave of Interconnect
Co-Packaged Optics (CPO) has long promised to transform datacenter connectivity, but it has taken a long time for the technology to come to market, with tangible deployment-ready products only arriving in 2025.

Home batteries are quietly becoming a game-changer for grid stability. As installations surge, utilities are tapping residential storage to manage peak demand during extreme weather—deferring costly upgrades while boosting resilience.
The key to scaling? Treat it like market development, not just tech deployment. Simple enrollment, risk-sharing models, and coordinated action between utilities and manufacturers can unlock massive participation.

Programmatic alignment is key to scaling residential battery demand response
Utilities, battery manufacturers, technology providers and customers all operate under different incentive structures, writes Uplight’s Sneha Vasudevan.

"Scaling ORCID Adoption: Technical and Organizational Approaches Within a Research Organization"
#ORCID iD use…

So, I guess no one has any idea how to fix Wayland vs. Chromium?
https://askubuntu.com/questions/1559959/chromium-apps-scaling-wrong-in-wayland-kubuntu-25-10

Chromium apps scaling wrong in Wayland / Kubuntu 25.10
I just installed Kubuntu 25.10 for the first time, on a fresh laptop install. 25.10 defaults to Wayland now. Now, Chromium-based apps (Chrome, Signal, and Slack so far) are showing mis-scaled; th...

Sources: Apple wound down plans for an AI-based virtual health coach in recent weeks; Eddy Cue has told colleagues that Apple needs to move faster in health (Mark Gurman/Bloomberg)
https://www.bloomberg.com/news/articles/20…

Why is the UK scaling back jury trials, and why is it controversial? | Civil Rights News | Al Jazeera
https://www.aljazeera.com/news/2025/12/2/why-is-the-uk-scaling-back-jury-trials-and-why-is-it-controversial?traffic_source=rss

David #Lammy,
“Trials are a fundamental part of our democratic settlement. Criminal trials without juries are a bad idea.”
And,
<<I have principles. If they are inconvenient, I have others,>>
Why is the UK scaling back jury trials, and why is it controversial? | Civil Rights News | Al Jazeera

Why is the UK scaling back jury trials, and why is it controversial?
Right to trial by jury seen as a touchstone of the British justice system, but severe court backlogs may prompt change.

Embarking on an online business journey is like a strategic expedition. 🌐 Start with thorough niche research – 80% of successful businesses thrive through specialization. Reduce risks by implementing small pilot projects before scaling up. Success lies in informed beginnings! #OnlineBusinessTips #Entrepreneurship

For fans of #Steam games where you can build -really- broken mechanics like Balatro or Slay the Spire (#deckbuilders, #roguelikes, etc. - "Make the numbers go UP!"), LOOTPLOT has been *extremely* satisfying for me
It's like: "what if Incredible Machine, but Ballionaire" - you randomly get access to a bunch of items that each have their own mechanics and trigger/play off each other, which you build out on a grid - but the grid itself can be manipulated by the items. Some of the interactions are absolutely wild.
Plays a little rough on CrossOver - I think the dynamic scaling plays havoc with texture calculation - but is still enjoyable all the same. (It's written in LÖVE - I really hope the author releases a macOS build!)
The sale price of $3.49 is crazy good for the enjoyment value I've gotten out of it
https://store.steampowered.com/app/3057190/LOOTPLOT/

I've been a GNOME user primarily for... probably over a decade at this point, occasionally trying #KDEPlasma. Nothing particularly bad about GNOME but recently been having some issues with scaling and theming so decided to try Plasma 6 and I think it might stick this time!

Massachusetts just awarded 1.3 GW of grid batteries to avoid costly upgrades. Kenya is scaling compressed earth blocks that cool homes with far less cement. CATL and Stellantis are building a 50 GWh battery plant in Spain to supply European EVs.
Real capacity, real progress.
Sign up for the For People And Planet climate solutions digest:

Weekly Climate Solutions Digest
Welcome First light of the year rises thin and tender, and somewhere a wren stitches the cold air with a single bright note. It feels like a cue to pay attention to what is being quietly built. This week gathers a clear theme of capacity made real. Money meets materials,

@… Good job. I've actually found Mint to be better at handling scaling than most distros.

