Tootfinder

Non-iid hypothesis testing: from classical to quantum
Giacomo De Palma, Marco Fanizza, Connor Mowry, Ryan O'Donnell
https://arxiv.org/abs/2510.06147 https://

Non-iid hypothesis testing: from classical to quantum
We study hypothesis testing (aka state certification) in the non-identically distributed setting. A recent work (Garg et al. 2023) considered the classical case, in which one is given (independent) samples from $T$ unknown probability distributions $p_1, \dots, p_T$ on $[d] = \{1, 2, \dots, d\}$, and one wishes to accept/reject the hypothesis that their average $p_{\mathrm{avg}}$ equals a known hypothesis distribution $q$. Garg et al. showed that if one has just $c = 2$ samples from each $p_i$,…

Geometric Model Selection for Latent Space Network Models: Hypothesis Testing via Multidimensional Scaling and Resampling Techniques
Jieyun Wang, Anna L. Smith
https://arxiv.org/abs/2510.06136

Geometric Model Selection for Latent Space Network Models: Hypothesis Testing via Multidimensional Scaling and Resampling Techniques
Latent space models assume that network ties are more likely between nodes that are closer together in an underlying latent space. Euclidean space is a popular choice for the underlying geometry, but hyperbolic geometry can mimic more realistic patterns of ties in complex networks. To identify the underlying geometry, past research has applied non-Euclidean extensions of multidimensional scaling (MDS) to the observed geodesic distances: the shortest path lengths between nodes. The difference in…

An examination of the two-peak hypothesis of $P_{\Psi s}^{\Lambda}(4459)$ using heavy quark symmetries
Duygu Y{\i}ld{\i}r{\i}m
https://arxiv.org/abs/2508.05265 https://

An examination of the two-peak hypothesis of $P_{Ψs}^Λ(4459)$ using heavy quark symmetries
The LHCb Collaboration announcement regarding the observation of the $P_{Ψs}^Λ (4459)$ stated that it might consist of two resonances rather than a single one. Naturally, the structure and composition of $P_{Ψs}^Λ(4459)$ state has prompted significant interest among researchers. Within the framework of generalized flavor-spin symmetry, the $P_{Ψs}^Λ(4459)$ has been correlated with the previously identified as one-peak states $P_c(4450)$, which were later found to be two-peak, $P_{c\bar{c}…

Hypothesis Selection: A High Probability Conundrum
Anders Aamand, Maryam Aliakbarpour, Justin Y. Chen, Sandeep Silwal
https://arxiv.org/abs/2509.03734 https://

Hypothesis Selection: A High Probability Conundrum
In the hypothesis selection problem, we are given a finite set of candidate distributions (hypotheses), $\mathcal{H} = \{H_1, \ldots, H_n\}$, and samples from an unknown distribution $P$. Our goal is to find a hypothesis $H_i$ whose total variation distance to $P$ is comparable to that of the nearest hypothesis in $\mathcal{H}$. If the minimum distance is $\mathsf{OPT}$, we aim to output an $H_i$ such that, with probability at least $1-δ$, its total variation distance to $P$ is at most $C \cdo…

Construction of optimal tests for symmetry on the torus and their quantitative error bounds
Andreas Anastasiou, Christophe Ley, Sophia Loizidou
https://arxiv.org/abs/2510.06055 …

Construction of optimal tests for symmetry on the torus and their quantitative error bounds
In this paper, we develop optimal tests for symmetry on the hyper-dimensional torus, leveraging Le Cam's methodology. We address both scenarios where the center of symmetry is known and where it is unknown. These tests are not only valid under a given parametric hypothesis but also under a very broad class of symmetric distributions. The asymptotic behavior of the proposed tests is studied both under the null hypothesis and local alternatives, and we derive quantitative bounds on the distributi…

Uniform Information Density and Syntactic Reduction: Revisiting $\textit{that}$-Mentioning in English Complement Clauses
Hailin Hao, Elsi Kaiser
https://arxiv.org/abs/2509.05254

Uniform Information Density and Syntactic Reduction: Revisiting $\textit{that}$-Mentioning in English Complement Clauses
Speakers often have multiple ways to express the same meaning. The Uniform Information Density (UID) hypothesis suggests that speakers exploit this variability to maintain a consistent rate of information transmission during language production. Building on prior work linking UID to syntactic reduction, we revisit the finding that the optional complementizer $\textit{that}$in English complement clauses is more likely to be omitted when the clause has low information density (i.e., more predicta…

When AI Gets Persuaded, Humans Follow: Inducing the Conformity Effect in Persuasive Dialogue
Rikuo Sasaki, Michimasa Inaba
https://arxiv.org/abs/2510.04229 https://

When AI Gets Persuaded, Humans Follow: Inducing the Conformity Effect in Persuasive Dialogue
Recent advancements in AI have highlighted its application in captology, the field of using computers as persuasive technologies. We hypothesized that the "conformity effect," where individuals align with others' actions, also occurs with AI agents. This study verifies this hypothesis by introducing a "Persuadee Agent" that is persuaded alongside a human participant in a three-party persuasive dialogue with a Persuader Agent. We conducted a text-based dialogue experiment with human participants…

Iterative Hypothesis Pruning and Distribution-based Early Labeling for Sequential Hypothesis Testing
George Vershinin, Asaf Cohen, Omer Gurewitz
https://arxiv.org/abs/2509.25908

Iterative Hypothesis Pruning and Distribution-based Early Labeling for Sequential Hypothesis Testing
We consider the problem where an active Decision-Maker (DM) is tasked to identify the true hypothesis using as few samples as possible while maintaining accuracy. The DM collects samples according to its determined actions and knows the distributions under each hypothesis. We propose the $Φ$-$Δ$ algorithm, a deterministic and adaptive multi-stage hypothesis-elimination algorithm where the DM selects an action, applies it repeatedly, and discards hypotheses in light of its obtained samples. Th…

Adversarial Decision-Making in Partially Observable Multi-Agent Systems: A Sequential Hypothesis Testing Approach
Haosheng Zhou, Daniel Ralston, Xu Yang, Ruimeng Hu
https://arxiv.org/abs/2509.03727

Adversarial Decision-Making in Partially Observable Multi-Agent Systems: A Sequential Hypothesis Testing Approach
Adversarial decision-making in partially observable multi-agent systems requires sophisticated strategies for both deception and counter-deception. This paper presents a sequential hypothesis testing (SHT)-driven framework that captures the interplay between strategic misdirection and inference in adversarial environments. We formulate this interaction as a partially observable Stackelberg game, where a follower agent (blue team) seeks to fulfill its primary task while actively misleading an ad…

Krylov exponents and power spectra for maximal quantum chaos: an EFT approach
Saskia Demulder, Maria Knysh, Andrew Rolph
https://arxiv.org/abs/2508.05444 https://

Krylov exponents and power spectra for maximal quantum chaos: an EFT approach
We examine the effective field theory (EFT) of maximal chaos through the lens of Krylov complexity and the Universal Operator Growth Hypothesis. We test the relationship between two measures of quantum chaos: out-of-time-ordered correlators (OTOCs) and Krylov complexity. In the EFT, a shift symmetry of the hydrodynamic modes enforces the maximal Lyapunov exponent in OTOCs, $λ_L = 2πT$, while simultaneously constraining thermal two-point autocorrelators. We solve these constraints on the autoc…

Serre weight conjectures for $\mathrm{GSp}_4$
Daniel Le, Bao V. Le Hung, Heejong Lee
https://arxiv.org/abs/2510.04805 https://arxiv.org/pdf/2510.04805

Serre weight conjectures for $\mathrm{GSp}_4$
We prove the weight part of Serre's conjecture for Galois representations valued in $\mathrm{GSp}_4$ that are tamely ramified with explicit genericity at places above $p$ as conjectured by Herzig--Tilouine and Gee--Herzig--Savitt. This improves on arXiv:2304.13879 where an inexplicit genericity hypothesis was required. As an application, we prove a modularity lifting theorem for $\mathrm{GSp}_4$ under similar assumptions.

