Tootfinder

Det är nu över 10 år sedan dietboksförfattare och influensers påstod att de visste hur man fixade tarmfloran och med det en rad olika hälsoproblem.
Och än idag har vi i princip ingenting konkret från vetenskapen kring tarmfloran och behandling av olika besvär utanför just tarmproblem.
The Autism-Microbiome Hypothesis Is Falling Apart

The Autism-Microbiome Hypothesis Is Falling Apart
Why this new review paper should be required reading for every microbiome researcher

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…

Blazars as a Potential Origin of the KM3-230213A Event: #neutrino KM3-23021 3A could come from the diffuse neutrino emission of blazars: https://www.km3net.org/blazar-origin-of-km3-230213a/

A Hypothesis-First Framework for Mechanistic Model Evaluation and Selection in Neuroimaging
Dominic Boutet, Sylvain Baillet
https://arxiv.org/abs/2509.16070 https://

A Hypothesis-First Framework for Mechanistic Model Evaluation and Selection in Neuroimaging
Neuroimaging provides rich measurements of brain structure and neural activity, but turning these data into mechanistic insight remains difficult. Statistical models quantify associations without much considerations for how they arise, whereas bio-realistic models directly embody candidate mechanisms but remain hard to deploy rigorously without specialized training. We present a framework that recasts modeling choices as testable mechanistic hypotheses and supplies a simple protocol for rejecti…

Shanks bias in function fields
Seewoo Lee
https://arxiv.org/abs/2509.16142 https://arxiv.org/pdf/2509.16142

Shanks bias in function fields
We study the function field analogue of Shanks bias. For Liouville function $λ(f)$, we compare the number of monic polynomials $f$ with $λ(f) χ_m(f) = 1$ and $λ(f) χ_m(f) = -1$ for a nontrivial quadratic character $χ_m$ modulo a monic square-free polynomial $m$ over a finite field. Under Grand Simplicity Hypothesis (GSH) for $L$-functions, we prove that $λ\cdot χ_m$ is biased towards $+1$. We also give some examples where GSH is violated.

Edison, which last month released AI tool Kosmos to speed up and automate complex scientific hypothesis generation, raised $70M at a $250M valuation (Rachel Metz/Bloomberg)
https://www.bloomberg.com/news/articles/2025-12-…

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…

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…

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…

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…

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…

Proof of the $p$-adic Kazhdan-Lusztig hypothesis for $\mathrm{GL}(n)$
Kristaps John Balodis
https://arxiv.org/abs/2510.09788 https://arxiv.org/pdf/2510.097…

Proof of the $p$-adic Kazhdan-Lusztig hypothesis for $\mathrm{GL}(n)$
In this article, we prove the $p$-adic Kazhdan-Lusztig hypothesis for $\mathrm{GL}_n(F)$. While the approach via graded affine Hecke algebras due to recent work of Solleveld leads to more general results, this article serves to completes and clarifies the approach via affine Hecke algebras of Chriss and Ginzburg. In particular, this article serves as an opportunity to articulate several results which are undoubtedly known to experts, but have not been formally recorded in the literature.

Hypothesis testing for the dimension of random geometric graph
Mingao Yuan, Feng Yu
https://arxiv.org/abs/2510.11844 https://arxiv.org/pdf/2510.11844

Hypothesis testing for the dimension of random geometric graph
Random geometric graphs (RGGs) offer a powerful tool for analyzing the geometric and dependence structures in real-world networks. For example, it has been observed that RGGs are a good model for protein-protein interaction networks. In RGGs, nodes are randomly distributed over an $m$-dimensional metric space, and edges connect the nodes if and only if their distance is less than some threshold. When fitting RGGs to real-world networks, the first step is probably to input or estimate the dimens…

SliceFine: The Universal Winning-Slice Hypothesis for Pretrained Networks
Md Kowsher, Ali O. Polat, Ehsan Mohammady Ardehaly, Mehrdad Salehi, Zia Ghiasi, Prasanth Murali, Chen Chen
https://arxiv.org/abs/2510.08513

SliceFine: The Universal Winning-Slice Hypothesis for Pretrained Networks
This paper presents a theoretical framework explaining why fine tuning small, randomly selected subnetworks (slices) within pre trained models can be sufficient for downstream adaptation. We prove that pretrained networks exhibit a universal winning slice property arising from two phenomena: (1) spectral balance the eigenspectra of different weight matrix slices are remarkably similar; and (2) high task energy their backbone representations retain rich, task relevant features. This leads to the…