Crosslisted article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- A quadratic-scaling algorithm with guaranteed convergence for quantum coupled-channel calculations
Hubert J. J\'o\'zwiak, Md Muktadir Rahman, Timur V. Tscherbul

Scaling Sucked Out All the Air in the Room - Ilya Sutskever - YouTube
https://www.youtube.com/shorts/wqIzd5sxt_E

National Grid DSO's contracted flexibility numbers are impressive. The domestic segment is showing particularly strong growth, with EV charging accounting for the majority of this. Many small units are coming together to make a big contribution.
https://dso.nationalg…

When I was a kid, I had a couple well-loved issues of G.I. Joe Special Missions, and this art from the cover of one of them was my absolute favorite. And I ran across it the other day again, and it still strikes me as extremely badass, even now. Just something about Snake Eyes scaling a wall in moonlight.
#art #comics …

Firefox is choking on video on my 4k monitor on Kubuntu. Youtube's status for nerds is showing 10 - 20% of frames dropped.
Chromium is fine. I think removing all the monitor scaling helps but does not fully fix it.
#ubuntu #linux

🤯 stable-pretraining-v1: Foundation Model Research Made Simple
#ai #llm

stable-pretraining-v1: Foundation Model Research Made Simple
Foundation models and self-supervised learning (SSL) have become central to modern AI, yet research in this area remains hindered by complex codebases, redundant re-implementations, and the heavy engineering burden of scaling experiments. We present stable-pretraining, a modular, extensible, and performance-optimized library built on top of PyTorch, Lightning, Hugging Face, and TorchMetrics. Unlike prior toolkits focused narrowly on reproducing state-of-the-art results, stable-pretraining is de…

What a great read and overview, recommended !
"The State Of LLMs 2025: Progress, Problems, and Predictions"
#AI

The State Of LLMs 2025: Progress, Progress, and Predictions
A 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.

I'm running into a really annoying render bug with the latest Kubuntu, which now uses Wayland. Anyone else seen this issue, and know how to fix it?
https://askubuntu.com/questions/1559959/chromium-apps-scaling-wrong-in-wayland-kubuntu-25-10

Chromium apps scaling wrong in Wayland / Kubuntu 25.10
I just installed Kubuntu 25.10 for the first time, on a fresh laptop install. 25.10 defaults to Wayland now. Now, Chromium-based apps (Chrome, Signal, and Slack so far) are showing mis-scaled; th...

For some reason, my home server was using the "performance" CPU scaling governor. Changing it to "conservative" seems to have lowered power consumption for the whole machine by almost 10%. This saves more than 25€ per year in electricity cost.
You can check your own CPU scaling governor with `cat /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor`.

Cursor's recent experiment involved running hundreds of AI agents for nearly a week to build a web browser, writing 1M lines of code across 1,000 files (Simon Willison/Simon Willison's Weblog)
https://simonwillison.net/2026/Jan/19/scaling-long-running-a…

Scaling long-running autonomous coding
Wilson Lin at Cursor has been doing some experiments to see how far you can push a large fleet of "autonomous" coding agents: This post describes what we've learned from …

I need to read it properly, but this looks 🔥 https://arxiv.org/abs/2511.16652

Evolution Strategies at the Hyperscale
We introduce Evolution Guided General Optimization via Low-rank Learning (EGGROLL), an evolution strategies (ES) algorithm designed to scale backprop-free optimization to large population sizes for modern large neural network architectures with billions of parameters. ES is a set of powerful blackbox optimisation methods that can handle non-differentiable or noisy objectives with excellent scaling potential through parallelisation. Na{ï}ve ES becomes prohibitively expensive at scale due to the…

#freshRss release notes:
"Scaling of user statistics in Web UI and CLI, to help instances with 1k users"
I feel a bit small with my installation for two users
https://github.com/FreshRSS/FreshRSS/r

Releases · FreshRSS/FreshRSS
A free, self-hostable news aggregator…. Contribute to FreshRSS/FreshRSS development by creating an account on GitHub.

Right after graduating in 2015, I was offered a job at the #BBC, working on scaling iPlayer. Well, continuing to scale iPlayer. It's one of my great what ifs.
It's an organisation I hugely admire, for many of the reasons that it is being attacked so viciously right now. Truth matters. Finding common ground matters. Keep the faith.

Allometric scaling of brain activity explained by avalanche criticality
Tiago S. A. N. Sim\~oes, Jos\'e S. Andrade Jr., Hans J. Herrmann, Stefano Zapperi, Lucilla de Arcangelis
https://arxiv.org/abs/2512.10834 https://arxiv.org/pdf/2512.10834 https://arxiv.org/html/2512.10834
arXiv:2512.10834v1 Announce Type: new
Abstract: Allometric scaling laws, such as Kleiber's law for metabolic rate, highlight how efficiency emerges with size across living systems. The brain, with its characteristic sublinear scaling of activity, has long posed a puzzle: why do larger brains operate with disproportionately lower firing rates? Here we show that this economy of scale is a universal outcome of avalanche dynamics. We derive analytical scaling laws directly from avalanche statistics, establishing that any system governed by critical avalanches must exhibit sublinear activity-size relations. This theoretical prediction is then verified in integrate-and-fire neuronal networks at criticality and in classical self-organized criticality models, demonstrating that the effect is not model-specific but generic. The predicted exponents align with experimental observations across mammal species, bridging dynamical criticality with the allometry of brain metabolism. Our results reveal avalanche criticality as a fundamental mechanism underlying Kleiber-like scaling in the brain.
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Either KDE fixes the problems with their Wayland session (faulty font rendering with fractional scaling, no ability to remap touchpad gestures that are literally baked in at compile time, and so on) or I'll be shopping for a new desktop environment once they drop X11 in 2027. I'll not be railroaded into accepting a dogshit user experience because somebody wants to dunk on the chuds. Plasma isn't that special!

