Tootfinder

President Trump orders regulators to investigate banks for "politicized or unlawful debanking", echoing allegations from conservatives and the crypto industry (Joel Khalili/Wired)
https://www.wired.com/story/donald-trump-orders-crackdow…

Donald Trump Orders Crackdown on Politically-Motivated ‘Debanking’
In a new executive order, the US president has called on federal regulators to investigate and punish banks for alleged discrimination against conservatives and certain types of business.

Differentially Private Model-X Knockoffs via Johnson-Lindenstrauss Transform
Yuxuan Tao, Adel Javanmard
https://arxiv.org/abs/2508.04800 https://arxiv.org/…

Differentially Private Model-X Knockoffs via Johnson-Lindenstrauss Transform
We introduce a novel privatization framework for high-dimensional controlled variable selection. Our framework enables rigorous False Discovery Rate (FDR) control under differential privacy constraints. While the Model-X knockoff procedure provides FDR guarantees by constructing provably exchangeable ``negative control" features, existing privacy mechanisms like Laplace or Gaussian noise injection disrupt its core exchangeability conditions. Our key innovation lies in privatizing the data knock…

The Alliance for International Exchange told Newsweek that it had learned that the Office of Management and Budget (OMB)
🆘 had decided to cut at least 22 offerings from the Bureau of Educational and Cultural Affairs (ECA)
totaling around $100 million in annual funding.
"While this does not impact flagship programs like Fulbright, Gilman, and IVLP at the moment,
it sets a dangerous precedent," Mark Overmann, executive director of the Alliance, told Newsweek. …

Fears Over Fulbright's Future as Trump Admin Cuts Exchange Programs
Funding for over 20 programs was reported to have been cut, leaving participants in limbo.

SLOPE and Designing Robust Studies for Generalization
Xinran Miao, Jiwei Zhao, Hyunseung Kang
https://arxiv.org/abs/2510.01577 https://arxiv.org/pdf/2510.0…

SLOPE and Designing Robust Studies for Generalization
A popular task in generalization is to learn about a new, target population based on data from an existing, source population. This task relies on conditional exchangeability, which asserts that differences between the source and target populations are fully captured by observable characteristics of the two populations. Unfortunately, this assumption is often untenable in practice due to unobservable differences between the source and target populations. Worse, the assumption cannot be verified…

Multisession Longitudinal Dynamic MRI Incorporating Patient-Specific Prior Image Information Across Time
Jingjia Chen, Hersh Chandarana, Daniel K. Sodickson, Li Feng
https://arxiv.org/abs/2507.19636

Multisession Longitudinal Dynamic MRI Incorporating Patient-Specific Prior Image Information Across Time
Serial Magnetic Resonance Imaging (MRI) exams are often performed in clinical practice, offering shared anatomical and motion information across imaging sessions. However, existing reconstruction methods process each session independently without leveraging this valuable longitudinal information. In this work, we propose a novel concept of longitudinal dynamic MRI, which incorporates patient-specific prior images to exploit temporal correlations across sessions. This framework enables progressi…

Promoting Efficient Reasoning with Verifiable Stepwise Reward
Chuhuai Yue, Chengqi Dong, Yinan Gao, Hang He, Jiajun Chai, Guojun Yin, Wei Lin
https://arxiv.org/abs/2508.10293 ht…

Promoting Efficient Reasoning with Verifiable Stepwise Reward
Large reasoning models (LRMs) have recently achieved significant progress in complex reasoning tasks, aided by reinforcement learning with verifiable rewards. However, LRMs often suffer from overthinking, expending excessive computation on simple problems and reducing efficiency. Existing efficient reasoning methods typically require accurate task assessment to preset token budgets or select reasoning modes, which limits their flexibility and reliability. In this work, we revisit the essence of…

Evaluating sugarcane bagasse-based biochar as an economically viable catalyst for agricultural and environmental advancement in Brazil through scenario-based economic modeling
Sebastian G. Nosenzo
https://arxiv.org/abs/2508.12454

Evaluating sugarcane bagasse-based biochar as an economically viable catalyst for agricultural and environmental advancement in Brazil through scenario-based economic modeling
The increasing global demand for sustainable agricultural practices and effective waste management has highlighted the potential of biochar as a multifaceted solution. This study evaluates the economic viability of sugarcane bagasse-based biochar in Brazil, focusing on its potential to enhance agricultural productivity and contribute to environmental sustainability. While existing literature predominantly explores the production, crop yield benefits, and carbon sequestration capabilities of bio…