Characterizing Power Spectra of Density Fluctuations in GRMHD Simulations of Black Hole Accretion Using Taylor's Frozen-in Hypothesis
Pravita Hallur, Lia Medeiros, Pierre Christian, George N. Wong
https://arxiv.org/abs/2510.09746

Characterizing Power Spectra of Density Fluctuations in GRMHD Simulations of Black Hole Accretion Using Taylor's Frozen-in Hypothesis
We characterize the spatial power spectrum of density fluctuations in magnetohydrodynamic flows in a suite of high-resolution, long-time-span general relativistic magnetohydrodynamic (GRMHD) simulations. Extracting the local spatial power spectrum in curved spacetime directly from GRMHD simulations can be challenging for several conceptual and mechanical reasons, including choices of the reference frame, the non-uniform co-ordinate grid of the outputs and limited resolution. Taylor's frozen-in …

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 …

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 $p_i$,…

Super resolving binary-source hypothesis testing with a double-clad fiber coupler
John S. Wallis, David R. Gozzard, Alex M. Frost, Benjamin P. Dix-Matthews, Nicolas Maron, Joshua J. Collier
https://arxiv.org/abs/2510.07781

Super resolving binary-source hypothesis testing with a double-clad fiber coupler
We present a technique for binary spatial mode demultiplexing, using a double-clad fiber coupler as an optical mode sorter, for hypothesis testing for one or two point sources in an incident optical field. By directly coupling an optical field through a double-clad fiber coupler, we demultiplex the field into the fundamental mode and a superposition of higher-order modes. We use the ratio of multi-mode to single-mode power to distinguish between single and double point sources. In a tabletop de…

@… and
@… might like this.
I think this is interesting, from "Frontiers in Neuroscience" mag. New "HYPOTHESIS AND THEORY article" by Joachim Keppler, head of Department of Consciousness …

Frontiers | Macroscopic quantum effects in the brain: new insights into the fundamental principle underlying conscious processes
Empirical findings indicate that conscious states are inextricably linked to long-range synchronized activity patterns that result from phase transitions and...

The Adoption Paradox: A Comparative Analysis of Veterinary AI Adoption in China and the North America
Shumin Li, Xiaoyun Lai
https://arxiv.org/abs/2510.11758 https://

The Adoption Paradox: A Comparative Analysis of Veterinary AI Adoption in China and the North America
This study compares the perception, adoption, and application of artificial intelligence (AI) among veterinary professionals in China and North America (NA), testing the hypothesis that adoption patterns are shaped by regional market and demographic factors. A descriptive, cross-sectional survey was conducted with 455 veterinary professionals in China between May and July 2025. The results were compared with published data from a 2024 survey of 3,968 veterinary professionals in the United State…

Personalized Motion Guidance Framework for Athlete-Centric Coaching
Ryota Takamidoa, Chiharu Suzukia, Hiroki Nakamoto
https://arxiv.org/abs/2510.10496 https://

Personalized Motion Guidance Framework for Athlete-Centric Coaching
A critical challenge in contemporary sports science lies in filling the gap between group-level insights derived from controlled hypothesis-driven experiments and the real-world need for personalized coaching tailored to individual athletes' unique movement patterns. This study developed a Personalized Motion Guidance Framework (PMGF) to enhance athletic performance by generating individualized motion-refinement guides using generative artificial intelligence techniques. PMGF leverages a vertic…

A geometrical approach to neutrino oscillation parameters
Mohammad Ful Hossain Seikh
https://arxiv.org/abs/2510.06526 https://arxiv.org/pdf/2510.06526

A geometrical approach to neutrino oscillation parameters
We propose a geometric hypothesis for neutrino mixing: twice the sum of the three mixing angles equals $180^\circ$, forming a Euclidean triangle. This condition leads to a predictive relation among the mixing angles and, through trigonometric constraints, enables reconstruction of the mass-squared splittings. The hypothesis offers a phenomenological resolution to the $θ_{23}$ octant ambiguity, reproduces the known mass hierarchy patterns, and suggests a normalized geometric structure underlyin…

Presentation due Tuesday, paper due Saturday. And tonight my professor ripped apart my hypothesis. Tomorrow is going to be a long day.