Neuralink scaling? At some point, with growing numbers of Neuralink brain implant recipients, Neuralink will be busier with trying to fix broken implants than with new implants for new patients. If not, where's support? https://chatgpt.com/share/690a6c48-8f98-8004-9d69-c2a05198d…

ChatGPT - Neuralink scaling challenges
Shared via ChatGPT

reading a prelim paper on scaling up gpu-accelerated database query engines and feeling kinda gobsmacked at where that world is at
i remember when we built a “massive” memory machine at princeton with … i think it was 256 MB of RAM. (it sat idle except when ken thompson was logged in and building hash tables for chess endgames which was most of the time)

But I think that - first of all - Europe needs a strong cost reduction drive for components, systems, and processes in the energy transition, in a cooperation between R&D, manufacturers, and governments, and aligned with scaling up the market for 'made in Europe' solutions. We'll probably not get to the Chinese level, but we need to get a lot closer. This is essential both for competitiveness and affordability.

Taking a step closer to scaling up residential #V2G, a nationwide network of Swedish electricians will start offering installations of the Ambibox DC bidirectional charger (compatible with cars from the VW Group) in February.

A reflection on AI advances in the past decade and how scaling and time-horizon trends might point to far greater capabilities in the decade ahead (Zhengdong Wang)
https://zhengdongwang.com/2025/12/30/2025-letter.html

2025 letter
Zhengdong Wang’s personal website

"When your number's up, your number's up", my mum used to say:
November 16, 2012. Patrick Edlinger, a celebrated climber who had braved all dangers with his bare hands, accidentally dies by falling down the stairs at home.

"Scientists Develop Cigarette Butt Asphalt to Build Stronger Roads"
#Roads #Recycling
https://hap…

Scientists Develop Cigarette Butt Asphalt to Build Stronger Roads | Happy Eco News
Scientists in Spain and Italy are developing cigarette butt asphalt by turning discarded cigarette filters into road-strengthening pellets. The innovation makes asphalt more durable, extends road lifespans, and reduces toxic waste in the environment. Pilot projects show promise for scaling, offering cities a sustainable solution to improve infrastructure and cut pollution.

I've finally had the mental space over the holidays to make the switch to #niri off of #sway and I am already very happy with it. For one thing it seems Xwayland with scaling isn't broken anymore (of course the sway authors say it isn't broken, I'm just holding it wrong).

I missed this one:
#12886 [css-fonts-5] Text Fitting: Default scaling limit
https://github.com/w3c/csswg-drafts/issues/12886
Essentially a discussion how responsive text can satisfy 1.4.4, especially in this fit-to-container pitch from Google.
I added a comment …

[css-fonts-5] Text Fitting: Default scaling limit · Issue #12886 · w3c/csswg-drafts
In the original issue we received valuable feedback that a native fit-to-width solution can potentially introduce a simple way for authors to violate Success Criterion 1.4.4 Resize Text, in the sam...

Well, that's two ways of putting it.
https://www.theverge.com/news/823750/european-union-ai-act-gdpr-changes

Europe is scaling back its landmark privacy and AI laws
The European Commission has proposed changes weakening EU privacy legislation and delaying parts of the AI Act to make the bloc more competitive globally.

While the world debates climate action, Chinese cities are already doing it.
Shenzhen leads with massive EV adoption and vehicle-to-grid tech. Wuhan built "sponge cities" that absorb floodwater naturally. Dalian is scaling hydrogen energy. Guangzhou and Qingdao are tackling food waste and carbon management.
These aren't pilot programs—they're blueprints other cities can follow.

Beehiiv CEO Tyler Denk says the newsletter company plans to double the size of its ad product and operations team in H1 2026; its full staff is now ~110 people (Mark Stenberg/Adweek)
https://www.adweek.com/media/beehiiv-ad-sales-newsletter-programmatic/

Beehiiv Doubles Ad Sales Team, Scaling Newsletter Ads Business
The expansion comes as advertiser demand grows for email-native inventory and creators look for passive revenue streams

I gotta say, #cosmicdesktop gets many things right even in its alpha state. Using it right now. X11 apps and Electron garbage all work fine with fractional scaling. Can't say that about #gnome49. Oh, and quarter tiling by default! Optimistic for what the future brings for it.

