Tootfinder

This sickening disgrace showcased all that is vile about Trump - Raw Story
https://www.rawstory.com/raw-investigates/tru…

This sickening disgrace showcased all that is vile about Trump
Before Juneteenth fades away in the rearview mirror, as yet another Republican president recklessly drives us toward yet another unwinnable war in the Middle East, I want to spend just a few minutes on this federal holiday, and the very old and sickening reasons lowlifes like Donald Trump make a poi...

Raiders report: Ashton Jeanty unimpressed by viral run, Madden rating https://www.reviewjournal.com/sports/raiders/raiders-report-ashton-jeanty-unimpressed-by-viral-run-madden-rating-3426638/

From Logic to Language: A Trust Index for Problem Solving with LLMs
Tehseen Rug, Felix B\"ohmer, Tessa Pfattheicher
https://arxiv.org/abs/2507.16028 h…

From Logic to Language: A Trust Index for Problem Solving with LLMs
Classical computation, grounded in formal, logical systems, has been the engine of technological progress for decades, excelling at problems that can be described with unambiguous rules. This paradigm, however, leaves a vast ocean of human problems -- those characterized by ambiguity, dynamic environments, and subjective context -- largely untouched. The advent of Large Language Models (LLMs) represents a fundamental shift, enabling computational systems to engage with this previously inaccessi…

Krugman:
❝What we’re looking at now isn’t the worst job market college graduates have ever seen. It is, however, the worst such market compared with workers in general that we’ve ever seen, by a large margin.
…
We have low overall unemployment, only slightly above historic lows, but unemployment among college graduates between 22 and 27 at recession-like levels.
This has never happened before.❞
https://paulkrugman.substack.com/p/bad-times-for-college-graduates

Left Leaning Models: AI Assumptions on Economic Policy
Maxim Chupilkin
https://arxiv.org/abs/2507.15771 https://arxiv.org/pdf/2507.15…

Left Leaning Models: AI Assumptions on Economic Policy
How does AI think about economic policy? While the use of large language models (LLMs) in economics is growing exponentially, their assumptions on economic issues remain a black box. This paper uses a conjoint experiment to tease out the main factors influencing LLMs' evaluation of economic policy. It finds that LLMs are most sensitive to unemployment, inequality, financial stability, and environmental harm and less sensitive to traditional macroeconomic concerns such as economic growth, inflat…

Breakdown of the thermodynamic limit in quantum spin and dimer models
Jeet Shah, Laura Shou, Jeremy Shuler, Victor Galitski
https://arxiv.org/abs/2506.15769

Breakdown of the thermodynamic limit in quantum spin and dimer models
The thermodynamic limit is foundational to statistical mechanics, underlying our understanding of many-body phases. It assumes that, as the system size grows infinitely at fixed density of particles, unambiguous macroscopic phases emerge that are independent of the system's boundary shape. We present explicit quantum spin and dimer Hamiltonians whose ground states violate this principle. Our construction relies on the previous mathematical work on classical dimers on the Aztec diamond and the s…

Artifacts in Halo Shapes: Imprints of the Initial Condition
Yu Yu, Zhao Chen
https://arxiv.org/abs/2507.16745 https://arxiv.org/pdf/2…

Artifacts in Halo Shapes: Imprints of the Initial Condition
Grid type pre-initial conditions are commonly used to initialize particle positions in cosmological simulations. While these conditions are known to produce noticeable numerical artifacts in void regions, their impact on halo properties has generally been assumed to be negligible. In this work, we employ multiple simulations to demonstrate that grid initialization induces statistically significant artifacts in halo shapes, despite the modest absolute amplitude ($\sim 1\%$) making them unimporta…

Humans, Machine Learning, and Language Models in Union: A Cognitive Study on Table Unionability
Sreeram Marimuthu, Nina Klimenkova, Roee Shraga
https://arxiv.org/abs/2506.12990

Humans, Machine Learning, and Language Models in Union: A Cognitive Study on Table Unionability
Data discovery and table unionability in particular became key tasks in modern Data Science. However, the human perspective for these tasks is still under-explored. Thus, this research investigates the human behavior in determining table unionability within data discovery. We have designed an experimental survey and conducted a comprehensive analysis, in which we assess human decision-making for table unionability. We use the observations from the analysis to develop a machine learning framewor…

New Insights into the Nature and Orbital Motion of Aristotle's Comet in 372 BC
Zdenek Sekanina
https://arxiv.org/abs/2507.15228 https://

New Insights into the Nature and Orbital Motion of Aristotle's Comet in 372 BC
Extending the investigation of the presumed primordial comet as part of continuing work on a new model of the Kreutz sungrazer system, I confront a previously derived set of orbital elements with Aristotle's remarks in his Meteorologica to test their compatibility and determine the comet's perihelion time. The two translations of the treatise into English that I am familiar with differ at one point substantially from each other. Unambiguously, the year and season of the comet's appearance was e…

MS-UMamba: An Improved Vision Mamba Unet for Fetal Abdominal Medical Image Segmentation
Caixu Xu, Junming Wei, Huizhen Chen, Pengchen Liang, Bocheng Liang, Ying Tan, Xintong Wei
https://arxiv.org/abs/2506.12441

MS-UMamba: An Improved Vision Mamba Unet for Fetal Abdominal Medical Image Segmentation
Recently, Mamba-based methods have become popular in medical image segmentation due to their lightweight design and long-range dependency modeling capabilities. However, current segmentation methods frequently encounter challenges in fetal ultrasound images, such as enclosed anatomical structures, blurred boundaries, and small anatomical structures. To address the need for balancing local feature extraction and global context modeling, we propose MS-UMamba, a novel hybrid convolutional-mamba mo…