Two-cardinal Kurepa Hypotheses
Fanxin Wu
https://arxiv.org/abs/2510.08860 https://arxiv.org/pdf/2510.08860

Two-cardinal Kurepa Hypotheses
We consider the two-cardinal Kurepa Hypothesis $\mathsf{KH}(κ,λ)$. We observe that if $κ\leqλ<μ$ are infinite cardinals then $\lnot\mathsf{KH}(κ,λ)\land\mathsf{KH}(κ,μ)\rightarrow\mathsf{KH}(λ^+,μ)$, and show that in some sense this is the only $\mathsf{ZFC}$ constraint. The case of singular $λ$ and its relation to Chang's Conjecture and scales is discussed. We also extend an independence result about Kurepa and Aronszajn trees due to Cummings to the case of successors of singular c…

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…

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 …

Doctor Rashomon and the UNIVERSE of Madness: Variable Importance with Unobserved Confounding and the Rashomon Effect
Jon Donnelly, Srikar Katta, Emanuele Borgonovo, Cynthia Rudin
https://arxiv.org/abs/2510.12734

Doctor Rashomon and the UNIVERSE of Madness: Variable Importance with Unobserved Confounding and the Rashomon Effect
Variable importance (VI) methods are often used for hypothesis generation, feature selection, and scientific validation. In the standard VI pipeline, an analyst estimates VI for a single predictive model with only the observed features. However, the importance of a feature depends heavily on which other variables are included in the model, and essential variables are often omitted from observational datasets. Moreover, the VI estimated for one model is often not the same as the VI estimated for…

Self-replication and Computational Universality
Jordan Cotler, Cl\'ement Hongler, Barbora Hudcov\'a
https://arxiv.org/abs/2510.08342 https://arxiv.…

Memory Retrieval and Consolidation in Large Language Models through Function Tokens
Shaohua Zhang, Yuan Lin, Hang Li
https://arxiv.org/abs/2510.08203 https://

Memory Retrieval and Consolidation in Large Language Models through Function Tokens
The remarkable success of large language models (LLMs) stems from their ability to consolidate vast amounts of knowledge into the memory during pre-training and to retrieve it from the memory during inference, enabling advanced capabilities such as knowledge memorization, instruction-following and reasoning. However, the mechanisms of memory retrieval and consolidation in LLMs remain poorly understood. In this paper, we propose the function token hypothesis to explain the workings of LLMs: Duri…

On modular invariants of the truncated polynomial ring in rank four
Dang Vo Phuc
https://arxiv.org/abs/2510.11464 https://arxiv.org/pdf/2510.11464

On modular invariants of the truncated polynomial ring in rank four
We prove the rank-4 case of the conjecture of Ha-Hai-Nghia for the invariant subspace of the truncated polynomial ring $\mathcal{Q}_m(n)=\mathbb{F}_q[x_1,\dots,x_n]/(x_1^{q^m},\dots,x_n^{q^m}),$ under a new, explicit technical hypothesis. Our argument extends the determinant calculus for the delta operator by deriving crucial rank-4 identities governing its interaction with the Dickson algebra. We show that the proof of the conjecture reduces to a specific vanishing property, for which we intro…

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.

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.

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…

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 polar debris disc around 99 Herculis: A potential signpost for polar circumbinary planets
Jeremy L. Smallwood, William DeRocco, Zhizhen Qin, Antranik A. Sefilian
https://arxiv.org/abs/2510.08698

The polar debris disc around 99 Herculis: A potential signpost for polar circumbinary planets
The nearby binary star system 99 Herculis (99 Her) is host to the only known polar-aligned circumbinary debris disc. We investigate the hypothesis that the narrow structure of this circumbinary disc is sculpted by the gravitational influence of one or more unseen polar circumbinary planets. We first establish the theoretically viable parameter space for a sculpting planet by considering dynamical stability and clearing mechanisms, including the chaotic zone, Hill radius, diffusion, and polar al…

SR-Scientist: Scientific Equation Discovery With Agentic AI
Shijie Xia, Yuhan Sun, Pengfei Liu
https://arxiv.org/abs/2510.11661 https://arxiv.org/pdf/2510.…

SR-Scientist: Scientific Equation Discovery With Agentic AI
Recently, Large Language Models (LLMs) have been applied to scientific equation discovery, leveraging their embedded scientific knowledge for hypothesis generation. However, current methods typically confine LLMs to the role of an equation proposer within search algorithms like genetic programming. In this paper, we present SR-Scientist, a framework that elevates the LLM from a simple equation proposer to an autonomous AI scientist that writes code to analyze data, implements the equation as co…