The Recursive Panopticon Hypothesis
Xiaoyu Yan
https://arxiv.org/abs/2509.02625 https://arxiv.org/pdf/2509.02625 …

The Recursive Panopticon Hypothesis
The cosmic "Great Silence" revealed by the Fermi paradox remains a central puzzle in contemporary science. Existing explanations such as the "Big Filter," "Zoo Hypothesis," and "Dark Forest" theory are trapped in isolated frameworks of "hypothesis list paradigm" that resist falsification. This paper proposes the "Recursive Panopticon Hypothesis" arguing that under the uncertainty of recursive higher-order deterrence, cosmic civilizations will universally adopt "silence" as their optimal surviva…

Non-algebraicity of non-abundant foliations and abundance for adjoint foliated structures
Jihao Liu, Zheng Xu
https://arxiv.org/abs/2510.04419 https://arxi…

Non-algebraicity of non-abundant foliations and abundance for adjoint foliated structures
Assuming the abundance conjecture in dimension $d$, we establish a non-algebraicity criterion of foliations: any log canonical foliation of rank $\le d$ with $ν\neqκ$ is not algebraically integrable, answering question of Ambro--Cascini--Shokurov--Spicer. Under the same hypothesis, we prove abundance for klt algebraically integrable adjoint foliated structures of dimension $\le d$ and show the existence of good minimal models or Mori fiber spaces. In particular, when $d=3$, all these results …

Full Eigenstate Thermalization in Integrable Spin Systems
Tanay Pathak
https://arxiv.org/abs/2510.05887 https://arxiv.org/pdf/2510.05887

Full Eigenstate Thermalization in Integrable Spin Systems
The Eigenstate Thermalization Hypothesis(ETH) is a standard tool to understand the thermalization properties of an isolated quantum system. Its generalization to higher order correlations of matrix elements of local operators, dubbed the full ETH, predicts the decomposition of higher-order correlation function into thermal free cumulants. In this work, we numerically test these predictions of full ETH using exact diagonalization of two spin models: the Ising and the XXZ Heisenberg models. The d…

Diffusion Models and the Manifold Hypothesis: Log-Domain Smoothing is Geometry Adaptive
Tyler Farghly, Peter Potaptchik, Samuel Howard, George Deligiannidis, Jakiw Pidstrigach
https://arxiv.org/abs/2510.02305

Diffusion Models and the Manifold Hypothesis: Log-Domain Smoothing is Geometry Adaptive
Diffusion models have achieved state-of-the-art performance, demonstrating remarkable generalisation capabilities across diverse domains. However, the mechanisms underpinning these strong capabilities remain only partially understood. A leading conjecture, based on the manifold hypothesis, attributes this success to their ability to adapt to low-dimensional geometric structure within the data. This work provides evidence for this conjecture, focusing on how such phenomena could result from the …

Turbulence Closure in RANS and Flow Inference around a Cylinder using PINNs and Sparse Experimental Data
Z. Zhang, K. Shukla, Z. Wang, A. Morales, T. K\"aufer, S. Salauddin, N. Walters, D. Barrett, K. Ahmed, M. S. Triantafyllou, G. E. Karniadakis
https://arxiv.org/abs/2510.06049

Turbulence Closure in RANS and Flow Inference around a Cylinder using PINNs and Sparse Experimental Data
Traditional Reynolds-averaged Navier-Stokes (RANS) closures, based on the Boussinesq eddy viscosity hypothesis and calibrated on canonical flows, often yield inaccurate predictions of both mean flow and turbulence statistics. Here, we consider flow past a circular cylinder over a range of Reynolds numbers (3,900-100,000) and Mach numbers (0-0.3), encompassing incompressible and weakly compressible regimes, with the goal of improving predictions of mean velocity and Reynolds stresses. To this en…

Glassy interphases reinforce elastomeric nanocomposites by enhancing percolation-driven volume expansion under strain
Pierre Kawak, Harshad Bhapkar, David S. Simmons
https://arxiv.org/abs/2509.04755

Glassy interphases reinforce elastomeric nanocomposites by enhancing percolation-driven volume expansion under strain
For nearly a century, introduction of nanoparticles to elastomers has yielded extraordinarily tough nanocomposites that are critical to technologies from actuators to tires. The mechanisms by which this reinforcement occurs have nevertheless remained a central open question in material science. One widely debated hypothesis posits that strong interactions between polymer and particles induce "glassy bridges" that cement particles into a cohesive percolating network that resists elongation. Here…

On the Feinberg-Piunovskiy Theorem and its extension to chattering policies
Francois Dufour, Tomas Prieto-Rumeau
https://arxiv.org/abs/2510.04808 https://a…

On the Feinberg-Piunovskiy Theorem and its extension to chattering policies
The Feinberg-Piunovskiy Theorem established in [14, Theorem 3.8] asserts that for a discrete-time uniformly absorbing and atomless Markov Decision Process (MDP) with Borel state space and multiple criteria, the family of deterministic stationary policies is a sufficient class of policies. In this paper, we study some related problems and some extensions. In particular dropping the atomless hypothesis, we establish that the set of chattering stationary policies is a sufficient class of policies …

Flatness and Nonforking without the Continuum Hypothesis
Philani Rodney Majozi
https://arxiv.org/abs/2509.01785 https://arxiv.org/pdf/2509.01785

Flatness and Nonforking without the Continuum Hypothesis
We investigate the structure of FN bases (Frechet-Nikodym bases) without assuming the Continuum Hypothesis (CH), refining results of Siu-Ah Ng concerning definability via flatness and nonforking. In particular, we examine the dependence of Theorem 3.4 and Corollary 3.5 of Ng's 1991 paper on CH, which guarantees the existence of nonforking primary heirs under specific ultrafilter conditions. We demonstrate that these properties can often be recovered in ZFC by analyzing the behavior of countably…

On Cryptography and Distribution Verification, with Applications to Quantum Advantage
Bruno Cavalar, Eli Goldin, Matthew Gray, Taiga Hiroka, Tomoyuki Morimae
https://arxiv.org/abs/2510.05028

On Cryptography and Distribution Verification, with Applications to Quantum Advantage
One of the most fundamental problems in the field of hypothesis testing is the identity testing problem: whether samples from some unknown distribution $\mathcal{G}$ are actually from some explicit distribution $\mathcal{D}$. It is known that when the distribution $\mathcal{D}$ has support $[N]$, the optimal sample complexity for the identity testing problem is roughly $O(\sqrt{N})$. However, many distributions of interest, including those which can be sampled efficiently, have exponential supp…

Multi-field as a determinable
Davide Romano
https://arxiv.org/abs/2508.04933 https://arxiv.org/pdf/2508.04933

Multi-field as a determinable
The paper advances the hypothesis that the multi-field is a determinable, that is, a physical object characterized by indeterminate values with respect to some properties. The multi-field is a realist interpretation of the wave function in quantum mechanics, specifically it interprets the wave function as a new physical entity in 3D space: a multi-field (Hubert & Romano 2018; Romano 2021). The multi-field is similar to a field as it assigns determinate values to N-tuples of points, but is also …

Replaced article(s) found for math.GM. https://arxiv.org/list/math.GM/new
[1/1]:
- Towards a proof of the Riemann Hypothesis
Guilherme Rocha de Rezende
https://…

Innocence Project - URGENT: Stop the execution of Robert Roberson
https://innocenceproject.org/petitions/call-on-gov-abbott-to-stop-robert-robersons-execution/

Urge Gov. Abbott to Stop Robert Roberson’s Execution
Mr. Roberson would be first person in the U.S. executed based on the discredited shaken baby syndrome hypothesis. Act now.

