Tootfinder

Investigating New Physics through the Observables of Semileptonic $B_{s}\to K^{\ast}(\to K \pi)\mu^{ }\mu^{-}$ Decay
Zohaib Aarfi, Qazi Maaz Us Salam, Ishtiaq Ahmed, Faisal Munir Bhutta, Rizwan Khalid, M. Ali Paracha
https://arxiv.org/abs/2506.20446

Investigating New Physics through the Observables of Semileptonic $B_{s}\to K^{\ast}(\to K π)μ^{+}μ^{-}$ Decay
The rare four-fold decay $B_s \to K^*(\to Kπ)μ^+μ^- $, governed by the flavor-changing neutral current transition $b \to dμ^+μ^-$, provides a sensitive probe for testing the Standard Model (SM) and investigating signatures of new physics (NP). This work presents a comprehensive model-independent analysis of the decay using the framework of the weak effective field theory. We compute a set of key physical observables, including the differential branching ratio, forward-backward asymmetry, l…

How Hard is it to be a Star? Convex Geometry and the Real Hierarchy
Marcus Schaefer, Daniel \v{S}tefankovi\v{c}
https://arxiv.org/abs/2506.18818 https://…

How Hard is it to be a Star? Convex Geometry and the Real Hierarchy
A set is star-shaped if there is a point in the set that can see every other point in the set in the sense that the line-segment connecting the points lies within the set. We show that testing whether a non-empty compact smooth region is star-shaped is $\forall\mathbb{R}$-complete. Since the obvious definition of star-shapedness has logical form $\exists\forall$, this is a somewhat surprising result, based on Krasnosel'ski\uı's theorem from convex geometry; we study several related complexity …

When you are a swift developer, every day is Xmas!
https://forums.swift.org/t/swift-sdks-for-webassembly-now-available-on-swift-org/80405

Swift SDKs for WebAssembly now available on swift.org
As the Platform Steering Group accepted the vision document for WebAssembly support, we’re excited to announce that Swift SDKs for Wasm are now available at swift.org/install. The website now also hosts a getting started guide for Wasm with installation and build instructions. You may notice "Swift SDKs" is in plural. The reason is that artifact bundles for Wasm distributed from swift.org include two Swift SDKs: one with the full feature set of the Swift standard library and Swift Testing, a…

CT Radiomics-Based Explainable Machine Learning Model for Accurate Differentiation of Malignant and Benign Endometrial Tumors: A Two-Center Study
Tingrui Zhang, Honglin Wu, Zekun Jiang, Yingying Wang, Rui Ye, Huiming Ni, Chang Liu, Jin Cao, Xuan Sun, Rong Shao, Xiaorong Wei, Yingchun Sun
https://arxiv.org/abs/2506.18106

CT Radiomics-Based Explainable Machine Learning Model for Accurate Differentiation of Malignant and Benign Endometrial Tumors: A Two-Center Study
Aimed to develop and validate a CT radiomics-based explainable machine learning model for diagnosing malignancy and benignity specifically in endometrial cancer (EC) patients. A total of 83 EC patients from two centers, including 46 with malignant and 37 with benign conditions, were included, with data split into a training set (n=59) and a testing set (n=24). The regions of interest (ROIs) were manually segmented from pre-surgical CT scans, and 1132 radiomic features were extracted from the pr…

Getting the Windows dev box set up for scopehal testing.
The most important step...

Guaranteed Guess: A Language Modeling Approach for CISC-to-RISC Transpilation with Testing Guarantees
Ahmed Heakl, Sarim Hashmi, Chaimaa Abi, Celine Lee, Abdulrahman Mahmoud
https://arxiv.org/abs/2506.14606

Guaranteed Guess: A Language Modeling Approach for CISC-to-RISC Transpilation with Testing Guarantees
The hardware ecosystem is rapidly evolving, with increasing interest in translating low-level programs across different instruction set architectures (ISAs) in a quick, flexible, and correct way to enhance the portability and longevity of existing code. A particularly challenging class of this transpilation problem is translating between complex- (CISC) and reduced- (RISC) hardware architectures, due to fundamental differences in instruction complexity, memory models, and execution paradigms. I…

Optimal Non-Adaptive Group Testing with One-Sided Error Guarantees
Daniel McMorrow, Jonathan Scarlett
https://arxiv.org/abs/2506.10374 https://

