Tootfinder

Appeals court rejects Trump’s authority to impose sweeping tariffs under IEEPA.
(Wait for SCOTUS to reverse this)
https://storage.courtlistener.com/recap/gov.uscourts.cafc.23105/gov.uscourts.cafc.23105.159.0_1.pdf

from my link log —
Recursive data structures. (Hoare, 1973)
https://apps.dtic.mil/sti/pdfs/AD0772509.pdf
saved 2025-09-25 https://d…

GCVE-BCP-04 - Recommendations and Best Practices for ID Allocation version 1.1 published.
BCP Document https://gcve.eu/bcp/gcve-bcp-04/
PDF https://

ANDRITZ: Renewable energy from tidal currents
https://www.andritz.com/resource/blob/31444/cf15d27bc23fd59db125229506ec87c7/hy-hammerfest-data.pdf

Analise Semantica Automatizada com LLM e RAG para Bulas Farmaceuticas
Daniel Meireles do Rego
https://arxiv.org/abs/2507.21103 https://arxiv.org/pdf/2507.2…

Analise Semantica Automatizada com LLM e RAG para Bulas Farmaceuticas
The production of digital documents has been growing rapidly in academic, business, and health environments, presenting new challenges in the efficient extraction and analysis of unstructured information. This work investigates the use of RAG (Retrieval-Augmented Generation) architectures combined with Large-Scale Language Models (LLMs) to automate the analysis of documents in PDF format. The proposal integrates vector search techniques by embeddings, semantic data extraction and generation of …

Overclocking Electrostatic Generative Models
Daniil Shlenskii, Alexander Korotin
https://arxiv.org/abs/2509.22454 https://arxiv.org/pdf/2509.22454

Overclocking Electrostatic Generative Models
Electrostatic generative models such as PFGM++ have recently emerged as a powerful framework, achieving state-of-the-art performance in image synthesis. PFGM++ operates in an extended data space with auxiliary dimensionality $D$, recovering the diffusion model framework as $D\to\infty$, while yielding superior empirical results for finite $D$. Like diffusion models, PFGM++ relies on expensive ODE simulations to generate samples, making it computationally costly. To address this, we propose Inve…

Category Discovery: An Open-World Perspective
Zhenqi He, Yuanpei Liu, Kai Han
https://arxiv.org/abs/2509.22542 https://arxiv.org/pdf/2509.22542

Category Discovery: An Open-World Perspective
Category discovery (CD) is an emerging open-world learning task, which aims at automatically categorizing unlabelled data containing instances from unseen classes, given some labelled data from seen classes. This task has attracted significant attention over the years and leads to a rich body of literature trying to address the problem from different perspectives. In this survey, we provide a comprehensive review of the literature, and offer detailed analysis and in-depth discussion on differen…

Large Language Models as Nondeterministic Causal Models
Sander Beckers
https://arxiv.org/abs/2509.22297 https://arxiv.org/pdf/2509.22297

Large Language Models as Nondeterministic Causal Models
Recent work by Chatzi et al. and Ravfogel et al. has developed, for the first time, a method for generating counterfactuals of probabilistic Large Language Models. Such counterfactuals tell us what would - or might - have been the output of an LLM if some factual prompt ${\bf x}$ had been ${\bf x}^*$ instead. The ability to generate such counterfactuals is an important necessary step towards explaining, evaluating, and comparing, the behavior of LLMs. I argue, however, that the existing method …

ArabJobs: A Multinational Corpus of Arabic Job Ads
Mo El-Haj
https://arxiv.org/abs/2509.22589 https://arxiv.org/pdf/2509.22589

ArabJobs: A Multinational Corpus of Arabic Job Ads
ArabJobs is a publicly available corpus of Arabic job advertisements collected from Egypt, Jordan, Saudi Arabia, and the United Arab Emirates. Comprising over 8,500 postings and more than 550,000 words, the dataset captures linguistic, regional, and socio-economic variation in the Arab labour market. We present analyses of gender representation and occupational structure, and highlight dialectal variation across ads, which offers opportunities for future research. We also demonstrate applicatio…

Equivalence via surjections
Tom Leinster
https://arxiv.org/abs/2508.20555 https://arxiv.org/pdf/2508.20555