Random #Gentoo ebuild hint: while you technically don't have to put Hypothesis in EPYTEST_PLUGINS (i.e. most of the packages will work without loading the plugin), moving it there ensures that the Gentoo profile is selected. This disables the health checks that can randomly break tests when they don't meet Hypothesis quality standards.
#pytest

Revisiting MFCCs: Evidence for Spectral-Prosodic Coupling
Vitor Magno de O. S. Bezerra, Gabriel F. A. Bastos, Jugurta Montalv\~ao
https://arxiv.org/abs/2510.05922 https://

Revisiting MFCCs: Evidence for Spectral-Prosodic Coupling
Mel-frequency cepstral coefficients (MFCCs) are an important feature in speech processing. A deeper understanding of their properties can contribute to the work that is being done with both classical and deep learning models. This study challenges the long-held assumption that MFCCs lack relevant temporal information by investigating their relationship with speech prosody. Using a null hypothesis significance testing framework, a systematic assessment is made about the statistical independence …

A new composite Mann-Whitney test for two-sample survival comparisons with right-censored data
Abid Hussain, Touqeer Ahmad
https://arxiv.org/abs/2510.05353 https://

A new composite Mann-Whitney test for two-sample survival comparisons with right-censored data
A fundamental challenge in comparing two survival distributions with right censored data is the selection of an appropriate nonparametric test, as the power of standard tests like the Log rank and Wilcoxon is highly dependent on the often unknown nature of the alternative hypothesis. This paper introduces a new, distribution free two sample test designed to overcome this limitation. The proposed method is based on a strategic decomposition of the data into uncensored and censored subsets, from …

#Aphantasia and the unconscious imagery hypothesis https://www.sciencedirect.com/science/article/pii/S1053810025001175 mental imagery

A universal compression theory: Lottery ticket hypothesis and superpolynomial scaling laws
Hong-Yi Wang, Di Luo, Tomaso Poggio, Isaac L. Chuang, Liu Ziyin
https://arxiv.org/abs/2510.00504

A universal compression theory: Lottery ticket hypothesis and superpolynomial scaling laws
When training large-scale models, the performance typically scales with the number of parameters and the dataset size according to a slow power law. A fundamental theoretical and practical question is whether comparable performance can be achieved with significantly smaller models and substantially less data. In this work, we provide a positive and constructive answer. We prove that a generic permutation-invariant function of $d$ objects can be asymptotically compressed into a function of $\ope…

An analysis of nuclear parton distribution function based on Kullback-Leibler divergence
Shu-Man Hu, Ao-Sheng Xiong, Ji Xu, Fu-Sheng Yu, Ji-Xin Yu
https://arxiv.org/abs/2508.05171

An analysis of nuclear parton distribution function based on Kullback-Leibler divergence
In this work, we present an attempt to quantify the difference between nuclear parton distribution functions (nPDFs) in different nuclei and parton distribution functions (PDFs) in free nucleons using the Kullback-Leibler (KL) divergence, a measure widely employed in quantum information theory. By introducing certain constraints and the ``minimum relative entropy'' hypothesis, we can determine the shape of the structure function in the intermediate-$x$ region, which is intimately connected with…

Exact Quench Dynamics from Thermal Pure Quantum States
Hui-Huang Chen
https://arxiv.org/abs/2510.05346 https://arxiv.org/pdf/2510.05346

Exact Quench Dynamics from Thermal Pure Quantum States
We present an exact solution for a quantum quench in an integrable system that reveals a new, coherent pathway to thermalization. In chaotic systems, thermalization is understood via the eigenstate thermalization hypothesis (ETH), which implies that a quench from a thermal pure quantum (TPQ) state should exhibit trivial dynamics. In contrast, integrable systems are expected to retain memory of their initial conditions in a non-thermal generalized Gibbs ensemble (GGE). We show that a quench from…

Comprehensive Analysis and Exclusion Hypothesis of $\alpha$-Approximation Method for Discretizing Analog Systems
Shen Chen, Jisong Wang, Dejun Liu, Jiaxi Ying, Shuai Wang
https://arxiv.org/abs/2509.02054

Comprehensive Analysis and Exclusion Hypothesis of $α$-Approximation Method for Discretizing Analog Systems
A popular method for designing digital models is transforming the transfer function of the corresponding analog models from continuous domain (s-domain) into discrete domain (z-domain) using the s-to-z transformation. The alpha-approximation is a generalized form of these transformations. When alpha is set to 0.5, the result is the well-known Tustin transformation or bi-linear transformation. In this paper, we provided a comprehensive analysis of the alpha-approximation method, including mathem…

Superposition disentanglement of neural representations reveals hidden alignment
Andr\'e Longon, David Klindt, Meenakshi Khosla
https://arxiv.org/abs/2510.03186 https://

Superposition disentanglement of neural representations reveals hidden alignment
The superposition hypothesis states that a single neuron within a population may participate in the representation of multiple features in order for the population to represent more features than the number of neurons. In neuroscience and AI, representational alignment metrics measure the extent to which different deep neural networks (DNNs) or brains represent similar information. In this work, we explore a critical question: \textit{does superposition interact with alignment metrics in any un…

Asymptotic distributions of four linear hypotheses test statistics under generalized spiked model
Zhijun Liu, Jiang Hu, Zhidong Bai, Zhihui Lv
https://arxiv.org/abs/2510.04185 h…

Asymptotic distributions of four linear hypotheses test statistics under generalized spiked model
In this paper, we establish the Central Limit Theorem (CLT) for linear spectral statistics (LSSs) of large-dimensional generalized spiked sample covariance matrices, where the spiked eigenvalues may be either bounded or diverge to infinity. Building upon this theorem, we derive the asymptotic distributions of linear hypothesis test statistics under the generalized spiked model, including Wilks' likelihood ratio test statistic U, the Lawley-Hotelling trace test statistic W, and the Bartlett-Nand…

On Unconditionality and Higher-Order Schreier Unconditionality
Mark Shiliaev
https://arxiv.org/abs/2510.02783 https://arxiv.org/pdf/2510.02783

On Unconditionality and Higher-Order Schreier Unconditionality
Let $X$ be a Banach space, $(e_n)_{n=1}^\infty$ be its basis, and $S_α$ be a Schreier family of order alpha. We introduce Condition A which is a weaker version of the Continuum Hypothesis. Granted Condition A, we show that if the basis $(e_n)$ is $S_α$-unconditional for every countable ordinal alpha, then it is unconditional.

Elastic Energy Storage Mechanism in Hovering Animal Flight: A Discriminative Method Based on Wing Kinematics
Shijie Sheng, Jianghao Wu, Renxuan Bo, Long Chen, Yanlai Zhang
https://arxiv.org/abs/2510.02819

Elastic Energy Storage Mechanism in Hovering Animal Flight: A Discriminative Method Based on Wing Kinematics
Existing research has yet to reach a consensus on whether and how small flying animals utilize elastic energy storage mechanisms to reduce flight energy expenditure, and there is a lack of systematic and universal methods for assessment. To address these gaps, this study proposes a method to evaluate elastic energy storage capacity based on wing kinematic parameters (flapping amplitude and flapping frequency), grounded in the hypothesis that animals tend to minimize flight energy expenditure. B…

When correcting for regression to the mean is worse than no correction at all
Jos\'e F. Fontanari, Mauro Santos
https://arxiv.org/abs/2509.04718 https://

When correcting for regression to the mean is worse than no correction at all
The ubiquitous regression to the mean (RTM) effect complicates statistical inference in biological studies of change. We demonstrate that common RTM correction methods are flawed: the Berry et al. method popularized by Kelly & Price in The American Naturalist is unreliable for hypothesis testing, leading to both false positives and negatives, while the theoretically unbiased Blomqvist method has poor efficiency in limited sample sizes. Our findings show that the most robust approach to handling…

Shape Happens: Automatic Feature Manifold Discovery in LLMs via Supervised Multi-Dimensional Scaling
Federico Tiblias, Irina Bigoulaeva, Jingcheng Niu, Simone Balloccu, Iryna Gurevych
https://arxiv.org/abs/2510.01025

Shape Happens: Automatic Feature Manifold Discovery in LLMs via Supervised Multi-Dimensional Scaling
The linear representation hypothesis states that language models (LMs) encode concepts as directions in their latent space, forming organized, multidimensional manifolds. Prior efforts focus on discovering specific geometries for specific features, and thus lack generalization. We introduce Supervised Multi-Dimensional Scaling (SMDS), a model-agnostic method to automatically discover feature manifolds. We apply SMDS to temporal reasoning as a case study, finding that different features form var…

First moment of quadratic Dirichlet $L$-functions with secondary terms
Martin \v{C}ech
https://arxiv.org/abs/2509.03197 https://arxiv.org/pdf/2509.03197

First moment of quadratic Dirichlet $L$-functions with secondary terms
We study the first moment of primitive quadratic Dirichlet $L$-functions. Assuming the Riemann hypothesis and the generalized Lindelöf hypothesis, we obtain an asymptotic formula at the central point with error $O(X^{1/4+ε})$, and identify lower-order terms of size $X^{1/3}\log X$.

