Tootfinder

Evolutionary Generative Optimization: Towards Fully Data-Driven Evolutionary Optimization via Generative Learning
Kebin Sun, Tao Jiang, Ran Cheng, Yaochu Jin, Kay Chen Tan
https://arxiv.org/abs/2508.00380

Evolutionary Generative Optimization: Towards Fully Data-Driven Evolutionary Optimization via Generative Learning
Recent advances in data-driven evolutionary algorithms (EAs) have demonstrated the potential of leveraging data to improve optimization accuracy and adaptability. Nevertheless, most existing approaches remain dependent on handcrafted heuristics, which limits their generality and automation. To address this challenge, we propose Evolutionary Generative Optimization (EvoGO), a fully data-driven framework empowered by generative learning. EvoGO streamlines the evolutionary optimization process int…

The Most Luminous Known Fast Blue Optical Transient AT 2024wpp: Unprecedented Evolution and Properties in the Ultraviolet to the Near-Infrared
Natalie LeBaron, Raffaella Margutti, Ryan Chornock, A. J. Nayana, Olivia Aspegren, Wenbin Lu, Brian Metzger, Daniel Kasen, Thomas Brink, Sergio Campana, Paolo D'Avanzo, Jakob Faber, Matteo Ferro, Alex Filippenko, Ryan Foley, Xinze Guo, Erica Hammerstein, Saurabh Jha, Charles Kilpatrick, Giulia Migliori, Dan Milisavljevic, Kishore Patra, Huei…

The Most Luminous Known Fast Blue Optical Transient AT 2024wpp: Unprecedented Evolution and Properties in the Ultraviolet to the Near-Infrared
We present an extensive photometric and spectroscopic ultraviolet-optical-infrared campaign on the luminous fast blue optical transient (LFBOT) AT 2024wpp over the first ~100 d. AT 2024wpp is the most luminous LFBOT discovered to date, with $L_{\rm{pk}}\approx(2-4)\times10^{45}$ erg s$^{-1}$ (5-10 times that of the prototypical AT 2018cow). This extreme luminosity enabled the acquisition of the most detailed LFBOT UV light curve thus far. In the first ~45 d, AT 2024wpp radiated $>10^{51}$ erg, …

C.J. Stroud exits game after hard hit, being evaluated for concussion https://www.nytimes.com/athletic/6771234/2025/11/02/c-j-stroud-exits-texans-broncos-concussion/

When Hallucination Costs Millions: Benchmarking AI Agents in High-Stakes Adversarial Financial Markets
Zeshi Dai, Zimo Peng, Zerui Cheng, Ryan Yihe Li
https://arxiv.org/abs/2510.00332

When Hallucination Costs Millions: Benchmarking AI Agents in High-Stakes Adversarial Financial Markets
We present CAIA, a benchmark exposing a critical blind spot in AI evaluation: the inability of state-of-the-art models to operate in adversarial, high-stakes environments where misinformation is weaponized and errors are irreversible. While existing benchmarks measure task completion in controlled settings, real-world deployment demands resilience against active deception. Using crypto markets as a testbed where $30 billion was lost to exploits in 2024, we evaluate 17 models on 178 time-anchore…

The Diversity and Evolution of Dust Attenuation Curves from Redshift z ~ 1 to 9
Irene Shivaei, Rohan P. Naidu, Francisco Rodr\'iguez Montero, Kosei Matsumoto, Joel Leja, Jorryt Matthee, Benjamin D. Johnson, Pascal A. Oesch, Jacopo Chevallard, Angela Adamo, Sarah Bodansky, Andrew J. Bunker, Alba Covelo Paz, Claudia Di Cesare, Eiichi Egami, Lukas J. Furtak, Kasper E. Heintz, Ivan Kramarenko, Romain A. Meyer, Naveen A. Reddy, Pierluigi Rinaldi, Sandro Tacchella, Alberto Torralba, Jori…

The Diversity and Evolution of Dust Attenuation Curves from Redshift z ~ 1 to 9
The UV-optical dust attenuation curve is key to interpreting the intrinsic properties of galaxies and provides insights into the nature of dust grains and their geometry relative to stars. In this work, we constrain the UV-optical slope of the stellar attenuation curve using a spectroscopic-redshift sample of ~3300 galaxies at z~1-9, to characterize the diversity and redshift evolution of stellar attenuation curves and to gain insight into dust production and evolution at high redshifts. The sa…