Equivalence via surjections
Many types of categorical structure obey the following principle: the natural notion of equivalence is generated, as an equivalence relation, by identifying $A$ with $B$ when there exists a strictly structure-preserving map $A \to B$ that is genuinely (not just essentially) surjective in each dimension and faithful in the top dimension. We prove this principle for four types of structure: categories, monoidal categories, bicategories and double categories. The last of these theorems suggests th…

Semantic Numeration Systems as Dynamical Systems
Alexander Yu. Chunikhin
https://arxiv.org/abs/2507.21295 https://arxiv.org/pdf/2507.21295

Semantic Numeration Systems as Dynamical Systems
The foundational concepts of semantic numeration systems theory are briefly outlined. The action of cardinal semantic operators unfolds over a set of cardinal abstract entities belonging to the cardinal semantic multeity. The cardinal abstract object (CAO) formed by them in a certain connectivity topology is proposed to be considered as a linear discrete dynamical system with nonlinear control. Under the assumption of ideal observability, the CAO state equations are provided for both stationary…

Efficient Cost Bounds with Linear Maps
David M Kahn, Jan Hoffmann, Thomas Reps, Jessie Grosen
https://arxiv.org/abs/2509.22982 https://arxiv.org/pdf/2509.2…

Efficient Cost Bounds with Linear Maps
The Automatic Amortized Resource Analysis (AARA) derives program-execution cost bounds using types. To do so, AARA often makes use of cost-free types, which are critical for the composition of types and cost bounds. However, inferring cost-free types using the current state-of-the-art algorithm is expensive due to recursive dependence on additional cost-free types. Furthermore, that algorithm uses a heuristic only applicable to polynomial cost bounds, and not, e.g., exponential bounds. This pap…

QIP $ \subseteq $ AM(2QCFA)
Abuzer Yakary{\i}lmaz
https://arxiv.org/abs/2508.21020 https://arxiv.org/pdf/2508.21020…

QIP $ \subseteq $ AM(2QCFA)
The class of languages having polynomial-time classical or quantum interactive proof systems ($\mathsf{IP}$ or $\mathsf{QIP}$, respectively) is identical to $\mathsf{PSPACE}$. We show that $\mathsf{PSPACE}$ (and so $\mathsf{QIP}$) is subset of $\mathsf{AM(2QCFA)}$, the class of languages having Arthur-Merlin proof systems where the verifiers are two-way finite automata with quantum and classical states (2QCFAs) communicating with the provers classically. Our protocols use only rational-valued q…

World's First Authenticated Satellite Pseudorange from Orbit
Jason Anderson
https://arxiv.org/abs/2509.21601 https://arxiv.org/pdf/2509.21601

World's First Authenticated Satellite Pseudorange from Orbit
Cryptographic Ranging Authentication is here! We present initial results on the Pulsar authenticated ranging service broadcast from space with Pulsar-0 utilizing a recording taken at Xona headquarters in Burlingame, CA. No assumptions pertaining to the ownership or leakage of encryption keys are required. This work discusses the Pulsar watermark design and security analysis. We derive the Pulsar watermark's probabilities of missed detection and false alarm, and we discuss the required receiver …

Improved Vehicle Maneuver Prediction using Game Theoretic Priors
Nishant Doshi
https://arxiv.org/abs/2509.21873 https://arxiv.org/pdf/2509.21873

Improved Vehicle Maneuver Prediction using Game Theoretic Priors
Conventional maneuver prediction methods use some sort of classification model on temporal trajectory data to predict behavior of agents over a set time horizon. Despite of having the best precision and recall, these models cannot predict a lane change accurately unless they incorporate information about the entire scene. Level-k game theory can leverage the human-like hierarchical reasoning to come up with the most rational decisions each agent can make in a group. This can be leveraged to mod…

A theoretical guarantee for SyncRank
Yang Rao
https://arxiv.org/abs/2509.22766 https://arxiv.org/pdf/2509.22766

A theoretical guarantee for SyncRank
We present a theoretical and empirical analysis of the SyncRank algorithm for recovering a global ranking from noisy pairwise comparisons. By adopting a complex-valued data model where the true ranking is encoded in the phases of a unit-modulus vector, we establish a sharp non-asymptotic recovery guarantee for the associated semidefinite programming (SDP) relaxation. Our main theorem characterizes a critical noise threshold - scaling as sigma = O(sqrt(n / log n)) - below which SyncRank achieves…