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)…

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…

On orientations preserving edge-connectivity in infinite graphs
Leandro Aurichi, Paulo Magalh\~aes J\'unior, Guilherme Eduardo Pinto
https://arxiv.org/abs/2510.06449 https:/…

On orientations preserving edge-connectivity in infinite graphs
We prove that every 2k-edge-connected graph with countably many edge-ends admits a k-arc-connected orientation, extending the previous result by Assem, Koloschin and Pitz that also assumed the hypothesis of the graph being locally finite. We prove that, if every locally finite graph has a well-balanced orientation, so does every graph. Lastly, we explore an alternative to the Nash-Williams Orientation Conjecture via topological paths, and prove that it is true for every finitely separated graph.

Detecting Black Hole Microstates
Vijay Balasubramanian, William KL Chan, Chitraang Murdia
https://arxiv.org/abs/2510.06309 https://arxiv.org/pdf/2510.06309…

Detecting Black Hole Microstates
We demonstrate that the Euclidean two-point function of an appropriately chosen probe operator can detect the microstate of an asymptotically AdS black hole. This detection, which requires a tuned, state-dependent choice of probe, is the result of a new gravitational saddle, which dominates over the usual saddles. The gravitational result can be explicitly reproduced in the dual boundary CFT if we assume the eigenstate thermalization hypothesis. We also discuss a binary search protocol to detec…

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…

Bayes Meets Riemann Again: Large Prime Discovery and Re-emergence of the Bone of Contention
Durba Bhattacharya, Sucharita Roy, Sourabh Bhattacharya
https://arxiv.org/abs/2510.09651

Bayes Meets Riemann Again: Large Prime Discovery and Re-emergence of the Bone of Contention
Prime numbers have fascinated mathematicians since antiquity, with ongoing efforts to uncover both their properties and ever-larger examples. While giant primes rarely aid cryptography, they find use in areas such as locally decodable codes. Large prime-hunting, often brute-force in nature, is conceptually linked to the Riemann Hypothesis and the prime number theorem, which portrays prime distribution as essentially random. This motivates a statistical perspective, with Bayesian methodology pro…

When vacuum breaks: a self-consistency test for astrophysical environments in extreme mass ratio inspirals
Lorenzo Copparoni, Rohit S. Chandramouli, Enrico Barausse
https://arxiv.org/abs/2510.06948

When vacuum breaks: a self-consistency test for astrophysical environments in extreme mass ratio inspirals
Gravitational-wave signals are typically interpreted under the vacuum hypothesis, i.e. assuming negligible influence from the astrophysical environment. This assumption is expected to break down for low-frequency sources such as extreme mass ratio inspirals (EMRIs), which are prime targets for the Laser Interferometer Space Antenna (LISA) and are expected to form, at least in part, in dense environments such as Active Galactic Nuclei or dark-matter spikes/cores. Modeling environmental effects p…

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 …

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…

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.

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…

Mathematical basis, phase transitions and singularities of (3 1)-dimensional phi4 scalar field model
Zhidong Zhang
https://arxiv.org/abs/2511.07439 https://arxiv.org/pdf/2511.07439 https://arxiv.org/html/2511.07439
arXiv:2511.07439v1 Announce Type: new
Abstract: The lambda phi4 scalar field model that can be applied to interpret pion-pion scattering and properties of hadrons. In this work, the mathematical basis, phase transitions and singularities of a (3 1)-dimensional (i.e., (3 1)D) phi4 scalar field model are investigated. It is found that as a specific example of topological quantum field theories, the (3 1)D phi4 scalar field model must be set up on the Jordan-von Neumann-Wigner framework and dealt with the parameter space of complex time (or complex temperature). The use of the time average and the topologic Lorentz transformation representing Reidemeister moves ensure the integrability, which takes into account for the contributions of nontrivial topological structures to physical properties of the many-body interacting system. The ergodic hypothesis is violated at finite temperatures in the (3 1)D phi4 scalar field model. Because the quantum field theories with ultraviolet cutoff can be mapped to the models in statistical mechanics, the (3 1)D phi4 scalar field model with ultraviolet cutoff is studied by inspecting its relation with the three-dimensional (3D) Ising model. Furthermore, the direct relation between the coupling K in the 3D Ising model and the bare coupling lambda0 in the (3 1)D phi4 scalar field model is determined in the strong coupling limit. The results obtained in the present work can be utilized to investigate thermodynamic physical properties and critical phenomena of quantum (scalar) field theories.
toXiv_bot_toot

