Tootfinder

Riddled basin geometry sets fundamental limits to predictability and reproducibility in deep learning
Andrew Ly, Pulin Gong
https://arxiv.org/abs/2510.05606 https://

Riddled basin geometry sets fundamental limits to predictability and reproducibility in deep learning
Fundamental limits to predictability are central to our understanding of many physical and computational systems. Here we show that, despite its remarkable capabilities, deep learning exhibits such fundamental limits rooted in the fractal, riddled geometry of its basins of attraction: any initialization that leads to one solution lies arbitrarily close to another that leads to a different one. We derive sufficient conditions for the emergence of riddled basins by analytically linking features w…

🤔 Maybe there's something interesting there as well?
#tegernsee #BergfilmFestival

Series D, Episode 10 - Gold
AVON: But I shouldn't imagine it's much use to you now. You'll just have to confess and pay up.
TARRANT: [Into comm.] We're ready, Vila.
KEILLER: Avon, what about me?
https://blake.torpidity.net/m/410/406 B7B4

The Landscape of Collapsar Outflows: Structure, Signatures and Origins of Einstein Probe Relativistic Supernova Transients
Ore Gottlieb
https://arxiv.org/abs/2509.04551 https://…

The Landscape of Collapsar Outflows: Structure, Signatures and Origins of Einstein Probe Relativistic Supernova Transients
The Einstein Probe is revolutionizing time-domain astrophysics through the discovery of new classes of X-ray transients associated with Type Ic-Broad Line supernovae. These events commonly exhibit bright early-time optical counterparts, and sudden afterglow rebrightening within the first week - features that existing models fail to explain. In particular, structured jet and cocoon scenarios are inconsistent with the observed sharp rebrightening and multi-day optical emission, while the refreshe…

What-If Analysis of Large Language Models: Explore the Game World Using Proactive Thinking
Yuan Sui, Yanming Zhang, Yi Liao, Yu Gu, Guohua Tang, Zhongqian Sun, Wei Yang, Bryan Hooi
https://arxiv.org/abs/2509.04791

What-If Analysis of Large Language Models: Explore the Game World Using Proactive Thinking
Large language models (LLMs) excel at processing information reactively but lack the ability to systemically explore hypothetical futures. They cannot ask, "what if we take this action? how will it affect the final outcome" and forecast its potential consequences before acting. This critical gap limits their utility in dynamic, high-stakes scenarios like strategic planning, risk assessment, and real-time decision making. To bridge this gap, we propose WiA-LLM, a new paradigm that equips LLMs wi…

Moody Urbanity - Up 😶‍🌫️
情绪化城市 - 上面 😶‍🌫️
📷 Nikon FE
🎞️ Ilford HP5 Plus 400, expired 1993
#filmphotography #Photography #blackandwhite

The garden festival / Landesgartenschau was not just about #gardening. There were also events etc. (Which we didn't attend)
One place was about #floristry with really beautifully decorated arrangements. I'm always a bit jealous of such things. They look really beautiful, and requir…

On Convergence Rates of General $N$-Player Stackelberg Games to their Mean Field Limits
Alain Bensoussan, Ziyu Huang, Sheng Wang, Sheung Chi Phillip Yam
https://arxiv.org/abs/2510.02380

On Convergence Rates of General $N$-Player Stackelberg Games to their Mean Field Limits
In this article, we establish precise convergence rates of a general class of $N$-Player Stackelberg games to their mean field limits, which allows the response time delay of information, empirical distribution based interactions, and the control-dependent diffusion coefficients. All these features makes our problem nonstandard, barely been touched in the literature, and they complicate the analysis and therefore reduce the convergence rate. We first justify the same convergence rate for both t…

Deconstructing the Crystal Ball: From Ad-Hoc Prediction to Principled Startup Evaluation with the SAISE Framework
Seyed Mohammad Ali Jafari, Ali Mobini Dehkordi, Ehsan Chitsaz, Yadollah Yaghoobzadeh
https://arxiv.org/abs/2508.05491

Deconstructing the Crystal Ball: From Ad-Hoc Prediction to Principled Startup Evaluation with the SAISE Framework
The integration of Artificial Intelligence (AI) into startup evaluation represents a significant technological shift, yet the academic research underpinning this transition remains methodologically fragmented. Existing studies often employ ad-hoc approaches, leading to a body of work with inconsistent definitions of success, atheoretical features, and a lack of rigorous validation. This fragmentation severely limits the comparability, reliability, and practical utility of current predictive mod…

Signatures from Non-classical Features of Axion Dark Matter in Cavity Haloscopes
Erik W. Lentz
https://arxiv.org/abs/2509.03877 https://arxiv.org/pdf/2509.…

Signatures from Non-classical Features of Axion Dark Matter in Cavity Haloscopes
I present in this article how non-classical features in the local axion dark matter state may imprint on cavity haloscopes. Example signatures from squeezed and pair-entangled DM states are presented and their potential for sensitivity enhancements of experimental searches attuned to these signatures compared to traditional classical field signatures are discussed.