Dynamics of Gender Bias in Software Engineering
Thomas J. Misa
https://arxiv.org/abs/2508.21050 https://arxiv.org/pdf/2508.21050

Dynamics of Gender Bias in Software Engineering
The field of software engineering is embedded in both engineering and computer science, and may embody gender biases endemic to both. This paper surveys software engineering's origins and its long-running attention to engineering professionalism, profiling five leaders; it then examines the field's recent attention to gender issues and gender bias. It next quantitatively analyzes women's participation as research authors in the field's leading International Conference of Software Engineering (1…

Attention is also needed for form design
B. Sankar, Dibakar Sen
https://arxiv.org/abs/2508.19708 https://arxiv.org/pdf/2508.19708

Attention is also needed for form design
Conventional product design is a cognitively demanding process, limited by its time-consuming nature, reliance on subjective expertise, and the opaque translation of inspiration into tangible concepts. This research introduces a novel, attention-aware framework that integrates two synergistic systems: EUPHORIA, an immersive Virtual Reality environment using eye-tracking to implicitly capture a designer's aesthetic preferences, and RETINA, an agentic AI pipeline that translates these implicit pr…

DHS released over the weekend its plans to deal with a government shutdown should that happen. CISA estimates 889 employees out of 2,540 total employees as the total number expected and estimated to be retained during a lapse in appropriations.
https://www.…

“ Countering Chinese State-Sponsored Actors Compromise of Networks Worldwide to Feed Global Espionage System”
#china

Senate report on DOGE dropped, here's a choice quote
PDF: https://www.hsgac.senate.gov/wp-content/uploads/DOGE_REPORT_FINAL_7.pdf

Delta-system method: a survey
Andrey Kupavskii
https://arxiv.org/abs/2508.20132 https://arxiv.org/pdf/2508.20132 …

Delta-system method: a survey
In 1960 Erd\H os and Rado published a paper that, in retrospect, became one of the most influential papers in extremal set theory. They proved a result of Ramsey theoretic flavour, stating that in any sufficiently large family of sets of bounded size there is a homogeneous substructure, called a $Δ$-system (also known under the name of a sunflower). For many qualitative results in Discrete Mathematics and Theoretical Computer Science, this has become a very powerful tool to analyze complex set…

Activation Function Design Sustains Plasticity in Continual Learning
Lute Lillo, Nick Cheney
https://arxiv.org/abs/2509.22562 https://arxiv.org/pdf/2509.22…

Activation Function Design Sustains Plasticity in Continual Learning
In independent, identically distributed (i.i.d.) training regimes, activation functions have been benchmarked extensively, and their differences often shrink once model size and optimization are tuned. In continual learning, however, the picture is different: beyond catastrophic forgetting, models can progressively lose the ability to adapt (referred to as loss of plasticity) and the role of the non-linearity in this failure mode remains underexplored. We show that activation choice is a primar…

Text Adversarial Attacks with Dynamic Outputs
Wenqiang Wang, Siyuan Liang, Xiao Yan, Xiaochun Cao
https://arxiv.org/abs/2509.22393 https://arxiv.org/pdf/25…

Text Adversarial Attacks with Dynamic Outputs
Text adversarial attack methods are typically designed for static scenarios with fixed numbers of output labels and a predefined label space, relying on extensive querying of the victim model (query-based attacks) or the surrogate model (transfer-based attacks). To address this gap, we introduce the Textual Dynamic Outputs Attack (TDOA) method, which employs a clustering-based surrogate model training approach to convert the dynamic-output scenario into a static single-output scenario. To impro…

Human-AI Collaborative Bot Detection in MMORPGs
Jaeman Son, Hyunsoo Kim
https://arxiv.org/abs/2508.20578 https://arxiv.org/pdf/2508.20578

Human-AI Collaborative Bot Detection in MMORPGs
In Massively Multiplayer Online Role-Playing Games (MMORPGs), auto-leveling bots exploit automated programs to level up characters at scale, undermining gameplay balance and fairness. Detecting such bots is challenging, not only because they mimic human behavior, but also because punitive actions require explainable justification to avoid legal and user experience issues. In this paper, we present a novel framework for detecting auto-leveling bots by leveraging contrastive representation learni…