Exact Matching and Top-k Perfect Matching Parameterized by Neighborhood Diversity or Bandwidth
Nicolas El Maalouly, Kostas Lakis
https://arxiv.org/abs/2510.12552 https://…

Exact Matching and Top-k Perfect Matching Parameterized by Neighborhood Diversity or Bandwidth
The Exact Matching (EM) problem asks whether there exists a perfect matching which uses a prescribed number of red edges in a red/blue edge-colored graph. While there exists a randomized polynomial-time algorithm for the problem, only some special cases admit a deterministic one so far, making it a natural candidate for testing the P=RP hypothesis. A polynomial-time equivalent problem, Top-k Perfect Matching (TkPM), asks for a perfect matching maximizing the weight of the $k$ heaviest edges. …

Rethinking Knowledge Distillation: A Data Dependent Regulariser With a Negative Asymmetric Payoff
Israel Mason-Williams, Gabryel Mason-Williams, Helen Yannakoudakis
https://arxiv.org/abs/2510.12615

Rethinking Knowledge Distillation: A Data Dependent Regulariser With a Negative Asymmetric Payoff
Knowledge distillation is often considered a compression mechanism when judged on the resulting student's accuracy and loss, yet its functional impact is poorly understood. In this work, we quantify the compression capacity of knowledge distillation and the resulting knowledge transfer from a functional perspective, decoupling compression from architectural reduction, which provides an improved understanding of knowledge distillation. We employ hypothesis testing, controls, and random control d…

Probing the Origin of Water in Planets within Habitable Zones by HWO
Yasuhiro Hasegawa, Courtney Dressing, Ludmila Carone
https://arxiv.org/abs/2510.07349 https://

Probing the Origin of Water in Planets within Habitable Zones by HWO
How do habitable environments arise and evolve within the context of their planetary systems? This is one fundamental question, and it can be addressed partly by identifying how planets in habitable zones obtain water. Historically, astronomers considered that water was delivered to the Earth via dynamical shake-up by Jupiter, which took place during the formation and post-formation eras (e.g., $\lesssim 100$ Myr). This hypothesis has recently been challenged by a more dynamic view of planet fo…

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 …

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…

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…

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, $…

Neural Hardware for the Language of Thought: New Rules for an Old Game
Gualtiero Piccinini
https://arxiv.org/abs/2510.10251 https://arxiv.org/pdf/2510.1025…

Neural Hardware for the Language of Thought: New Rules for an Old Game
The Language of Thought (LOT) hypothesis posits that at least some important cognitive processes involve language-like representations. These representations must be processed by appropriate hardware. Since the organ of biological cognition is the nervous system, whether biological cognition relies on a LOT depends on how neural hardware works. I distinguish between different versions of LOT, articulate their hardware requirements, and consider which versions of LOT are supported by empirical e…

Accretion onto Reissner-Nordstr\"{o}m naked singularities
Tomasz Krajewski, W{\l}odek Klu\'zniak
https://arxiv.org/abs/2510.10043 https://arxiv.or…

Accretion onto Reissner-Nordström naked singularities
Nearly every galactic core contains a supermassive compact object, hypothesized to be a Kerr black hole. It was only with the advent of Event Horizon Telescope observations that the predictions of this hypothesis could be observationally tested for our own Galaxy, and the nearby elliptical M87, on spatial scales comparable to the gravitational radius. At the same time it became possible to test whether alternatives such as naked singularities in general relativity, or similar objects in alterna…

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…

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…

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 …

Exchange for Growth: Currency Dynamics in Emerging Markets
Shaunak Kulkarni, Rohan Ajay Dubey
https://arxiv.org/abs/2510.07039 https://arxiv.org/pdf/2510.0…

Exchange for Growth: Currency Dynamics in Emerging Markets
Currency crises are frequently discussed retrospectively as a necessary and deterministic outcome of a finite sequence of fiscal decisions, monetary manoeuvres, and limited exogenous inputs. Parallelly, the Twin Deficits Hypothesis (TDH) posits that an increase in the budget deficit leads to a direct rise in the current account deficit; although analogous to the idea of currency crises being the outcome of finite inputs (through a balance of payments crisis here), this notion runs contrary to t…