Optimal Non-Adaptive Group Testing with One-Sided Error Guarantees
The group testing problem consists of determining a sparse subset of defective items from within a larger set of items via a series of tests, where each test outcome indicates whether at least one defective item is included in the test. We study the approximate recovery setting, where the recovery criterion of the defective set is relaxed to allow a small number of items to be misclassified. In particular, we consider one-sided approximate recovery criteria, where we allow either only false neg…

Labelling Data with Unknown References
Adrian de Wynter
https://arxiv.org/abs/2506.03083 https://arxiv.org/pdf/2506.03083

Labelling Data with Unknown References
An evaluator is trustworthy when there exists some agreed-upon way to measure its performance as a labeller. The two ways to establish trustworthiness are either by testing it, or by assuming the evaluator `knows' somehow the way to label the corpus. However, if labelled references (e.g., a development set) are unavailable, neither of these approaches work: the former requires the data, and the latter is an assumption, not evidence. To address this, we introduce an algorithm (the `No-Data Algor…

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Remote fetch replies is set as experimental and also asynchronous, unclear if it would be ready for the final release. https://mastodon.social/@MastodonEngineering/114625074809479231

Conditional Method Confidence Set
Lukas Bauer, Ekaterina Kazak
https://arxiv.org/abs/2505.21278 https://arxiv.org/pdf/2505.21278

Conditional Method Confidence Set
This paper proposes a Conditional Method Confidence Set (CMCS) which allows to select the best subset of forecasting methods with equal predictive ability conditional on a specific economic regime. The test resembles the Model Confidence Set by Hansen et al. (2011) and is adapted for conditional forecast evaluation. We show the asymptotic validity of the proposed test and illustrate its properties in a simulation study. The proposed testing procedure is particularly suitable for stress-testing …

Testing Suffixient Sets
Davide Cenzato, Francisco Olivares, Nicola Prezza
https://arxiv.org/abs/2506.08225 https://arxiv.org/pdf/2506…

Testing Suffixient Sets
Suffixient sets are a novel prefix array (PA) compression technique based on subsampling PA (rather than compressing the entire array like previous techniques used to do): by storing very few entries of PA (in fact, a compressed number of entries), one can prove that pattern matching via binary search is still possible provided that random access is available on the text. In this paper, we tackle the problems of determining whether a given subset of text positions is (1) a suffixient set or (2)…

Polynomial-Time Algorithms for Black-Box Distributive Expanded Groups
Mikhail Anokhin
https://arxiv.org/abs/2505.20497 https://arxiv.…

Polynomial-Time Algorithms for Black-Box Distributive Expanded Groups
Let $Ω$ be a finite set of finitary operation symbols. An $Ω$-expanded group is a group (written additively and called the additive group of the $Ω$-expanded group) with an $Ω$-algebra structure. We use the black-box model of computation in $Ω$-expanded groups. In this model, elements of a finite $Ω$-expanded group $H$ are represented (not necessarily uniquely) by bit strings of the same length, say, $n$. Given representations of elements of $H$, equality testing and the fundamental opera…

Detecting non-uniform patterns on high-dimensional hyperspheres
Tiefeng Jiang, Tuan Pham
https://arxiv.org/abs/2506.00444 https://arx…

Detecting non-uniform patterns on high-dimensional hyperspheres
We propose a new probabilistic characterization of the uniform distribution on hyperspheres in terms of its inner product, extending the ideas of \cite{cuesta2009projection,cuesta2007sharp} in a data-driven manner. Using this characterization, we define a new distance that quantifies the deviation of an arbitrary distribution from uniformity. As an application, we construct a novel nonparametric test for the uniformity testing problem: determining whether a set of \(n\) i.i.d. random points on …

Evaluating financial tail risk forecasts: Testing Equal Predictive Ability
Lukas Bauer
https://arxiv.org/abs/2505.23333 https://arxiv…

Evaluating financial tail risk forecasts: Testing Equal Predictive Ability
This paper provides comprehensive simulation results on the finite sample properties of the Diebold-Mariano (DM) test by Diebold and Mariano (1995) and the model confidence set (MCS) testing procedure by Hansen et al. (2011) applied to the asymmetric loss functions specific to financial tail risk forecasts, such as Value-at-Risk (VaR) and Expected Shortfall (ES). We focus on statistical loss functions that are strictly consistent in the sense of Gneiting (2011a). We find that the tests show lit…