A functorial approach to $0$-abelian categories
Vitor Gulisz
https://arxiv.org/abs/2509.24810 https://arxiv.org/pdf/2509.24810

A functorial approach to $0$-abelian categories
We use functorial methods to define and study $0$-abelian categories, which we propose to be the case $n = 0$ of Jasso's $n$-abelian categories. In particular, we define a bifunctor for $0$-abelian categories with enough injectives or projectives, which is analogous to the extension bifunctor for an abelian category. We prove a few results concerning this bifunctor, including $0$-abelian versions of the long exact sequence involving the extension bifunctors, of a conjecture due to Auslander on …

Selective Retrieval-Augmentation for Long-Tail Legal Text Classification
Boheng Mao
https://arxiv.org/abs/2508.19997 https://arxiv.org/pdf/2508.19997

Selective Retrieval-Augmentation for Long-Tail Legal Text Classification
Legal text classification is a fundamental NLP task in the legal domain. Benchmark datasets in this area often exhibit a long-tail label distribution, where many labels are underrepresented, leading to poor model performance on rare classes. This paper proposes Selective Retrieval-Augmentation (SRA) as a solution to this problem. SRA focuses on augmenting samples belonging to low-frequency labels in the training set, preventing the introduction of noise for well-represented classes, and require…

Composable Effect Handling for Programming LLM-integrated Scripts
Di Wang
https://arxiv.org/abs/2507.22048 https://arxiv.org/pdf/2507.22048

Composable Effect Handling for Programming LLM-integrated Scripts
Implementing LLM-integrated scripts introduces challenges in modularity and performance, as scripts are often coupled to specific LLM implementations and fail to exploit parallelization opportunities. This paper proposes using composable effect handling to separate workflow logic from effectful operations, such as LLM calls, I/O, and concurrency, enabling modularity without sacrificing the opportunity for performance optimization. By treating these operations as abstract interfaces and discharg…

from my link log —
Stackful coroutines made fast.
https://photonlibos.github.io/blog/stackful-coroutine-made-fast
saved 2025-10-28 htt…

A predictive solution of the EPR paradox
Henryk Gzyl
https://arxiv.org/abs/2508.20788 https://arxiv.org/pdf/2508.20788

A predictive solution of the EPR paradox
In this work an incorrect argument in EPR's paper is corrected. A predictive approach to further confirm the validity of quantum theory is also proposed. The essence of the detail that EPR missed is that in a state of given total momentum (in their example the total momentum is zero), since the total momentum operator $\hat{\bp}=\hat{\bp}_1+\hat{\bp}_2$ does not commute with any of the position operators $\hat{\bx}_1$ and $\hat{\bx}_2,$ then in an eigenstate of the total momentum operator, the …

Security Issues on the OpenPLC project and corresponding solutions
Chaerin Kim
https://arxiv.org/abs/2509.22664 https://arxiv.org/pdf/2509.22664

Security Issues on the OpenPLC project and corresponding solutions
As Programmable Logic Controller (PLC) became a useful device and rose as an interesting research topic but remained expensive, multiple PLC simulators/emulators were introduced for various purposes. Open-source Programmable Logic Controller (OpenPLC) software, one of the most popular PLC simulators, is designed to be vendor-neutral and run on almost any computer or low-cost embedded devices, e.g., Raspberry Pi, Arduino, and other controllers. The project succeeded in introducing itself as an a…

SimShear: Sim-to-Real Shear-based Tactile Servoing
Kipp McAdam Freud, Yijiong Lin, Nathan F. Lepora
https://arxiv.org/abs/2508.20561 https://arxiv.org/pdf/…

SimShear: Sim-to-Real Shear-based Tactile Servoing
We present SimShear, a sim-to-real pipeline for tactile control that enables the use of shear information without explicitly modeling shear dynamics in simulation. Shear, arising from lateral movements across contact surfaces, is critical for tasks involving dynamic object interactions but remains challenging to simulate. To address this, we introduce shPix2pix, a shear-conditioned U-Net GAN that transforms simulated tactile images absent of shear, together with a vector encoding shear informat…