Interplay of Fidelity and Diversity in the Evolution of the Genetic Code
Yudam Seo, Tsvi Tlusty, Junghyo Jo
https://arxiv.org/abs/2510.10871 https://arxiv.…

Interplay of Fidelity and Diversity in the Evolution of the Genetic Code
The origin and organizing principles of the genetic code remain fundamental puzzles in life science. The vanishingly low probability of the natural codon-to-amino acid mapping arising by chance has spurred the hypothesis that its structure is a solution optimized for robustness against mutations and translational errors. For the construction of effective molecular machines, the dictionary of encoded amino acids must also be diverse enough in physicochemical features. Here, we examine whether th…

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…

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…

A Kolmogorov-Smirnov-Type Test for Dependently Double-Truncated Data
Anne-Marie Toparkus, Rafael Weissbach
https://arxiv.org/abs/2510.11517 https://arxiv.o…

A Kolmogorov-Smirnov-Type Test for Dependently Double-Truncated Data
With double-truncated lifespans, we test the hypothesis of a parametric distribution family for the lifespan. The typical finding from demography is an instationary behaviour of the life expectancy, and a copula models the resulting weak dependence of lifespan and the age at truncation. Our main example is the Farlie-Gumbel-Morgenststern copula. The test is based on Donsker-class arguments and the functional delta method for empirical processes. The assumptions also allow parametric inference, …

Engineering Dominating Patterns: A Fine-grained Case Study
Jonathan Dransfeld, Marvin K\"unnemann, Mirza Redzic, Marcus Wunderlich
https://arxiv.org/abs/2510.12232 https://…

Engineering Dominating Patterns: A Fine-grained Case Study
The \emph{Dominating $H$-Pattern} problem generalizes the classical $k$-Dominating Set problem: for a fixed \emph{pattern} $H$ and a given graph $G$, the goal is to find an induced subgraph $S$ of $G$ such that (1) $S$ is isomorphic to $H$, and (2) $S$ forms a dominating set in $G$. Fine-grained complexity results show that on worst-case inputs, any significant improvement over the naive brute-force algorithm is unlikely, as this would refute the Strong Exponential Time Hypothesis. Nevertheless…

Replaced article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Hypothesis testing on invariant subspaces of non-diagonalizable matrices with applications to net...
J\'er\^ome R. Simons

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…

Artificial intelligence as a surrogate brain: Bridging neural dynamical models and data
Yinuo Zhang, Demao Liu, Zhichao Liang, Jiani Cheng, Kexin Lou, Jinqiao Duan, Ting Gao, Bin Hu, Quanying Liu
https://arxiv.org/abs/2510.10308

Artificial intelligence as a surrogate brain: Bridging neural dynamical models and data
Recent breakthroughs in artificial intelligence (AI) are reshaping the way we construct computational counterparts of the brain, giving rise to a new class of ``surrogate brains''. In contrast to conventional hypothesis-driven biophysical models, the AI-based surrogate brain encompasses a broad spectrum of data-driven approaches to solve the inverse problem, with the primary objective of accurately predicting future whole-brain dynamics with historical data. Here, we introduce a unified framewo…

The Second Moment of $\mathrm{GL}_3 \times \mathrm{GL}_2$ $L$-functions at Special Points
Zhi Qi
https://arxiv.org/abs/2510.11191 https://arxiv.org/pdf/251…

The Second Moment of $\mathrm{GL}_3 \times \mathrm{GL}_2$ $L$-functions at Special Points
Let $ϕ$ be a fixed Hecke--Maass form for $\mathrm{SL}_3 (\mathbb{Z})$ and $u_j $ traverse an orthonormal basis of Hecke--Maass forms for $\mathrm{SL}_2 (\mathbb{Z}) $. Let $1/4+t_j^2$ be the Laplace eigenvalue of $u_j $. In this paper, we prove the mean Lindelöf hypothesis for the second moment of $ L (1/2+it_j, ϕ\times u_j) $ on $ T < t_j \leqslant T + \sqrt{T} $. Previously, this was proven by Young on $ t_j \leqslant T$. Our approach is more direct as we do not apply the Poisson summation…

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…

Evaluation of the magnetic field of hot Jupiters within the geometric approach
Babenko I. A., Zhilkin A. G
https://arxiv.org/abs/2509.16565 https://arxiv.o…