Contrasting success in neurotechnology: Sensory substitution, brain–computer interfaces, and the limits of dimensional reduction https://www.researchgate.net/publication/3

Q&A with Ilya Sutskever about model jaggedness, why we are moving beyond the "age of scaling", SSI's plan to straight-shot superintelligence, AGI, and more (Dwarkesh Patel/Dwarkesh Podcast)
https://www.dwarkesh.com/p/ilya-sutskever-2

Spatially-informed transformers: Injecting geostatistical covariance biases into self-attention for spatio-temporal forecasting
Yuri Calleo
https://arxiv.org/abs/2512.17696 https://arxiv.org/pdf/2512.17696 https://arxiv.org/html/2512.17696
arXiv:2512.17696v1 Announce Type: new
Abstract: The modeling of high-dimensional spatio-temporal processes presents a fundamental dichotomy between the probabilistic rigor of classical geostatistics and the flexible, high-capacity representations of deep learning. While Gaussian processes offer theoretical consistency and exact uncertainty quantification, their prohibitive computational scaling renders them impractical for massive sensor networks. Conversely, modern transformer architectures excel at sequence modeling but inherently lack a geometric inductive bias, treating spatial sensors as permutation-invariant tokens without a native understanding of distance. In this work, we propose a spatially-informed transformer, a hybrid architecture that injects a geostatistical inductive bias directly into the self-attention mechanism via a learnable covariance kernel. By formally decomposing the attention structure into a stationary physical prior and a non-stationary data-driven residual, we impose a soft topological constraint that favors spatially proximal interactions while retaining the capacity to model complex dynamics. We demonstrate the phenomenon of ``Deep Variography'', where the network successfully recovers the true spatial decay parameters of the underlying process end-to-end via backpropagation. Extensive experiments on synthetic Gaussian random fields and real-world traffic benchmarks confirm that our method outperforms state-of-the-art graph neural networks. Furthermore, rigorous statistical validation confirms that the proposed method delivers not only superior predictive accuracy but also well-calibrated probabilistic forecasts, effectively bridging the gap between physics-aware modeling and data-driven learning.
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(Adaptive) Scaled gradient methods beyond locally Holder smoothness: Lyapunov analysis, convergence rate and complexity
Susan Ghaderi, Morteza Rahimi, Yves Moreau, Masoud Ahookhosh
https://arxiv.org/abs/2511.10425 https://arxiv.org/pdf/2511.10425 https://arxiv.org/html/2511.10425
arXiv:2511.10425v1 Announce Type: new
Abstract: This paper addresses the unconstrained minimization of smooth convex functions whose gradients are locally Holder continuous. Building on these results, we analyze the Scaled Gradient Algorithm (SGA) under local smoothness assumptions, proving its global convergence and iteration complexity. Furthermore, under local strong convexity and the Kurdyka-Lojasiewicz (KL) inequality, we establish linear convergence rates and provide explicit complexity bounds. In particular, we show that when the gradient is locally Lipschitz continuous, SGA attains linear convergence for any KL exponent. We then introduce and analyze an adaptive variant of SGA (AdaSGA), which automatically adjusts the scaling and step-size parameters. For this method, we show global convergence, and derive local linear rates under strong convexity.
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Geometric Interpretation of the Redshift Evolution of H_0(z)
Seokcheon Lee
https://arxiv.org/abs/2511.07454 https://arxiv.org/pdf/2511.07454 https://arxiv.org/html/2511.07454
arXiv:2511.07454v1 Announce Type: new
Abstract: Recent analyses of the Master Type Ia supernova (SN Ia) sample have revealed a mild redshift dependence in the inferred local Hubble parameter, often expressed as tilde{H}_0(z) = H_0 (1 z)^{-\alpha}, where \alpha quantifies possible departures from the standard cosmological time dilation relation. In this work, we show that such an empirical scaling can be interpreted as a purely geometric effect arising from a small, gauge-dependent normalization of cosmic time within the Robertson-Walker metric. This interpretation naturally unifies the observed redshift evolution of tilde{H}_0(z) and the corresponding deviation in SN Ia light-curve durations under a single geometric time-normalization framework. We demonstrate that this mapping leaves all background distances--linked to the Hubble radius in the general-relativistic frame--unchanged, while the apparent evolution in SN Ia luminosity distances arises from the redshift dependence of the Chandrasekhar mass. The result provides a unified and observationally consistent explanation of the mild Hubble-tension trend as a manifestation of the geometric structure of cosmic time rather than a modification of the expansion dynamics.
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The EU unveils proposed updates to GDPR, including simplifying cookie permission pop-ups, and plans to water down the AI Act, after US and tech company pressure (The Verge)
https://www.theverge.com/news/823750/european-union-ai-act-gdpr-changes

Europe is scaling back its landmark privacy and AI laws
The European Commission has proposed changes weakening EU privacy legislation and delaying parts of the AI Act to make the bloc more competitive globally.