An account of the arrow of time when scale is surplus
Sean Gryb, Simon Friederich
https://arxiv.org/abs/2510.03041 https://arxiv.org/pdf/2510.03041

An account of the arrow of time when scale is surplus
Existing accounts of the cosmological arrow of time face a dilemma: generalist approaches that posit time-asymmetric laws lack independent motivation, while particularist approaches that invoke a Past Hypothesis face serious conceptual and explanatory problems. We propose a novel account that dispenses with the need for both time-asymmetric laws and a Past Hypothesis. Instead, it is centred around a symmetry argument that reveals attractors and so-called 'Janus points'. The main idea is that th…

Mechanisms of Matter: Language Inferential Benchmark on Physicochemical Hypothesis in Materials Synthesis
Yingming Pu, Tao Lin, Hongyu Chen
https://arxiv.org/abs/2509.25281 http…

Mechanisms of Matter: Language Inferential Benchmark on Physicochemical Hypothesis in Materials Synthesis
The capacity of Large Language Models (LLMs) to generate valid scientific hypotheses for materials synthesis remains largely unquantified, hindered by the absence of benchmarks probing physicochemical logics reasoning. To address this, we introduce MatterMech, a benchmark for evaluating LLM-generated hypotheses across eight nanomaterial synthesis domains. Our analysis reveals a critical disconnect: LLMs are proficient in abstract logic yet fail to ground their reasoning in fundamental physicoch…

Podpowiedź do ebuildów #Gentoo: technicznie rzecz biorąc, nie trzeba ładować hypothesis w EPYTEST_PLUGINS (w sensie, że większość paczek będzie po prostu działać bez ładowania wtyczki) — ale warto to zrobić, bo dzięki temu jest ładowany profil Gentoo. Wówczas wyłączane są "health checks", które mogą doprowadzić do przypadkowo padających testów, które nie spełniają wymagań jakości.

WoW: Towards a World omniscient World model Through Embodied Interaction
Xiaowei Chi, Peidong Jia, Chun-Kai Fan, Xiaozhu Ju, Weishi Mi, Kevin Zhang, Zhiyuan Qin, Wanxin Tian, Kuangzhi Ge, Hao Li, Zezhong Qian, Anthony Chen, Qiang Zhou, Yueru Jia, Jiaming Liu, Yong Dai, Qingpo Wuwu, Chengyu Bai, Yu-Kai Wang, Ying Li, Lizhang Chen, Yong Bao, Zhiyuan Jiang, Jiacheng Zhu, Kai Tang, Ruichuan An, Yulin Luo, Qiuxuan Feng, Siyuan Zhou, Chi-min Chan, Chengkai Hou, Wei Xue, Sirui Han, Yike Guo, …

WoW: Towards a World omniscient World model Through Embodied Interaction
Humans develop an understanding of intuitive physics through active interaction with the world. This approach is in stark contrast to current video models, such as Sora, which rely on passive observation and therefore struggle with grasping physical causality. This observation leads to our central hypothesis: authentic physical intuition of the world model must be grounded in extensive, causally rich interactions with the real world. To test this hypothesis, we present WoW, a 14-billion-paramet…

The Narcissus Hypothesis:Descending to the Rung of Illusion
Riccardo Cadei, Christian Intern\`o
https://arxiv.org/abs/2509.17999 https://arxiv.org/pdf/2509…

The Narcissus Hypothesis:Descending to the Rung of Illusion
Modern foundational models increasingly reflect not just world knowledge, but patterns of human preference embedded in their training data. We hypothesize that recursive alignment-via human feedback and model-generated corpora-induces a social desirability bias, nudging models to favor agreeable or flattering responses over objective reasoning. We refer to it as the Narcissus Hypothesis and test it across 31 models using standardized personality assessments and a novel Social Desirability Bias …

Analysis of Semantic Communication for Logic-based Hypothesis Deduction
Ahmet Faruk Saz, Siheng Xiong, Faramarz Fekri
https://arxiv.org/abs/2508.21755 https://

Analysis of Semantic Communication for Logic-based Hypothesis Deduction
This work presents an analysis of semantic communication in the context of First-Order Logic (FOL)-based deduction. Specifically, the receiver holds a set of hypotheses about the State of the World (SotW), while the transmitter has incomplete evidence about the true SotW but lacks access to the ground truth. The transmitter aims to communicate limited information to help the receiver identify the hypothesis most consistent with true SotW. We formulate the objective as approximating the posterio…

VulAgent: Hypothesis-Validation based Multi-Agent Vulnerability Detection
Ziliang Wang, Ge Li, Jia Li, Hao Zhu, Zhi Jin
https://arxiv.org/abs/2509.11523 https://

VulAgent: Hypothesis-Validation based Multi-Agent Vulnerability Detection
The application of language models to project-level vulnerability detection remains challenging, owing to the dual requirement of accurately localizing security-sensitive code and correctly correlating and reasoning over complex program context. We present VulAgent, a multi-agent vulnerability detection framework based on hypothesis validation. Our design is inspired by how human auditors review code: when noticing a sensitive operation, they form a hypothesis about a possible vulnerability, co…

Double-faced white dwarfs and the magnetic inhibition of convection
Sivan Ginzburg
https://arxiv.org/abs/2509.02671 https://arxiv.org/pdf/2509.02671…

Double-faced white dwarfs and the magnetic inhibition of convection
About one in five white dwarfs undergoes spectral evolution from a helium atmosphere to hydrogen and then back to helium. These short-lived hydrogen envelopes - the result of residual hydrogen diffusion - are eventually destroyed by either hydrogen or helium convection. An emerging class of double-faced white dwarfs seems to catch this process in the act, with varying amounts of hydrogen across regions of the stellar surface. Here, we quantitatively test the hypothesis that these inhomogeneitie…

Eigenstate thermalization hypothesis versus Bohigas-Giannoni-Schmit conjecture: a comparison
Hans A. Weidenm\"uller
https://arxiv.org/abs/2509.17634 https://

Eigenstate thermalization hypothesis versus Bohigas-Giannoni-Schmit conjecture: a comparison
Thermalization of a closed chaotic quantum system is commonly addressed in terms of the eigenstate ther- malization hypothesis (ETH). An alternative approach uses the Bohigas-Giannoni-Schmit (BGS) conjecture. The comparison shows that the two approaches differ significantly. In contrast to ETH, BGS fully uses the statistical properies of the chaotic Hamiltonian. In both approaches, the criterion for thermalization is similar. BGS goes beyond ETH in predicting quantitatively the time dependence …

Statistical inference using debiased group graphical lasso for multiple sparse precision matrices
Sayan Ranjan Bhowal, Debashis Paul, Gopal K Basak, Samarjit Das
https://arxiv.org/abs/2510.04683

Statistical inference using debiased group graphical lasso for multiple sparse precision matrices
Debiasing group graphical lasso estimates enables statistical inference when multiple Gaussian graphical models share a common sparsity pattern. We analyze the estimation properties of group graphical lasso, establishing convergence rates and model selection consistency under irrepresentability conditions. Based on these results, we construct debiased estimators that are asymptotically Gaussian, allowing hypothesis testing for linear combinations of precision matrix entries across populations. …

ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression
Tom Burgert, Oliver Stoll, Paolo Rota, Beg\"um Demir
https://arxiv.org/abs/2509.20234

ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression
The hypothesis that Convolutional Neural Networks (CNNs) are inherently texture-biased has shaped much of the discourse on feature use in deep learning. We revisit this hypothesis by examining limitations in the cue-conflict experiment by Geirhos et al. To address these limitations, we propose a domain-agnostic framework that quantifies feature reliance through systematic suppression of shape, texture, and color cues, avoiding the confounds of forced-choice conflicts. By evaluating humans and n…

