Tootfinder

The Alternative Hypothesis for Zeros of the Riemann Zeta-Function
Siegfred Alan C. Baluyot, Daniel Alan Goldston, Ade Irma Suriajaya, Caroline L. Turnage-Butterbaugh
https://arxiv.org/abs/2508.10857

The Alternative Hypothesis for Zeros of the Riemann Zeta-Function
In 2016, the first-named author introduced a formulation of the Alternative Hypothesis that assumes that consecutive zeros of the Riemann zeta-function are spaced at multiples of half of the average spacing, but does not assume that the zeros are simple. In this paper, we assume the Riemann Hypothesis and a similar formulation of the Alternative Hypothesis, and for each integer $k$ we obtain constraints on the density of pairs of zeros whose normalized differences are at $k/2$ times the average…

If quasars form from primordial black holes
Jeremy Mould, Adam Batten
https://arxiv.org/abs/2507.11023 https://arxiv.org/pdf/2507.110…

If quasars form from primordial black holes
We explore the consequences of a novel but increasingly well-supported hypothesis that supermassive black holes may have formed from primordial black holes form ed prior to, and rapidly growing in, the radiation-dominated universe. We show that this hypothesis can predict the luminosity of quasars and their luminosity distribution. With reasonable values of the parameters introduced, these predictions are borne out by observations. The model predicts density evolution in accordance with observa…

WIP: Exploring the Value of a Debugging Cheat Sheet and Mini Lecture in Improving Undergraduate Debugging Skills and Mindset
Andrew Ash, John Hu
https://arxiv.org/abs/2506.11339

WIP: Exploring the Value of a Debugging Cheat Sheet and Mini Lecture in Improving Undergraduate Debugging Skills and Mindset
This work-in-progress research paper explores the efficacy of a small-scale microelectronics debugging education intervention utilizing quasi-experimental design in an introductory microelectronics course for third-year electrical and computer engineering (ECE) students. In the first semester of research, the experimental group attended a debugging "mini lecture" covering two common sources of circuit error and received a debugging cheat sheet with recommendations for testing and hypothesis for…

Symmetry breaking for inductive logic programming
Andrew Cropper, David M. Cerna, Matti J\"arvisalo
https://arxiv.org/abs/2508.06263 https://arxiv.org…

Symmetry breaking for inductive logic programming
The goal of inductive logic programming is to search for a hypothesis that generalises training data and background knowledge. The challenge is searching vast hypothesis spaces, which is exacerbated because many logically equivalent hypotheses exist. To address this challenge, we introduce a method to break symmetries in the hypothesis space. We implement our idea in answer set programming. Our experiments on multiple domains, including visual reasoning and game playing, show that our approach …

Modelling Skewed and Heavy-Tailed Errors in Bayesian Mediation Analysis
Zongyu Li, Mark Steel, Zhiyong Zhang
https://arxiv.org/abs/2508.09311 https://arxiv…

Modelling Skewed and Heavy-Tailed Errors in Bayesian Mediation Analysis
Traditional mediation models in both the frequentist and Bayesian frameworks typically assume normality of the error terms. Violations of this assumption can impair the estimation and hypothesis testing of the mediation effect in conventional approaches. This study addresses the non-normality issue by explicitly modelling skewed and heavy-tailed error terms within the Bayesian mediation framework. Building on the work of Fernandez and Steel (1998), this study introduces a novel family of distri…

Experiments to test the hypothesis for solar and dark matter axions
Babette D\"obrich, Igor G. Irastorza
https://arxiv.org/abs/2507.06414 https://

Experiments to test the hypothesis for solar and dark matter axions
We present a pedagogical introduction to the direct search of axions as dark matter, as well as to searches for solar axions. The plethora of experimental searches exploit the axion's coupling to two photons: They attempt to convert the axion dark matter to photons in a resonator placed in an external magnetic field or convert solar axions into X-rays in a magnet pointing towards the sun. We give a basic introduction to this concept, its many variants and to searches that exploit the axion's ot…

Learning with Episodic Hypothesis Testing in General Games: A Framework for Equilibrium Selection
Ruifan Yang, Manxi Wu
https://arxiv.org/abs/2507.23149 https://

Learning with Episodic Hypothesis Testing in General Games: A Framework for Equilibrium Selection
We introduce a new hypothesis testing-based learning dynamics in which players update their strategies by combining hypothesis testing with utility-driven exploration. In this dynamics, each player forms beliefs about opponents' strategies and episodically tests these beliefs using empirical observations. Beliefs are resampled either when the hypothesis test is rejected or through exploration, where the probability of exploration decreases with the player's (transformed) utility. In general fin…

Alice and the Caterpillar: A more descriptive null model for assessing data mining results
Giulia Preti, Gianmarco De Francisci Morales, Matteo Riondato
https://arxiv.org/abs/2506.09764

Alice and the Caterpillar: A more descriptive null model for assessing data mining results
We introduce novel null models for assessing the results obtained from observed binary transactional and sequence datasets, using statistical hypothesis testing. Our null models maintain more properties of the observed dataset than existing ones. Specifically, they preserve the Bipartite Joint Degree Matrix of the bipartite (multi-)graph corresponding to the dataset, which ensures that the number of caterpillars, i.e., paths of length three, is preserved, in addition to other properties conside…

Learning Logical Rules using Minimum Message Length
Ruben Sharma, Sebastijan Duman\v{c}i\'c, Ross D. King, Andrew Cropper
https://arxiv.org/abs/2508.06230 https://

Learning Logical Rules using Minimum Message Length
Unifying probabilistic and logical learning is a key challenge in AI. We introduce a Bayesian inductive logic programming approach that learns minimum message length programs from noisy data. Our approach balances hypothesis complexity and data fit through priors, which explicitly favour more general programs, and a likelihood that favours accurate programs. Our experiments on several domains, including game playing and drug design, show that our method significantly outperforms previous method…

Holistic Explainable AI (H-XAI): Extending Transparency Beyond Developers in AI-Driven Decision Making
Kausik Lakkaraju, Siva Likitha Valluru, Biplav Srivastava
https://arxiv.org/abs/2508.05792

Holistic Explainable AI (H-XAI): Extending Transparency Beyond Developers in AI-Driven Decision Making
Current eXplainable AI (XAI) methods largely serve developers, often focusing on justifying model outputs rather than supporting diverse stakeholder needs. A recent shift toward Evaluative AI reframes explanation as a tool for hypothesis testing, but still focuses primarily on operational organizations. We introduce Holistic-XAI (H-XAI), a unified framework that integrates causal rating methods with traditional XAI methods to support explanation as an interactive, multi-method process. H-XAI al…