“Google also announced the expansion of its 24/7 Carbon-Free Energy (CFE) partnership with Engie in Germany [..] now scaling up to contribute to Germany's energy transition and grid stability.
[..] Google's German operations are projected to run at or near 85% carbon-free energy in 2026.”

Google Announces €5.5 Billion Investment in Germany, including AI Infrastructure, through 2029
BERLIN — November 11, 2025 — Google today announced a new €5.5 billion investment (2026-2029) in infrastructure and offices in Germany — including a new data center in Dietzenbach,...

Invariant Price of Anarchy: a Metric for Welfarist Traffic Control
Ilia Shilov, Mingjia He, Heinrich H. Nax, Emilio Frazzoli, Gioele Zardini, Saverio Bolognani
https://arxiv.org/abs/2512.05843 https://arxiv.org/pdf/2512.05843 https://arxiv.org/html/2512.05843
arXiv:2512.05843v1 Announce Type: new
Abstract: The Price of Anarchy (PoA) is a standard metric for quantifying inefficiency in socio-technical systems, widely used to guide policies like traffic tolling. Conventional PoA analysis relies on exact numerical costs. However, in many settings, costs represent agents' preferences and may be defined only up to possibly arbitrary scaling and shifting, representing informational and modeling ambiguities. We observe that while such transformations preserve equilibrium and optimal outcomes, they change the PoA value. To resolve this issue, we rely on results from Social Choice Theory and define the Invariant PoA. By connecting admissible transformations to degrees of comparability of agents' costs, we derive the specific social welfare functions which ensure that efficiency evaluations do not depend on arbitrary rescalings or translations of individual costs. Case studies on a toy example and the Zurich network demonstrate that identical tolling strategies can lead to substantially different efficiency estimates depending on the assumed comparability. Our framework thus demonstrates that explicit axiomatic foundations are necessary in order to define efficiency metrics and to appropriately guide policy in large-scale infrastructure design robustly and effectively.
toXiv_bot_toot

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

Anthropic commits to buy $30B in Azure capacity in a new deal with Microsoft and Nvidia, which commit to invest up to $5B and $10B, respectively, in Anthropic (Microsoft)
https://blogs.microsoft.com/blog/2025/11/18/microsoft-nvidia-…

Microsoft, NVIDIA and Anthropic announce strategic partnerships - The Official Microsoft Blog
Anthropic to scale Claude on Azure Anthropic to adopt NVIDIA architecture NVIDIA and Microsoft to invest in Anthropic Today Microsoft, NVIDIA and Anthropic announced new strategic partnerships. Anthropic is scaling its rapidly-growing Claude AI model on Microsoft Azure, powered by NVIDIA, which will broaden access to Claude and provide Azure enterprise customers with expanded model choice and new capabilities. Anthropic...

Prefrontal scaling of reward prediction error readout gates reinforcement-derived adaptive behavior in primates
Tian Sang, Yichun Huang, Fangwei Zhong, Miao Wang, Shiqi Yu, Jiahui Li, Yuanjing Feng, Yizhou Wang, Kwok Sze Chai, Ravi S. Menon, Meiyun Wang, Fang Fang, Zheng Wang
https://arxiv.org/abs/2512.09761 https://arxiv.org/pdf/2512.09761 https://arxiv.org/html/2512.09761
arXiv:2512.09761v1 Announce Type: new
Abstract: Reinforcement learning (RL) enables adaptive behavior across species via reward prediction errors (RPEs), but the neural origins of species-specific adaptability remain unknown. Integrating RL modeling, transcriptomics, and neuroimaging during reversal learning, we discovered convergent RPE signatures - shared monoaminergic/synaptic gene upregulation and neuroanatomical representations, yet humans outperformed macaques behaviorally. Single-trial decoding showed RPEs guided choices similarly in both species, but humans disproportionately recruited dorsal anterior cingulate (dACC) and dorsolateral prefrontal cortex (dlPFC). Cross-species alignment uncovered that macaque prefrontal circuits encode human-like optimal RPEs yet fail to translate them into action. Adaptability scaled not with RPE encoding fidelity, but with the areal extent of dACC/dlPFC recruitment governing RPE-to-action transformation. These findings resolve an evolutionary puzzle: behavioral performance gaps arise from executive cortical readout efficiency, not encoding capacity.
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Q&A with Rivian founder and CEO RJ Scaringe on founding Rivian in 2009, production challenges, the VW partnership, autonomy, AI, EVs, chips, CarPlay, and more (Ben Thompson/Stratechery)
https://stratechery.com/2025/an-interv

An Interview with Rivian CEO RJ Scaringe About Building a Car Company and Autonomy
An interview with Rivian founder and CEO RJ Scaringe about starting a car company, scaling, and building for an autonomous future.