Debiased Front-Door Learners for Heterogeneous Effects
Yonghan Jung
https://arxiv.org/abs/2509.22531 https://arxiv.org/pdf/2509.22531

Debiased Front-Door Learners for Heterogeneous Effects
In observational settings where treatment and outcome share unmeasured confounders but an observed mediator remains unconfounded, the front-door (FD) adjustment identifies causal effects through the mediator. We study the heterogeneous treatment effect (HTE) under FD identification and introduce two debiased learners: FD-DR-Learner and FD-R-Learner. Both attain fast, quasi-oracle rates (i.e., performance comparable to an oracle that knows the nuisances) even when nuisance functions converge as …

GPU-Accelerated Loopy Belief Propagation for Program Analysis
Haoyu Feng, Xin Zhang
https://arxiv.org/abs/2509.22337 https://arxiv.org/pdf/2509.22337

GPU-Accelerated Loopy Belief Propagation for Program Analysis
Loopy Belief Propagation (LBP) is a widely used approximate inference algorithm in probabilistic graphical models, with applications in computer vision, error correction codes, protein folding, program analysis, etc. However, LBP faces significant computational challenges when applied to large-scale program analysis. While GPU (Graphics Processing Unit) parallel computing provides a promising solution, existing approaches lack support for flexible update strategies and have yet to integrate log…

Floor sensors are cheap and easy to use! A Nihon Buyo Case Study
Miho Imai
https://arxiv.org/abs/2508.19261 https://arxiv.org/pdf/2508.19261

Floor sensors are cheap and easy to use! A Nihon Buyo Case Study
As floor-sensing technologies gain traction in movement research, questions remain about their usability and effectiveness for non-expert users. This study presents a case study evaluating Flexel, a modular, low-cost, high-resolution pressure-sensing floor interface, in the context of Nihon Buyo, a traditional Japanese dance. The system was installed, calibrated, and used by a first-time, non-technical user to track weight distribution patterns of a teacher and learner over nine weeks. Live pre…

Growth Forms of Tilings
Peter Hilgers, Anton Shutov
https://arxiv.org/abs/2508.19928 https://arxiv.org/pdf/2508.19928…

Growth Forms of Tilings
The growth form (or corona limit) of a tiling is the limit form of its coordination shells, i.e. its set of tiles located at a fixed distance from some tile. We give an overview of current results, conjectures and open questions about growth forms, including periodic, multigrid, substitution, and hat tilings.

Learning Admissible Heuristics for A*: Theory and Practice
Ehsan Futuhi, Nathan R. Sturtevant
https://arxiv.org/abs/2509.22626 https://arxiv.org/pdf/2509.2…

Learning Admissible Heuristics for A*: Theory and Practice
Heuristic functions are central to the performance of search algorithms such as A-star, where admissibility - the property of never overestimating the true shortest-path cost - guarantees solution optimality. Recent deep learning approaches often disregard admissibility and provide limited guarantees on generalization beyond the training data. This paper addresses both of these limitations. First, we pose heuristic learning as a constrained optimization problem and introduce Cross-Entropy Admis…

Axiomatic Choice and the Decision-Evaluation Paradox
Ben Abramowitz, Nicholas Mattei
https://arxiv.org/abs/2509.21836 https://arxiv.org/pdf/2509.21836

Axiomatic Choice and the Decision-Evaluation Paradox
We introduce a framework for modeling decisions with axioms that are statements about decisions, e.g., ethical constraints. Using our framework we define a taxonomy of decision axioms based on their structural properties and demonstrate a tension between the use of axioms to make decisions and the use of axioms to evaluate decisions which we call the Decision-Evaluation Paradox. We argue that the Decision-Evaluation Paradox arises with realistic axiom structures, and the paradox illuminates why…

Double Categories of Open Systems: the Cospan Approach
John C. Baez
https://arxiv.org/abs/2509.22584 https://arxiv.org/pdf/2509.22584

Double Categories of Open Systems: the Cospan Approach
This is an overview of double categories of "open systems": systems that can interact with their environment. We focus on the variable sharing paradigm, where we compose open systems by identifying variables. This paradigm is often implemented using structured or decorated cospans. We explain this approach using three main examples: open Petri nets, open dynamical systems, and open Petri nets with rates. We compare the virtues of structured and decorated cospan double categories, and study thei…

