Tootfinder

As recently as Thursday, Vladimir Putin told a Kremlin demographic conference that increasing births was “crucial” for Russia.
Putin has launched initiatives to encourage people to have more children -- from free school meals for large families to awarding Soviet-style “hero-mother” medals to women with 10 or more children.
“Many of our grandmothers and great-grandmothers had seven, eight, and even more children,” Putin said in 2023.
“Let’s preserve and revive these wonderful…

Russia's population is getting smaller and older. Putin sees that as a national security threat
Russia has grappled with a shrinking and aging population for decades, with President Vladimir Putin viewing it as a threat to national security. Yet despite efforts like cash incentives and family-friendly policies, the number of deaths now outpaces births. Economic uncertainty, restrictions on immigration and the war in Ukraine are making the crisis worse. Desperate to reverse the trend, Russian authorities are also rolling out a wave of restrictive laws, such as banning "child-free propagand…

Attosecond-resolved quantum fluctuations of light and matter
Matan Even Tzur, Chen Mor, Noa Yaffe, Michael Birk, Andrei Rasputnyi, Omer Kneller, Ido Nisim, Ido Kaminer, Maria Chekhova, Michael Krueger, Misha Ivanov, Nirit Dudovich, Oren Cohen
https://arxiv.org/abs/2511.18362 https://arxiv.org/pdf/2511.18362 https://arxiv.org/html/2511.18362
arXiv:2511.18362v1 Announce Type: new
Abstract: Until recently, attosecond optical spectroscopy and quantum optics evolved along non-overlapping directions. In attosecond science, attosecond pulses have been regarded as classical waves, applied to probe electron dynamics on their natural time scale. Here, we transfer fundamental concepts of quantum optics into attosecond physics, enabling control of both the properties of the XUV attosecond pulses and the quantum fluctuations of matter on attosecond time scales. By combining bright squeezed vacuum (BSV) with a strong laser field to drive high-harmonic generation, we transfer the quantum properties of the BSV onto the resulting XUV attosecond pulses. Applying advanced attosecond interferometry, we reconstruct the quantum state of the XUV high harmonics and their associated attosecond pulses with attosecond precision. Finally, we resolve the squeezing of the electron's wavepacket during one of the most fundamental strong-field phenomena - field induced tunneling. The ability to measure and control quantum correlations in both electrons and XUV attosecond pulses establishes a foundation for attosecond quantum electrodynamics, manipulating the quantum state of electrons and photons with sub-cycle precision.
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Hey all, there are some photos from a hike in the #schwarzwald
Actually we thought that it would just take us less than an hour - but it wasn't simply a straight walk :-D
It was raining from time to time - which was indeed pretty cool. A) there was noone around except us and B) the colors were often just insane. Fully saturated green, the brown from the wood - and sometimes…

Easy Adaptation: An Efficient Task-Specific Knowledge Injection Method for Large Models in Resource-Constrained Environments
Dong Chen, Zhengqing Hu, Shixing Zhao, Yibo Guo
https://arxiv.org/abs/2512.17771 https://arxiv.org/pdf/2512.17771 https://arxiv.org/html/2512.17771
arXiv:2512.17771v1 Announce Type: new
Abstract: While the enormous parameter scale endows Large Models (LMs) with unparalleled performance, it also limits their adaptability across specific tasks. Parameter-Efficient Fine-Tuning (PEFT) has emerged as a critical approach for effectively adapting LMs to a diverse range of downstream tasks. However, existing PEFT methods face two primary challenges: (1) High resource cost. Although PEFT methods significantly reduce resource demands compared to full fine-tuning, it still requires substantial time and memory, making it impractical in resource-constrained environments. (2) Parameter dependency. PEFT methods heavily rely on updating a subset of parameters associated with LMs to incorporate task-specific knowledge. Yet, due to increasing competition in the LMs landscape, many companies have adopted closed-source policies for their leading models, offering access only via Application Programming Interface (APIs). Whereas, the expense is often cost-prohibitive and difficult to sustain, as the fine-tuning process of LMs is extremely slow. Even if small models perform far worse than LMs in general, they can achieve superior results on particular distributions while requiring only minimal resources. Motivated by this insight, we propose Easy Adaptation (EA), which designs Specific Small Models (SSMs) to complement the underfitted data distribution for LMs. Extensive experiments show that EA matches the performance of PEFT on diverse tasks without accessing LM parameters, and requires only minimal resources.
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Graphene and thin graphite films for ultrafast optical Kerr gating at 1 GHz repetition rate under focused illumination
Amr Farrag, Assegid M. Flatae, Mario Agio
https://arxiv.org/abs/2511.17713 https://arxiv.org/pdf/2511.17713 https://arxiv.org/html/2511.17713
arXiv:2511.17713v1 Announce Type: new
Abstract: The ability to address sub-picosecond events of weak optical signals is essential for progress in quantum science, nonlinear optics, and ultrafast spectroscopy. While up-conversion and optical Kerr gating (OKG) offer femtosecond resolution, they are generally limited to ensemble measurements, making ultrafast detection in nano-optics challenging. OKG, with its broadband response and high throughput without phase-matching, is especially promising when used at high repetition rates under focused illumination.
Here, we demonstrate an ultrafast detection scheme using the third-order nonlinearity of graphene and thin graphite films, operating at 1 GHz with sub-nanojoule pulses and achieving 141 fs temporal resolution. Their exceptionally large nonlinear refractive index, orders of magnitude higher than conventional Kerr media, enhances detection efficiency at smaller thicknesses, enables sub-picosecond response, and supports broadband operation. Their atomic-scale thickness minimizes dispersion and simplifies integration with microscopy platforms, optical fibers, and nanophotonic circuits, making them a compact, practical material platform for nano-optical and on-chip ultrafast Kerr gating.
toXiv_bot_toot