Europe just opened major funding for industrial decarbonization—clean hydrogen, net zero manufacturing, carbon capture.
Carbon removal is scaling too: 268,000 tonnes contracted in November across biochar, direct air capture, and biomass. Real projects, real revenue.
Sign up for the For People And Planet climate solutions digest.

Weekly Climate Solutions Digest
Welcome This week feels like work and wonder at once. Night comes early in the north and the Geminids begin to stitch bright threads across the cold sky. Far south, heat lifts and cicadas test their summer chorus. In that split screen of seasons, our stories settle on two steady

"‘We’ve future-proofed’: how UK’s biggest car factory upgraded for EV revolution"
#UK #UnitedKingdom #EV #ElectricVehicles

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/3]:
- Fraud detection in credit card transactions using Quantum-Assisted Restricted Boltzmann Machines
Jo\~ao Marcos Cavalcanti de Albuquerque Neto, Gustavo Castro do Amaral, Guilherme Penello Tempor\~ao
https://arxiv.org/abs/2512.17660 https://mastoxiv.page/@arXiv_quantph_bot/115762703945731580
- Vidarc: Embodied Video Diffusion Model for Closed-loop Control
Feng, Xiang, Mao, Tan, Zhang, Huang, Zheng, Liu, Su, Zhu
https://arxiv.org/abs/2512.17661 https://mastoxiv.page/@arXiv_csRO_bot/115762650859932523
- Imputation Uncertainty in Interpretable Machine Learning Methods
Pegah Golchian, Marvin N. Wright
https://arxiv.org/abs/2512.17689 https://mastoxiv.page/@arXiv_statML_bot/115762577479255577
- Revisiting the Broken Symmetry Phase of Solid Hydrogen: A Neural Network Variational Monte Carlo ...
Shengdu Chai, Chen Lin, Xinyang Dong, Yuqiang Li, Wanli Ouyang, Lei Wang, X. C. Xie
https://arxiv.org/abs/2512.17703 https://mastoxiv.page/@arXiv_condmatstrel_bot/115762481116668454
- Breast Cancer Neoadjuvant Chemotherapy Treatment Response Prediction Using Aligned Longitudinal M...
Rahul Ravi, Ruizhe Li, Tarek Abdelfatah, Stephen Chan, Xin Chen
https://arxiv.org/abs/2512.17759 https://mastoxiv.page/@arXiv_eessIV_bot/115762481771898369
- MedNeXt-v2: Scaling 3D ConvNeXts for Large-Scale Supervised Representation Learning in Medical Im...
Roy, Kirchhoff, Ulrich, Rokuss, Wald, Isensee, Maier-Hein
https://arxiv.org/abs/2512.17774 https://mastoxiv.page/@arXiv_eessIV_bot/115762492258209812
- Domain-Aware Quantum Circuit for QML
Gurinder Singh, Thaddeus Pellegrini, Kenneth M. Merz, Jr
https://arxiv.org/abs/2512.17800 https://mastoxiv.page/@arXiv_quantph_bot/115762723607200478
- Visually Prompted Benchmarks Are Surprisingly Fragile
Feng, Lian, Dunlap, Shu, Wang, Wang, Darrell, Suhr, Kanazawa
https://arxiv.org/abs/2512.17875 https://mastoxiv.page/@arXiv_csCV_bot/115762781936221554
- Learning vertical coordinates via automatic differentiation of a dynamical core
Tim Whittaker, Seth Taylor, Elsa Cardoso-Bihlo, Alejandro Di Luca, Alex Bihlo
https://arxiv.org/abs/2512.17877 https://mastoxiv.page/@arXiv_physicsaoph_bot/115762405092703069
- RadarGen: Automotive Radar Point Cloud Generation from Cameras
Tomer Borreda, Fangqiang Ding, Sanja Fidler, Shengyu Huang, Or Litany
https://arxiv.org/abs/2512.17897 https://mastoxiv.page/@arXiv_csCV_bot/115762783246540528
- Distributionally Robust Imitation Learning: Layered Control Architecture for Certifiable Autonomy
Gahlawat, Aboudonia, Banik, Hovakimyan, Matni, Ames, Zardini, Speranzon
https://arxiv.org/abs/2512.17899 https://mastoxiv.page/@arXiv_eessSY_bot/115762532257741954
- Re-Depth Anything: Test-Time Depth Refinement via Self-Supervised Re-lighting
Ananta R. Bhattarai, Helge Rhodin
https://arxiv.org/abs/2512.17908 https://mastoxiv.page/@arXiv_csCV_bot/115762785868778349
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Bound and Resonant States of Muonic Few-Body Coulomb Systems: Extended Stochastic Variational Approach
Liang-Zhen Wen, Shi-Lin Zhu
https://arxiv.org/abs/2512.07323 https://arxiv.org/pdf/2512.07323 https://arxiv.org/html/2512.07323
arXiv:2512.07323v1 Announce Type: new
Abstract: We compute the bound and resonant states of hydrogen-like muonic ions ($\mu\mu p$, $\mu\mu d$, $\mu\mu t$) and three-body muonic molecular ions ($pp\mu$, $pd\mu$, $pt\mu$, $dd\mu$, $dt\mu$, $tt\mu$), and the four-body double-muonic hydrogen molecule ($\mu\mu pp$) using an extended stochastic variational method combined with complex scaling. The approach provides a unified treatment of bound and quasibound states and achieves an energy accuracy better than $0.1~\mathrm{eV}$ across all systems studied. Complete spectra below the corresponding $n=2$ atomic thresholds are obtained, including several previously unresolved shallow resonances in both three- and four-body sectors.
toXiv_bot_toot