Evaluation of the magnetic field of hot Jupiters within the geometric approach
Theoretical and experimental foundations of the hypothesis about the origin of the magnetic fields of the Earth and other astrophysical objects, proposed in the early 20th century by W. Sutherland, A. Einstein, and independently by Yu.S. Vladimirov, are discussed in the paper. According to this hypothesis, the electric charges of the electron and proton slightly differ in magnitude, leading to the emergence of a magnetic field in rotating astrophysical objects. The theoretical justification of …

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…

Absolutely Abelian Hilbert Class Fields and $\ell$-torsion conjecture
Mahesh Kumar Ram, Prem Prakash Pandey, Nimish Kumar Mahapatra
https://arxiv.org/abs/2510.10725 https://

Absolutely Abelian Hilbert Class Fields and $\ell$-torsion conjecture
There are several recent works where authors have shown that number fields $K$ with `sufficiently many' units and cyclic class group contain a Euclidean ideal class provided the Hilbert class field $H(K)$ is an abelian extension of $\mathbb{Q}$. In this article, we explore the latter hypothesis: how often a number field $K$ satisfies that its Hilbert class field $H(K)$ is an abelian extension of $\mathbb{Q}$? We also noticed that for such number fields, when the Hilbert class field is an abelia…

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 compressed code for memory discrimination
Dale Zhou, Sharon Mina Noh, Nora C Harhen, Nidhi V Banavar, C. Brock Kirwan, Michael A Yassa, Aaron M Bornstein
https://arxiv.org/abs/2510.10791

A compressed code for memory discrimination
The ability to discriminate similar visual stimuli is an important index of memory function. This ability is widely thought to be supported by expanding the dimensionality of relevant neural codes, such that neural representations for similar stimuli are maximally distinct, or ``separated.'' An alternative hypothesis is that discrimination is supported by lossy compression of visual inputs, efficiently coding sensory information by discarding seemingly irrelevant details. A benefit of compressi…

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…

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://

Characterizing the Multiclass Learnability of Forgiving 0-1 Loss Functions
Jacob Trauger, Tyson Trauger, Ambuj Tewari
https://arxiv.org/abs/2510.08382 https://

Characterizing the Multiclass Learnability of Forgiving 0-1 Loss Functions
In this paper we will give a characterization of the learnability of forgiving 0-1 loss functions in the finite label multiclass setting. To do this, we create a new combinatorial dimension that is based off of the Natarajan Dimension \citep{natarajan1989learning} and we show that a hypothesis class is learnable in our setting if and only if this Generalized Natarajan Dimension is finite. We also show a connection to learning with set-valued feedback. Through our results we show that the learna…

Spin quantum computing, spin quantum cognition
Betony Adams, Francesco Petruccione
https://arxiv.org/abs/2510.07196 https://arxiv.org/pdf/2510.07196…

Spin quantum computing, spin quantum cognition
Over two decades ago, Bruce Kane proposed that spin-half phosphorus nuclei embedded in a spin-zero silicon substrate could serve as a viable platform for spin-based quantum computing. These nuclear spins exhibit remarkably long coherence times, making them ideal candidates for qubits. Despite this advantage, practical realisation of spin quantum computing remains a challenge. More recently, physicist Matthew Fisher proposed a hypothesis linking nuclear spin dynamics, specifically those of phosp…

Note on large quadratic character sums
Zikang Dong, Yutong Song, Ruihua Wang, Shengbo Zhao
https://arxiv.org/abs/2510.09005 https://arxiv.org/pdf/2510.0900…

Note on large quadratic character sums
In this article, we investigate the conditional large values of quadratic Dirichlet character sums. We prove an Omega result for quadratic character sums under the assumption of the generalized Riemann hypothesis.

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…

Confidence Regions for Multiple Outcomes, Effect Modifiers, and Other Multiple Comparisons
Paul N Zivich, Stephen R Cole, Noah Greifer, Lina M Montoya, Michael R Kosorok, Jessie K Edwards
https://arxiv.org/abs/2510.07076

Confidence Regions for Multiple Outcomes, Effect Modifiers, and Other Multiple Comparisons
In epidemiology, some have argued that multiple comparison corrections are not necessary as there is rarely interest in the universal null hypothesis. From a parameter estimation perspective, epidemiologists may still be interested in multiple parameters. In this context, standard confidence intervals are not guaranteed to provide simultaneous coverage of more than one parameter. In other words, use of confidence intervals in these cases will understate the uncertainty due to random error. To a…