Observational Tests of Terrestrial Planet Buffering Feedbacks and the Habitable Zone Concept
Morgan Underwood, Adrian Lenardic, Johnny Seales, Benjamin Kwait-Gonchar
https://arxiv.org/abs/2509.02848

Observational Tests of Terrestrial Planet Buffering Feedbacks and the Habitable Zone Concept
The habitable zone is defined as the orbital region around a star where planetary feedback cycles buffer atmospheric greenhouse gases that, in combination with solar luminosity, maintain surface temperatures suitable for liquid water. Evidence supports the existence of buffering feedbacks on Earth, but whether these same feedbacks are active on other Earth-like planets remains untested, as does the habitable zone hypothesis. While feedbacks are central to the habitable zone concept, one does no…

Quantum Sequential Universal Hypothesis Testing
Matteo Zecchin, Osvaldo Simeone, Aaditya Ramdas
https://arxiv.org/abs/2508.21594 https://arxiv.org/pdf/2508…

Quantum Sequential Universal Hypothesis Testing
Quantum hypothesis testing (QHT) concerns the statistical inference of unknown quantum states. In the general setting of composite hypotheses, the goal of QHT is to determine whether an unknown quantum state belongs to one or another of two classes of states based on the measurement of a number of copies of the state. Prior art on QHT with composite hypotheses focused on a fixed-copy two-step protocol, with state estimation followed by an optimized joint measurement. However, this fixed-copy ap…

Optimizing Geometry Problem Sets for Skill Development
Michael Bouzinier, Sergey Trifonov
https://arxiv.org/abs/2509.02758 https://arxiv.org/pdf/2509.02758…

Optimizing Geometry Problem Sets for Skill Development
This article describes an ontology and methodology for annotating and organizing Euclidean Geometry problems, developed in the early 1990s and implemented as a software tool. While the majority of this work -- including the ontology and solution graph paradigm -- was completed over thirty years ago, we argue that it has renewed relevance in the context of modern artificial intelligence. In particular, we explore the hypothesis that this established framework can facilitate automated solution va…

"Low Frequency Tweeters Have More to Say!" A New Approach to Identify Importance of Tweets
Gautam Khannaa, Yeliz Yesilada, Sukru Eraslan, Simon Harper
https://arxiv.org/abs/2509.03931

"Low Frequency Tweeters Have More to Say!" A New Approach to Identify Importance of Tweets
Twitter is one of the most popular social media platforms.With a large number of tweets, the activity feed of users becomes noisy, challenging to read, and most importantly tweets often get lost. We present a new approach to personalise the ranking of the tweets toward solving the problem of information overload which is achieved by analysing the relationship between the importance of tweets to the frequency at which the author tweets. The hypothesis tested is that "low-frequency tweeters have …

The density Hypothesis for irreducible lattices in $\mathrm{PSL}_2(\mathbb{R})^d$
Dubi Kelmer
https://arxiv.org/abs/2509.22595 https://arxiv.org/pdf/2509.2…

The density Hypothesis for irreducible lattices in $\mathrm{PSL}_2(\mathbb{R})^d$
We prove the density hypothesis for congruence subgroups of an irreducible uniform lattice in $\mathrm{PSL}_2(\mathbb{R})^d$, extending previous results on the spherical density hypothesis to bound multiplicities of non-tempered non-spherical representations. Our bounds are uniform in the level as well as the spectral parameters.

Off Critical Zeros Contradict Contraction in the Dynamical Reformulation of the Riemann Hypothesis
Hendrik Wladimir Albrecht Edwin Kuipers
https://arxiv.org/abs/2509.16240 https…

Off Critical Zeros Contradict Contraction in the Dynamical Reformulation of the Riemann Hypothesis
We continue the dynamical reformulation of the Riemann Hypothesis initiated in [1]. The framework is built from an integer map in which composites advance by pi(m) and primes retreat by their prime gap, producing trajectories whose contraction properties encode the distribution of primes. In this setting, RH is equivalent to the persistence of contraction inequalities for trajectory-based error functionals E(X), E~(X) across multiplicative scales. In the present paper we prove that if zeta(s)…

And more to read in your freetime, if you are interested in AI, from Bluesky, Phillip Isola.
"Over the past year, my lab has been working on fleshing out theory applications of the Platonic Representation Hypothesis.
Today I want to share two new works on this topic:"
Eliciting higher alignment:
https://arxiv.org/…

Words That Make Language Models Perceive
Large language models (LLMs) trained purely on text ostensibly lack any direct perceptual experience, yet their internal representations are implicitly shaped by multimodal regularities encoded in language. We test the hypothesis that explicit sensory prompting can surface this latent structure, bringing a text-only LLM into closer representational alignment with specialist vision and audio encoders. When a sensory prompt tells the model to 'see' or 'hear', it cues the model to resolve its next…

When Scores Learn Geometry: Rate Separations under the Manifold Hypothesis
Xiang Li, Zebang Shen, Ya-Ping Hsieh, Niao He
https://arxiv.org/abs/2509.24912 https://

When Scores Learn Geometry: Rate Separations under the Manifold Hypothesis
Score-based methods, such as diffusion models and Bayesian inverse problems, are often interpreted as learning the data distribution in the low-noise limit ($σ\to 0$). In this work, we propose an alternative perspective: their success arises from implicitly learning the data manifold rather than the full distribution. Our claim is based on a novel analysis of scores in the small-$σ$ regime that reveals a sharp separation of scales: information about the data manifold is $Θ(σ^{-2})$ stronger…

Reflexive Modules, the Infinite Root Algebra and the Generating Hypothesis
Oliver House
https://arxiv.org/abs/2508.07116 https://arxiv.org/pdf/2508.07116…

Reflexive Modules, the Infinite Root Algebra and the Generating Hypothesis
This thesis concerns the algebraic consequences of Freyd's Generating Hypothesis, and explores the question of whether there exists a self-injective ring R that can be constructed purely algebraically that exhibits some of the known properties of the stable homotopy ring, including some conjectured properties that follow from Freyd's Generating Hypothesis. As an example, we investigate the infinite root algebra of Hahn series P, firstly by establishing results for the related Hahn ring A. In pa…

On the hypothesis of a bi-isotropic plasma permeating the interstellar space
Filipe S. Ribeiro, Pedro D. S. Silva, Rodolfo Casana, Manoel M. Ferreira Jr
https://arxiv.org/abs/2508.15879

On the hypothesis of a bi-isotropic plasma permeating the interstellar space
In this work, we study the propagation of electromagnetic waves in a magnetized chiral plasma that pervades the interstellar space. The Maxwell equations, supplemented by bi-isotropic constitutive relations, are rewritten to describe a cold, uniform, and collisionless plasma model that yields new collective electromagnetic modes for distinct pairs of refractive indices associated with right- and left-handed circularly polarized waves. We have investigated the optical behavior through the rotato…

MH-LVC: Multi-Hypothesis Temporal Prediction for Learned Conditional Residual Video Coding
Huu-Tai Phung, Zong-Lin Gao, Yi-Chen Yao, Kuan-Wei Ho, Yi-Hsin Chen, Yu-Hsiang Lin, Alessandro Gnutti, Wen-Hsiao Peng
https://arxiv.org/abs/2510.12479

MH-LVC: Multi-Hypothesis Temporal Prediction for Learned Conditional Residual Video Coding
This work, termed MH-LVC, presents a multi-hypothesis temporal prediction scheme that employs long- and short-term reference frames in a conditional residual video coding framework. Recent temporal context mining approaches to conditional video coding offer superior coding performance. However, the need to store and access a large amount of implicit contextual information extracted from past decoded frames in decoding a video frame poses a challenge due to excessive memory access. Our MH-LVC ov…

Rewarding Explainability in Drug Repurposing with Knowledge Graphs
Susana Nunes, Samy Badreddine, Catia Pesquita
https://arxiv.org/abs/2509.02276 https://a…

Rewarding Explainability in Drug Repurposing with Knowledge Graphs
Knowledge graphs (KGs) are powerful tools for modelling complex, multi-relational data and supporting hypothesis generation, particularly in applications like drug repurposing. However, for predictive methods to gain acceptance as credible scientific tools, they must ensure not only accuracy but also the capacity to offer meaningful scientific explanations. This paper presents a novel approach REx, for generating scientific explanations based in link prediction in knowledge graphs. It employs r…