Development and Evaluation of an AI-Driven Telemedicine System for Prenatal Healthcare
Juan Barrientos, Michaelle P\'erez, Douglas Gonz\'alez, Favio Reyna, Julio Fajardo, Andrea Lara
https://arxiv.org/abs/2510.01194

Development and Evaluation of an AI-Driven Telemedicine System for Prenatal Healthcare
Access to obstetric ultrasound is often limited in low-resource settings, particularly in rural areas of low- and middle-income countries. This work proposes a human-in-the-loop artificial intelligence (AI) system designed to assist midwives in acquiring diagnostically relevant fetal images using blind sweep protocols. The system incorporates a classification model along with a web-based platform for asynchronous specialist reviews. By identifying key frames in blind sweep studies, the AI syste…

The evolution of influence operations
from crude Russian troll farms to sophisticated AI systems using large language models;
the discovery of GoLaxy documents revealing a "Smart Propaganda System" that collects millions of data points daily, builds psychological profiles, and generates resilient personas;
the fundamental challenges of measuring effectiveness;
GoLaxy's ties to Chinese intelligence agencies;
operations targeting Hong Kong's…

On three classes of logarithmic integrals
Necdet Bat{\i}r, Nandan Sai Dasireddy
https://arxiv.org/abs/2510.00870 https://arxiv.org/pdf/2510.00870

On three classes of logarithmic integrals
In this paper, we evaluate the following families of definite integrals in closed form and we show that they are expressible only in terms of the dilogarithm function and the inverse tangent integral, and elementary functions. \begin{equation*} \int_{0}^{1}\frac{\log\big(x^m+1\big)}{x+1}\thinspace{\rm d}x \quad \mbox{and}\quad \int_{0}^{1}\frac{\log\big(x^m+1\big)}{x^2+1}\thinspace{\rm d}x, \end{equation*} where $m$ is a positive odd integer. When $m$ is a positive even integer, these integrals…

Stable Cinemetrics : Structured Taxonomy and Evaluation for Professional Video Generation
Agneet Chatterjee, Rahim Entezari, Maksym Zhuravinskyi, Maksim Lapin, Reshinth Adithyan, Amit Raj, Chitta Baral, Yezhou Yang, Varun Jampani
https://arxiv.org/abs/2509.26555

Stable Cinemetrics : Structured Taxonomy and Evaluation for Professional Video Generation
Recent advances in video generation have enabled high-fidelity video synthesis from user provided prompts. However, existing models and benchmarks fail to capture the complexity and requirements of professional video generation. Towards that goal, we introduce Stable Cinemetrics, a structured evaluation framework that formalizes filmmaking controls into four disentangled, hierarchical taxonomies: Setup, Event, Lighting, and Camera. Together, these taxonomies define 76 fine-grained control nodes…

The Most Luminous Known Fast Blue Optical Transient AT 2024wpp: Unprecedented Evolution and Properties in the X-rays and Radio
A. J. Nayana, Raffaella Margutti, Eli Wiston, Tanmoy Laskar, Giulia Migliori, Ryan Chornock, Timothy J. Galvin, Natalie LeBaron, Aprajita Hajela, Collin T. Christy, Itai Sfaradi, Daichi Tsuna, Olivia Aspegren, Fabio De Colle, Brian D. Metzger, Wenbin Lu, Paz Beniamini, Daniel Kasen, Edo Berger, Brian W. Grefenstette, Kate D. Alexander, G. C. Anupama, Deanne L. …

The Most Luminous Known Fast Blue Optical Transient AT 2024wpp: Unprecedented Evolution and Properties in the X-rays and Radio
We present X-ray (0.3--79 keV) and radio (0.25--203 GHz) observations of the most luminous Fast Blue Optical Transient (LFBOT) AT\,2024wpp at $z=0.0868$, spanning 2--280 days after first light. AT 2024wpp shows luminous ($L_{\rm X} \approx 1.5 \times 10^{43}\, \rm erg\,s^{-1}$), variable X-ray emission with a Compton hump peaking at $δt \approx 50$ days. The X-ray spectrum evolves from a soft ($F_ν \propto ν^{-0.6}$) to an extremely hard state ($F_ν \propto ν^{1.26}$) accompanied by a re-b…