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…

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…

Bridging the behavior-neural gap: A multimodal AI reveals the brain's geometry of emotion more accurately than human self-reports
Changde Du, Yizhuo Lu, Zhongyu Huang, Yi Sun, Zisen Zhou, Shaozheng Qin, Huiguang He
https://arxiv.org/abs/2509.24298

Bridging the behavior-neural gap: A multimodal AI reveals the brain's geometry of emotion more accurately than human self-reports
The ability to represent emotion plays a significant role in human cognition and social interaction, yet the high-dimensional geometry of this affective space and its neural underpinnings remain debated. A key challenge, the `behavior-neural gap,' is the limited ability of human self-reports to predict brain activity. Here we test the hypothesis that this gap arises from the constraints of traditional rating scales and that large-scale similarity judgments can more faithfully capture the brain'…

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…

Reading Images Like Texts: Sequential Image Understanding in Vision-Language Models
Yueyan Li, Chenggong Zhao, Zeyuan Zang, Caixia Yuan, Xiaojie Wang
https://arxiv.org/abs/2509.19191

Reading Images Like Texts: Sequential Image Understanding in Vision-Language Models
Vision-Language Models (VLMs) have demonstrated remarkable performance across a variety of real-world tasks. However, existing VLMs typically process visual information by serializing images, a method that diverges significantly from the parallel nature of human vision. Moreover, their opaque internal mechanisms hinder both deeper understanding and architectural innovation. Inspired by the dual-stream hypothesis of human vision, which distinguishes the "what" and "where" pathways, we deconstruc…

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…

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), …

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…

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 …

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- State-space kinetic Ising model reveals task-dependent entropy flow in sparsely active nonequilib...
Ken Ishihara, Hideaki Shimazaki
https://arxiv.org/abs/2502.15440 https://mastoxiv.page/@arXiv_qbioNC_bot/114057779012161849
- Mechanisms for anesthesia, unawareness, respiratory depression, memory replay and sleep: MHb > IP...
Karin Vadovi\v{c}ov\'a
https://arxiv.org/abs/2509.04454 https://mastoxiv.page/@arXiv_qbioNC_bot/115167812677714466
- Meta-learning three-factor plasticity rules for structured credit assignment with sparse feedback
Dimitra Maoutsa
https://arxiv.org/abs/2512.09366 https://mastoxiv.page/@arXiv_qbioNC_bot/115699940165988688
- Prefrontal scaling of reward prediction error readout gates reinforcement-derived adaptive behavi...
Sang, Huang, Zhong, Wang, Yu, Li, Feng, Wang, Chai, Menon, Wang, Fang, Wang
https://arxiv.org/abs/2512.09761 https://mastoxiv.page/@arXiv_qbioNC_bot/115700046994546552
- Proof of a perfect platonic representation hypothesis
Liu Ziyin, Isaac Chuang
https://arxiv.org/abs/2507.01098 https://mastoxiv.page/@arXiv_csLG_bot/114788750477759162
toXiv_bot_toot

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. …

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://

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.

From Input Perception to Predictive Insight: Modeling Model Blind Spots Before They Become Errors
Maggie Mi, Aline Villavicencio, Nafise Sadat Moosavi
https://arxiv.org/abs/2509.20065

From Input Perception to Predictive Insight: Modeling Model Blind Spots Before They Become Errors
Language models often struggle with idiomatic, figurative, or context-sensitive inputs, not because they produce flawed outputs, but because they misinterpret the input from the outset. We propose an input-only method for anticipating such failures using token-level likelihood features inspired by surprisal and the Uniform Information Density hypothesis. These features capture localized uncertainty in input comprehension and outperform standard baselines across five linguistically challenging d…

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…

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…

Rationality fields of CM modular forms
Kimball Martin
https://arxiv.org/abs/2509.24119 https://arxiv.org/pdf/2509.24119

Rationality fields of CM modular forms
We formulate a conjecture on the finitude of rationality fields (i.e., Fourier coefficient fields) of newforms of bounded degree, and prove this for CM forms assuming a generalized Riemann hypothesis. Then we explicitly determine what quadratic and cubic rationality fields occur for weight 2 CM forms, which is related to classifications of CM abelian varieties of GL(2) type. Several of these fields do not appear in the existing tables of newforms in the LMFDB.