HEAL: A Hypothesis-Based Preference-Aware Analysis Framework
Yifu Huo, Chenglong Wang, Qiren Zhu, Shunjie Xing, Tong Xiao, Chunliang Zhang, Tongran Liu, Jinbo Zhu
https://arxiv.org/abs/2508.19922

HEAL: A Hypothesis-Based Preference-Aware Analysis Framework
Preference optimization methods like DPO have achieved remarkable performance in LLM alignment. However, the evaluation for these methods relies on a single response and overlooks other potential outputs, which could also be generated in real-world applications within this hypothetical space. To address this issue, this paper presents a \textbf{H}ypothesis-based Pr\textbf{E}ference-aware \textbf{A}na\textbf{L}ysis Framework (HEAL), a novel evaluation paradigm that formulates preference alignmen…

A solution to the mystery of the sub-harmonic series and to the combination tone via a linear mathematical model of the cochlea
Ugo Boscain (SU, CNRS, CaGE, LJLL), Xiangyu Ma (SU, CNRS, CaGE, LJLL), Dario Prandi (L2S, CNRS), Giuseppina Turco (LLF - UMR7110, CNRS, UPCit\'e)
https://arxiv.org/abs/2509.26395…

A solution to the mystery of the sub-harmonic series and to the combination tone via a linear mathematical model of the cochlea
In this paper, we study a simple linear model of the cochlea as a set of vibrating strings. We make hypothesis that the information sent to the auditory cortex is the energy stored in the strings and consider all oscillation modes of the strings. We show the emergence of the sub-harmonic series whose existence was hypothesized in the XVI century to explain the consonance of the minor chord. We additionally show how the nonlinearity of the energy can be used to study the emergence of the combina…

Some series equivalent to the extended Riemann hypothesis for Dedekind zeta functions
Vincent Nguyen
https://arxiv.org/abs/2509.21518 https://arxiv.org/pdf…

Some series equivalent to the extended Riemann hypothesis for Dedekind zeta functions
The extended Riemann hypothesis (ERH) for Dedekind zeta functions remains one of the most elusive open problems in number theory. Over the last century, many equivalent statements to the classical Riemann hypothesis alone have been discovered. We seek to show that the closed form of some infinite series over the non-trivial zeros of Dedekind zeta functions is equivalent to ERH.

An operator-Weyl-symbol approach to eigenstate thermalization hypothesis
Xiao Wang, Wen-ge Wang
https://arxiv.org/abs/2509.24490 https://arxiv.org/pdf/2509…

An operator-Weyl-symbol approach to eigenstate thermalization hypothesis
In this letter, by an approach that employs Weyl symbols for operators, a semiclassical theory is developed for the offdiagonal function in the eigenstate thermalization hypothesis, which is for offdiagonal elements $\langle{E_i}\left|O\right|{E_j}\rangle$ of an observable $O$ on the energy basis. It is shown analytically that the matrix of $O$ has a banded structure, possessing a bandwidth $w_b$ that scales linearly with $\hbar$, a phase-space gradient of the classical Hamiltonian, $…

Confirmatory Adaptive Hypothesis Tests in Markovian Illness-Death Models
Rene Schmidt, Moritz Fabian Danzer
https://arxiv.org/abs/2509.02315 https://arxiv.…

Confirmatory Adaptive Hypothesis Tests in Markovian Illness-Death Models
Classic adaptive designs for time-to-event trials are based on the log-rank statistic and its increments. Thereby, only information from the time-to-event endpoint on which the selected log-rank statistic is based may be used for data-dependent design modifications in interim analyses. Further information (e.g. surrogate parameters) may not be used. As pointed out in a letter by P. Bauer and M. Posch in 2004, adaptive tests on overall survival (OS) based on the log-rank statistic do in general …

Making Characters Count. A Computational Approach to Scribal Profiling in 14th-Century Middle Dutch Manuscripts from the Carthusian Monastery of Herne
Caroline Vandyck, Wouter Haverals, Mike Kestemont
https://arxiv.org/abs/2509.00067

Making Characters Count. A Computational Approach to Scribal Profiling in 14th-Century Middle Dutch Manuscripts from the Carthusian Monastery of Herne
The Carthusian monastery of Herne was exceptionally prolific in producing high-quality manuscripts during the late 14th century. Although the scribes remain anonymous, previous research has distinguished thirteen different scribal hands based on paleography and codicology. In this study, we revisit this hypothesis through the lens of linguistic characteristics of the texts, using computational methods from the field of scribal profiling. Using a newly created corpus of diplomatic and HTR-based …

Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph
Gautam Kamath, Alireza F. Pour, Matthew Regehr, David P. Woodruff
https://arxiv.org/abs/2509.16180 htt…

Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph
We propose an algorithm with improved query-complexity for the problem of hypothesis selection under local differential privacy constraints. Given a set of $k$ probability distributions $Q$, we describe an algorithm that satisfies local differential privacy, performs $\tilde{O}(k^{3/2})$ non-adaptive queries to individuals who each have samples from a probability distribution $p$, and outputs a probability distribution from the set $Q$ which is nearly the closest to $p$. Previous algorithms req…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[5/7]:
- Superficial Safety Alignment Hypothesis
Jianwei Li, Jung-Eun Kim
https://

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[1/4]:
- Superficial Safety Alignment Hypothesis
Jianwei Li, Jung-Eun Kim
https://

Shape Happens: Automatic Feature Manifold Discovery in LLMs via Supervised Multi-Dimensional Scaling
Federico Tiblias, Irina Bigoulaeva, Jingcheng Niu, Simone Balloccu, Iryna Gurevych
https://arxiv.org/abs/2510.01025

Shape Happens: Automatic Feature Manifold Discovery in LLMs via Supervised Multi-Dimensional Scaling
The linear representation hypothesis states that language models (LMs) encode concepts as directions in their latent space, forming organized, multidimensional manifolds. Prior efforts focus on discovering specific geometries for specific features, and thus lack generalization. We introduce Supervised Multi-Dimensional Scaling (SMDS), a model-agnostic method to automatically discover feature manifolds. We apply SMDS to temporal reasoning as a case study, finding that different features form var…

A Conditional Reduction of the Rational Hodge Conjecture for Threefolds and Deformation-Theoretic Verifications in Several Families
Karim Mansour
https://arxiv.org/abs/2508.08321

A Conditional Reduction of the Rational Hodge Conjecture for Threefolds and Deformation-Theoretic Verifications in Several Families
We formulate a concrete geometric approximation hypothesis (Hypothesis~BB) asserting that codimension-$2$ Hodge classes on a smooth projective threefold can be realized as specializations of families whose general members are complete-intersection curves. We prove that Hypothesis~BB implies the (rational) Hodge conjecture for the threefold. We then give deformation-theoretic sufficient criteria (cohomology-vanishing and surjectivity conditions) which imply Hypothesis~BB, and we prove these crit…

Variational Uncertainty Decomposition for In-Context Learning
I. Shavindra Jayasekera, Jacob Si, Wenlong Chen, Filippo Valdettaro, A. Aldo Faisal, Yingzhen Li
https://arxiv.org/abs/2509.02327

Variational Uncertainty Decomposition for In-Context Learning
As large language models (LLMs) gain popularity in conducting prediction tasks in-context, understanding the sources of uncertainty in in-context learning becomes essential to ensuring reliability. The recent hypothesis of in-context learning performing predictive Bayesian inference opens the avenue for Bayesian uncertainty estimation, particularly for decomposing uncertainty into epistemic uncertainty due to lack of in-context data and aleatoric uncertainty inherent in the in-context predictio…

Infinite temperature at zero energy
Matteo Ippoliti, David M. Long
https://arxiv.org/abs/2509.04410 https://arxiv.org/pdf/2509.04410

Infinite temperature at zero energy
We construct a family of static, geometrically local Hamiltonians that inherit eigenstate properties of periodically-driven (Floquet) systems. Our construction is a variation of the Feynman-Kitaev clock -- a well-known mapping between quantum circuits and local Hamiltonians -- where the clock register is given periodic boundary conditions. Assuming the eigenstate thermalization hypothesis (ETH) holds for the input circuit, our construction yields Hamiltonians whose eigenstates have properties c…