The carbon removal market is heating up fast.
This week alone saw major companies signing CDR purchase agreements, new breakthroughs in biogenic CO2 capture and storage, and over 1,000 companies tapping into market intelligence platforms.
Fresh research on biochar and weathering is out, plus a new legal framework report showing how serious the industry has become about scaling durable carbon removal.

This Week in CDR - Week 38, 2025
CDR.fyi is the reporting platform for the durable carbon removal market.

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[1/5]:
- Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization a...
Haoyue Bai, Gregory Canal, Xuefeng Du, Jeongyeol Kwon, Robert Nowak, Yixuan Li
https://arxiv.org/abs/2306.09158
- Sparse, Efficient and Explainable Data Attribution with DualXDA
Galip \"Umit Yolcu, Moritz Weckbecker, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
https://arxiv.org/abs/2402.12118 https://mastoxiv.page/@arXiv_csLG_bot/111962593972369958
- HGQ: High Granularity Quantization for Real-time Neural Networks on FPGAs
Sun, Que, {\AA}rrestad, Loncar, Ngadiuba, Luk, Spiropulu
https://arxiv.org/abs/2405.00645 https://mastoxiv.page/@arXiv_csLG_bot/112370274737558603
- On the Identification of Temporally Causal Representation with Instantaneous Dependence
Li, Shen, Zheng, Cai, Song, Gong, Chen, Zhang
https://arxiv.org/abs/2405.15325 https://mastoxiv.page/@arXiv_csLG_bot/112511890051553111
- Basis Selection: Low-Rank Decomposition of Pretrained Large Language Models for Target Applications
Yang Li, Daniel Agyei Asante, Changsheng Zhao, Ernie Chang, Yangyang Shi, Vikas Chandra
https://arxiv.org/abs/2405.15877 https://mastoxiv.page/@arXiv_csLG_bot/112517547424098076
- Privacy Bias in Language Models: A Contextual Integrity-based Auditing Metric
Yan Shvartzshnaider, Vasisht Duddu
https://arxiv.org/abs/2409.03735 https://mastoxiv.page/@arXiv_csLG_bot/113089789682783135
- Low-Rank Filtering and Smoothing for Sequential Deep Learning
Joanna Sliwa, Frank Schneider, Nathanael Bosch, Agustinus Kristiadi, Philipp Hennig
https://arxiv.org/abs/2410.06800 https://mastoxiv.page/@arXiv_csLG_bot/113283021321510736
- Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classification
Xiaoyu Tao, Tingyue Pan, Mingyue Cheng, Yucong Luo, Qi Liu, Enhong Chen
https://arxiv.org/abs/2410.18686 https://mastoxiv.page/@arXiv_csLG_bot/113367101100828901
- Fairness via Independence: A (Conditional) Distance Covariance Framework
Ruifan Huang, Haixia Liu
https://arxiv.org/abs/2412.00720 https://mastoxiv.page/@arXiv_csLG_bot/113587817648503815
- Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning
Simon Frieder, et al.
https://arxiv.org/abs/2412.15184 https://mastoxiv.page/@arXiv_csLG_bot/113683924322164777
- Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy
Ishank Juneja, Carlee Joe-Wong, Osman Ya\u{g}an
https://arxiv.org/abs/2501.10290 https://mastoxiv.page/@arXiv_csLG_bot/113859392622871057
- Towards Human-Guided, Data-Centric LLM Co-Pilots
Evgeny Saveliev, Jiashuo Liu, Nabeel Seedat, Anders Boyd, Mihaela van der Schaar
https://arxiv.org/abs/2501.10321 https://mastoxiv.page/@arXiv_csLG_bot/113859392688054204
- Regularized Langevin Dynamics for Combinatorial Optimization
Shengyu Feng, Yiming Yang
https://arxiv.org/abs/2502.00277
- Generating Samples to Probe Trained Models
Eren Mehmet K{\i}ral, Nur\c{s}en Ayd{\i}n, \c{S}. \.Ilker Birbil
https://arxiv.org/abs/2502.06658 https://mastoxiv.page/@arXiv_csLG_bot/113984059089245671
- On Agnostic PAC Learning in the Small Error Regime
Julian Asilis, Mikael M{\o}ller H{\o}gsgaard, Grigoris Velegkas
https://arxiv.org/abs/2502.09496 https://mastoxiv.page/@arXiv_csLG_bot/114000974082372598
- Preconditioned Inexact Stochastic ADMM for Deep Model
Shenglong Zhou, Ouya Wang, Ziyan Luo, Yongxu Zhu, Geoffrey Ye Li
https://arxiv.org/abs/2502.10784 https://mastoxiv.page/@arXiv_csLG_bot/114023667639951005
- On the Effect of Sampling Diversity in Scaling LLM Inference
Wang, Liu, Chen, Light, Liu, Chen, Zhang, Cheng
https://arxiv.org/abs/2502.11027 https://mastoxiv.page/@arXiv_csLG_bot/114023688225233656
- How to use score-based diffusion in earth system science: A satellite nowcasting example
Randy J. Chase, Katherine Haynes, Lander Ver Hoef, Imme Ebert-Uphoff
https://arxiv.org/abs/2505.10432 https://mastoxiv.page/@arXiv_csLG_bot/114516300594057680
- PEAR: Equal Area Weather Forecasting on the Sphere
Hampus Linander, Christoffer Petersson, Daniel Persson, Jan E. Gerken
https://arxiv.org/abs/2505.17720 https://mastoxiv.page/@arXiv_csLG_bot/114572963019603744
- Train Sparse Autoencoders Efficiently by Utilizing Features Correlation
Vadim Kurochkin, Yaroslav Aksenov, Daniil Laptev, Daniil Gavrilov, Nikita Balagansky
https://arxiv.org/abs/2505.22255 https://mastoxiv.page/@arXiv_csLG_bot/114589956040892075
- A Certified Unlearning Approach without Access to Source Data
Umit Yigit Basaran, Sk Miraj Ahmed, Amit Roy-Chowdhury, Basak Guler
https://arxiv.org/abs/2506.06486 https://mastoxiv.page/@arXiv_csLG_bot/114658421178857085
toXiv_bot_toot