Towson University students moved their “No Kings” rally off campus
after a school official told them speakers’ names would be run through federal government databases and vetted for security reasons.
The demonstration, one of dozens planned in Maryland on Saturday,
will protest authoritarian policies of President Donald Trump.
Students moved the event, fearing that speakers would be targeted by the Trump administration,
which has threatened to pursue and punish …

Towson U. ‘No Kings’ rally relocates over speaker background checks
Towson University students moved their “No Kings” rally off campus after school officials told them speakers’ names would be run through federal government databases and vetted for security reasons.

I felt such a deep surge of hope reading this story. Toronto the bad, of all places.
https://www.theguardian.com/world/2025/oct/09/toronto-waterfront-soil-plants-worms

Correlation of Rankings in Matching Markets
R\'emi Castera, Patrick Loiseau, Bary S. R. Pradelski
https://arxiv.org/abs/2512.05304 https://arxiv.org/pdf/2512.05304 https://arxiv.org/html/2512.05304
arXiv:2512.05304v1 Announce Type: new
Abstract: We study the role of correlation in matching markets, where multiple decision-makers simultaneously face selection problems from the same pool of candidates. We propose a model in which a candidate's priority scores across different decision-makers exhibit varying levels of correlation dependent on the candidate's sociodemographic group. Such differential correlation can arise in school choice due to the varying prevalence of selection criteria, in college admissions due to test-optional policies, or due to algorithmic monoculture, that is, when decision-makers rely on the same algorithms and data sets to evaluate candidates. We show that higher correlation for one of the groups generally improves the outcome for all groups, leading to higher efficiency. However, students from a given group are more likely to remain unmatched as their own correlation level increases. This implies that it is advantageous to belong to a low-correlation group. Finally, we extend the tie-breaking literature to multiple priority classes and intermediate levels of correlation. Overall, our results point to differential correlation as a previously overlooked systemic source of group inequalities in school, university, and job admissions.
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Offline Reinforcement Learning with Generative Trajectory Policies
Xinsong Feng, Leshu Tang, Chenan Wang, Haipeng Chen
https://arxiv.org/abs/2510.11499 https://

Offline Reinforcement Learning with Generative Trajectory Policies
Generative models have emerged as a powerful class of policies for offline reinforcement learning (RL) due to their ability to capture complex, multi-modal behaviors. However, existing methods face a stark trade-off: slow, iterative models like diffusion policies are computationally expensive, while fast, single-step models like consistency policies often suffer from degraded performance. In this paper, we demonstrate that it is possible to bridge this gap. The key to moving beyond the limitati…

The A.I. insurance market is in its infancy, but Mr. Kvist says mainstream insurers are lining up to back him.
One of his clients is a job recruiting company that uses A.I. to sift through candidates.
“Which is great, but you can now discriminate at a scale we’ve never seen before,” Mr. Kvist said.
“It’s a breeding ground for class-action lawsuits.”
Mr. Kvist believes the work he is doing now will lay the foundation for more complex A.I. insurance policies to come.

Opinion | The A.I. Prompt That Could End the World
A destructive A.I., like a nuclear bomb, is now a concrete possibility; the question is whether anyone will be reckless enough to build one.