A Theoretical Framework of the Processes of Change in Psychotherapy Delivered by Artificial Agents
Arthur Bran Herbener, Malene Flensborg Damholdt
https://arxiv.org/abs/2509.02144

A Theoretical Framework of the Processes of Change in Psychotherapy Delivered by Artificial Agents
The question of whether artificial agents (e.g., chatbots and social robots) can replace human therapists has received notable attention following the recent launch of large language models. However, little is known about the processes of change in psychotherapy delivered by artificial agents. To facilitate hypothesis development and stimulate scientific debate, the present article offers the first theoretical framework of the processes of change in psychotherapy delivered by artificial agents.…

Practically significant change points in high dimension -- measuring signal strength pro active component
Pascal Quanz, Holger Dette
https://arxiv.org/abs/2508.21520 https://

Practically significant change points in high dimension -- measuring signal strength pro active component
We consider the change point testing problem for high-dimensional time series. Unlike conventional approaches, where one tests whether the difference $δ$ of the mean vectors before and after the change point is equal to zero, we argue that the consideration of the null hypothesis $H_0:\|δ\|\leΔ$, for some norm $\|\cdot\|$ and a threshold $Δ>0$, is better suited. By the formulation of the null hypothesis as a composite hypothesis, the change point testing problem becomes …

Testing the heavy decaying sterile neutrino hypothesis at the DUNE near detector
Sabya Sachi Chatterjee, St\'ephane Lavignac, O. G. Miranda
https://arxiv.org/abs/2508.15888 …

Testing the heavy decaying sterile neutrino hypothesis at the DUNE near detector
One of the most convincing explanations of the LSND and MiniBooNE anomalies relies on a heavy, mostly sterile neutrino with a small muon neutrino component, which decays to an electron neutrino and an invisible light scalar field. We investigate the possibility to test this hypothesis at the near detector complex of the upcoming DUNE experiment. We find that the DUNE liquid argon near detector (ND-LAr) can probe a larger region of the parameter space than the Fermilab SBN program, and may help …

Learning-Based Testing for Deep Learning: Enhancing Model Robustness with Adversarial Input Prioritization
Sheikh Md Mushfiqur Rahman, Nasir Eisty
https://arxiv.org/abs/2509.23961

Learning-Based Testing for Deep Learning: Enhancing Model Robustness with Adversarial Input Prioritization
Context: Deep Neural Networks (DNNs) are increasingly deployed in critical applications, where resilience against adversarial inputs is paramount. However, whether coverage-based or confidence-based, existing test prioritization methods often fail to efficiently identify the most fault-revealing inputs, limiting their practical effectiveness. Aims: This project aims to enhance fault detection and model robustness in DNNs by integrating Learning-Based Testing (LBT) with hypothesis and mutation t…

Active Sequential Hypothesis Testing with Non-Homogeneous Costs
George Vershinin, Asaf Cohen, Omer Gurewitz
https://arxiv.org/abs/2509.11632 https://arxiv.…

Active Sequential Hypothesis Testing with Non-Homogeneous Costs
We study the Non-Homogeneous Sequential Hypothesis Testing (NHSHT), where a single active Decision-Maker (DM) selects actions with heterogeneous positive costs to identify the true hypothesis under an average error constraint \(δ\), while minimizing expected total cost paid. Under standard arguments, we show that the objective decomposes into the product of the mean number of samples and the mean per-action cost induced by the policy. This leads to a key design principle: one should optimize t…

Detecting zeros of Dirichlet $L$-functions via the Riemann zeta-function
Masatoshi Suzuki
https://arxiv.org/abs/2508.17701 https://arxiv.org/pdf/2508.17701…

Detecting zeros of Dirichlet $L$-functions via the Riemann zeta-function
Assuming the Riemann hypothesis, we show that a certain vertical distribution of the nontrivial zeros of the Riemann zeta-function is equivalent to the generalized Riemann hypothesis for Dirichlet $L$-functions. Furthermore, under both the Riemann hypothesis and the generalized Riemann hypothesis, we show that the nontrivial zeros of Dirichlet $L$-functions can be detected through those of the Riemann zeta-function.

Generative Model Inversion Through the Lens of the Manifold Hypothesis
Xiong Peng, Bo Han, Fengfei Yu, Tongliang Liu, Feng Liu, Mingyuan Zhou
https://arxiv.org/abs/2509.20177 ht…

Generative Model Inversion Through the Lens of the Manifold Hypothesis
Model inversion attacks (MIAs) aim to reconstruct class-representative samples from trained models. Recent generative MIAs utilize generative adversarial networks to learn image priors that guide the inversion process, yielding reconstructions with high visual quality and strong fidelity to the private training data. To explore the reason behind their effectiveness, we begin by examining the gradients of inversion loss with respect to synthetic inputs, and find that these gradients are surprisi…

An application of Titchmarsh's theorem and the Salem equivalence
Alexander E. Patkowski
https://arxiv.org/abs/2508.21789 https://arxiv.org/pdf/2508.217…

An application of Titchmarsh's theorem and the Salem equivalence
We extend the equivalence of the Salem type for the Riemann hypothesis by application of Titchmarsh's theorem. Other equivalences to the Riemann hypothesis and notes on related Fourier integrals are provided.

Feedback-Enhanced Online Multiple Testing with Applications to Conformal Selection
Lin Lu, Yuyang Huo, Haojie Ren, Zhaojun Wang, Changliang Zou
https://arxiv.org/abs/2509.03297 …

Feedback-Enhanced Online Multiple Testing with Applications to Conformal Selection
We study online multiple testing with feedback, where decisions are made sequentially and the true state of the hypothesis is revealed after the decision has been made, either instantly or with a delay. We propose GAIF, a feedback-enhanced generalized alpha-investing framework that dynamically adjusts thresholds using revealed outcomes, ensuring finite-sample false discovery rate (FDR)/marginal FDR control. Extending GAIF to online conformal testing, we construct independent conformal $p$-value…

Quantum mechanics, non-locality, and the space discreteness hypothesis
W. A. Z\'u\~niga-Galindo
https://arxiv.org/abs/2508.14836 https://arxiv.org/pdf/…

Quantum mechanics, non-locality, and the space discreteness hypothesis
The space discreteness hypothesis asserts that the nature of space at short distances is radically different from that at large distances. Based on the Bronstein inequality, here, we use a totally disconnected topological space $\mathcal{X}$ as a model for the space. However, we consider the time as a real variable. In this framework, the formalism of Dirac-von Neumann can be used. This discreteness hypothesis implies that given two different points in space, there is no continuous curve (a wor…

AgentPack: A Dataset of Code Changes, Co-Authored by Agents and Humans
Yangtian Zi, Zixuan Wu, Aleksander Boruch-Gruszecki, Jonathan Bell, Arjun Guha
https://arxiv.org/abs/2509.21891

AgentPack: A Dataset of Code Changes, Co-Authored by Agents and Humans
Fine-tuning large language models for code editing has typically relied on mining commits and pull requests. The working hypothesis has been that commit messages describe human intent in natural language, and patches to code describe the changes that implement that intent. However, much of the previously collected data is noisy: commit messages are terse, human-written commits commingle several unrelated edits, and many commits come from simple, rule-based bots. The recent adoption of softwar…

One-Token Rollout: Guiding Supervised Fine-Tuning of LLMs with Policy Gradient
Rui Ming, Haoyuan Wu, Shoubo Hu, Zhuolun He, Bei Yu
https://arxiv.org/abs/2509.26313 https://

One-Token Rollout: Guiding Supervised Fine-Tuning of LLMs with Policy Gradient
Supervised fine-tuning (SFT) is the predominant method for adapting large language models (LLMs), yet it often struggles with generalization compared to reinforcement learning (RL). In this work, we posit that this performance disparity stems not just from the loss function, but from a more fundamental difference: SFT learns from a fixed, pre-collected dataset, whereas RL utilizes on-policy data sampled from the current policy. Building on this hypothesis, we introduce one-token rollout (OTR), …