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- State-space kinetic Ising model reveals task-dependent entropy flow in sparsely active nonequilib...
Ken Ishihara, Hideaki Shimazaki
https://arxiv.org/abs/2502.15440 https://mastoxiv.page/@arXiv_qbioNC_bot/114057779012161849
- Mechanisms for anesthesia, unawareness, respiratory depression, memory replay and sleep: MHb > IP...
Karin Vadovi\v{c}ov\'a
https://arxiv.org/abs/2509.04454 https://mastoxiv.page/@arXiv_qbioNC_bot/115167812677714466
- Meta-learning three-factor plasticity rules for structured credit assignment with sparse feedback
Dimitra Maoutsa
https://arxiv.org/abs/2512.09366 https://mastoxiv.page/@arXiv_qbioNC_bot/115699940165988688
- Prefrontal scaling of reward prediction error readout gates reinforcement-derived adaptive behavi...
Sang, Huang, Zhong, Wang, Yu, Li, Feng, Wang, Chai, Menon, Wang, Fang, Wang
https://arxiv.org/abs/2512.09761 https://mastoxiv.page/@arXiv_qbioNC_bot/115700046994546552
- Proof of a perfect platonic representation hypothesis
Liu Ziyin, Isaac Chuang
https://arxiv.org/abs/2507.01098 https://mastoxiv.page/@arXiv_csLG_bot/114788750477759162
toXiv_bot_toot

Australia is connecting Snowy 2.0 to the grid with 800 new transmission towers, unlocking 2.2 GW of renewable power.
Vikram Solar opened a 5 GW plant in Tamil Nadu, scaling India's solar capacity.
Bolivia created the Loma Santa Indigenous Conservation Area, protecting Amazon forests under Indigenous stewardship.
Sign up for the For People And Planet climate solutions digest:

Weekly Climate Solutions Digest
Welcome Early December settles in. In the north, frost filigrees the last leaves and Orion lifts above. It is a good week to pay attention to what connects. That is the thread running through our stories. New lines knit a giant alpine battery into Australia's grid. A factory in Tamil