Revisiting the Uniform Information Density Hypothesis in LLM Reasoning Traces
Minju Gwak, Guijin Son, Jaehyung Kim
https://arxiv.org/abs/2510.06953 https://

Revisiting the Uniform Information Density Hypothesis in LLM Reasoning Traces
The Uniform Information Density (UID) hypothesis suggests that effective communication maintains a stable flow of information. In this work, we revisit this principle in the context of large language model (LLM) reasoning traces, asking whether step-level uniformity reflects reasoning quality. To this end, we propose an entropy-based stepwise information density metric and introduce two complementary measures of uniformity, local and global uniformity scores. Across the experiments on six diffe…

MAD: Manifold Attracted Diffusion
Dennis Elbr\"achter, Giovanni S. Alberti, Matteo Santacesaria
https://arxiv.org/abs/2509.24710 https://arxiv.org/pdf…

MAD: Manifold Attracted Diffusion
Score-based diffusion models are a highly effective method for generating samples from a distribution of images. We consider scenarios where the training data comes from a noisy version of the target distribution, and present an efficiently implementable modification of the inference procedure to generate noiseless samples. Our approach is motivated by the manifold hypothesis, according to which meaningful data is concentrated around some low-dimensional manifold of a high-dimensional ambient s…

Dorabella Cipher as Musical Inspiration
Bradley Hauer, Colin Choi, Abram Hindle, Scott Smallwood, Grzegorz Kondrak
https://arxiv.org/abs/2509.17950 https://

Dorabella Cipher as Musical Inspiration
The Dorabella cipher is an encrypted note written by English composer Edward Elgar, which has defied decipherment attempts for more than a century. While most proposed solutions are English texts, we investigate the hypothesis that Dorabella represents enciphered music. We weigh the evidence for and against the hypothesis, devise a simplified music notation, and attempt to reconstruct a melody from the cipher. Our tools are n-gram models of music which we validate on existing music corpora enci…

Learning in an Echo Chamber: Online Learning with Replay Adversary
Daniil Dmitriev, Harald Eskelund Franck, Carolin Heinzler, Amartya Sanyal
https://arxiv.org/abs/2509.25135 htt…

Learning in an Echo Chamber: Online Learning with Replay Adversary
As machine learning systems increasingly train on self-annotated data, they risk reinforcing errors and becoming echo chambers of their own beliefs. We model this phenomenon by introducing a learning-theoretic framework: Online Learning in the Replay Setting. In round $t$, the learner outputs a hypothesis $\hat{h}_t$; the adversary then reveals either the true label $f^\ast(x_t)$ or a replayed label $\hat{h}_i(x_t)$ from an earlier round $i < t$. A mistake is counted only when the true label is…

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…

Testing maximum entropy models with e-values
Francesca Giuffrida, Diego Garlaschelli, Peter Gr\"unwald
https://arxiv.org/abs/2509.01064 https://arxiv.…

Testing maximum entropy models with e-values
E-values have recently emerged as a robust and flexible alternative to p-values for hypothesis testing, especially under optional continuation, i.e., when additional data from further experiments are collected. In this work, we define optimal e-values for testing between maximum entropy models, both in the microcanonical (hard constraints) and canonical (soft constraints) settings. We show that, when testing between two hypotheses that are both microcanonical, the so-called growth-rate optimal …

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 …

The non-existence of some Galois representations of moderate degree in small characteristic
Alexandru Ghitza, Takuya Yamauchi
https://arxiv.org/abs/2509.00635 https://

The non-existence of some Galois representations of moderate degree in small characteristic
Refining arguments of Hyunsuk Moon, under the assumption of the Generalized Riemann Hypothesis, we prove the non-existence of irreducible mod 2 Galois representations unramified outside 2 of dimensions $\leq 4$, and of totally real such representations of dimensions $\leq 8$. We also prove the non-existence of irreducible totally real mod 3 representations unramified outside 3 of dimensions $\leq 4$. We show unconditionally that the image of an irreducible mod 2 symplectic 4-dimensional Galoi…

Local reminiscence in the PXP model
Francesco Perciavalle, Gian Marco Rizzo, Francesco Plastina, Nicola Lo Gullo
https://arxiv.org/abs/2509.19944 https://a…

Local reminiscence in the PXP model
We study the emergence of local reminiscence in the PXP model, a constrained spin system realized in Rydberg atom arrays. The spectrum of this model is characterized by a majority of eigenstates that satisfy the eigenstate thermalization hypothesis, alongside a set of nonthermal eigenstates, known as quantum many-body scars, that violate it. While generic initial states lead to thermalization consistent with eigenstate thermalization hypothesis, special configurations generate non-ergodic dynam…

Bayesian Estimation and Regularization Techniques in Categorical Data Analysis
Jan Kalina
https://arxiv.org/abs/2509.02222 https://arxiv.org/pdf/2509.02222…

Bayesian Estimation and Regularization Techniques in Categorical Data Analysis
This paper explores Bayesian estimation for categorical data, focusing on simple yet effective models that provide a foundation for applying more advanced methods accurately and reliably in real-world applications. We begin by revisiting Bayesian estimators for the binomial distribution and investigating their properties. Next, we develop hypothesis tests for categorical data (sign test, homogeneity test, symmetry test) based on regularized maximum likelihood estimates of the probabilities. Fin…

Unified theory of testing relevant hypothesis in functional time series
Leheng Cai, Qirui Hu
https://arxiv.org/abs/2508.18624 https://arxiv.org/pdf/2508.18…

Unified theory of testing relevant hypothesis in functional time series
In this paper, we present a general framework for testing relevant hypotheses in functional time series. Our unified approach covers one-sample, two-sample, and change point problems under contaminated observations with arbitrary sampling schemes. By employing B-spline estimators and the self-normalization technique, we propose nuisance-parameter-free testing procedures, obviating the need for additional procedures such as estimating long-run covariance or measurement-error variance functions. …

Investigating the Lottery Ticket Hypothesis for Variational Quantum Circuits
Michael K\"olle, Leonhard Klingert, Julian Sch\"onberger, Philipp Altmann, Tobias Rohe, Claudia Linnhoff-Popien
https://arxiv.org/abs/2509.11190

Investigating the Lottery Ticket Hypothesis for Variational Quantum Circuits
Quantum computing is an emerging field in computer science that has seen considerable progress in recent years, especially in machine learning. By harnessing the principles of quantum physics, it can surpass the limitations of classical algorithms. However, variational quantum circuits (VQCs), which rely on adjustable parameters, often face the barren plateau phenomenon, hindering optimization. The Lottery Ticket Hypothesis (LTH) is a recent concept in classical machine learning that has led to…

On the Birch and Swinnerton-Dyer formula modulo squares for certain quadratic twists of elliptic curves
Alexander J. Barrios, Chung Pang Mok
https://arxiv.org/abs/2510.00926 htt…

On the Birch and Swinnerton-Dyer formula modulo squares for certain quadratic twists of elliptic curves
Let $E/\mathbb{Q}$ be an elliptic curve with conductor $N=N_+N_-$, where $N_+$ and $N_-$ are coprime and $N_-$ is squarefree. Let $D$ be a positive fundamental discriminant satisfying the modified Heegner hypothesis with respect to $(N_+,N_-)$: primes dividing $N_+$ (resp. $N_-$) split (resp. are inert) in $\mathbb{Q}(\sqrt{D})$; we denote by $E^D/\mathbb{Q}$ the quadratic twist of $E/\mathbb{Q}$ by $D$. In the first half of the paper we consider the situation where $N_-$ is a squarefree produc…

Semiclassical analytical solutions of the eigenstate thermalization hypothesis in a quantum billiard
Yaoqi Ye, Chengkai Lin, Xiao Wang
https://arxiv.org/abs/2510.12517 https://

Semiclassical analytical solutions of the eigenstate thermalization hypothesis in a quantum billiard
We derive semiclassical analytical solutions for both the diagonal and off-diagonal functions in the eigenstate thermalization hypothesis (ETH) in a quarter-stadium quantum billiard. For a representative observable, we obtain an explicit expression and an asymptotic closed-form solution that naturally separate into a local contribution and a phase-space correlation term. These analytical results predict the band structure of the observable matrix, including its bandwidth and scaling behavior. W…