Representing LLMs in Prompt Semantic Task Space
Idan Kashani, Avi Mendelson, Yaniv Nemcovsky
https://arxiv.org/abs/2509.22506 https://arxiv.org/pdf/2509.22…

Representing LLMs in Prompt Semantic Task Space
Large language models (LLMs) achieve impressive results over various tasks, and ever-expanding public repositories contain an abundance of pre-trained models. Therefore, identifying the best-performing LLM for a given task is a significant challenge. Previous works have suggested learning LLM representations to address this. However, these approaches present limited scalability and require costly retraining to encompass additional models and datasets. Moreover, the produced representation utili…

One Weird Trick to Untie Landin's Knot
Paulette Koronkevich, William J. Bowman
https://arxiv.org/abs/2507.21317 https://arxiv.org/pdf/2507.21317…

One Weird Trick to Untie Landin's Knot
In this work, we explore Landin's Knot, which is understood as a pattern for encoding general recursion, including non-termination, that is possible after adding higher-order references to an otherwise terminating language. We observe that this isn't always true -- higher-order references, by themselves, don't lead to non-termination. The key insight is that Landin's Knot relies not primarily on references storing functions, but on unrestricted quantification over a function's environment. We s…

Simultaneous Quantization and Reduction of Constrained Systems
Jianhao M. Yang
https://arxiv.org/abs/2509.22747 https://arxiv.org/pdf/2509.22747

Simultaneous Quantization and Reduction of Constrained Systems
We present a novel framework for quantizing constrained quantum systems in which the processes of quantization and constraint enforcement are performed simultaneously. The approach is based on an extension of the stationary action principle, incorporating an information-theoretic term arising from vacuum fluctuations. Constraints are included directly in the Lagrangian via Lagrange multipliers, allowing the subsequent variational procedure to yield the quantum dynamics without ambiguity regardi…

AI Propaganda factories with language models
Lukasz Olejnik
https://arxiv.org/abs/2508.20186 https://arxiv.org/pdf/2508.20186

AI Propaganda factories with language models
AI-powered influence operations can now be executed end-to-end on commodity hardware. We show that small language models produce coherent, persona-driven political messaging and can be evaluated automatically without human raters. Two behavioural findings emerge. First, persona-over-model: persona design explains behaviour more than model identity. Second, engagement as a stressor: when replies must counter-arguments, ideological adherence strengthens and the prevalence of extreme content incre…

Diffusion Denoiser-Aided Gyrocompassing
Gershy Ben-Arie, Daniel Engelsman, Rotem Dror, Itzik Klein
https://arxiv.org/abs/2507.21245 https://arxiv.org/pdf/2…

Diffusion Denoiser-Aided Gyrocompassing
An accurate initial heading angle is essential for efficient and safe navigation across diverse domains. Unlike magnetometers, gyroscopes can provide accurate heading reference independent of the magnetic disturbances in a process known as gyrocompassing. Yet, accurate and timely gyrocompassing, using low-cost gyroscopes, remains a significant challenge in scenarios where external navigation aids are unavailable. Such challenges are commonly addressed in real-world applications such as autonomo…

Variance-Bounded Evaluation without Ground Truth: VB-Score
Kaihua Ding
https://arxiv.org/abs/2509.22751 https://arxiv.org/pdf/2509.22751

Variance-Bounded Evaluation without Ground Truth: VB-Score
Reliable evaluation is a central challenge in machine learning when tasks lack ground truth labels or involve ambiguity and noise. Conventional frameworks, rooted in the Cranfield paradigm and label-based metrics, fail in such cases because they cannot assess how robustly a system performs under uncertain interpretations. We introduce VB-Score, a variance-bounded evaluation framework that measures both effectiveness and robustness without requiring ground truth. Given a query or input, VB-Score…

Towards a fundamental theory of modeling discrete systems
Peter Fettke, Wolfgang Reisig
https://arxiv.org/abs/2508.19803 https://arxiv.org/pdf/2508.19803…

Towards a fundamental theory of modeling discrete systems
Modeling is a central concern in both science and engineering. However, we need a new fundamental theory to address the challenges of the digital age. In this paper, we first explain why modeling is fundamental and which challenges must be addressed in the digital world. As a main contribution, we introduce the Heraklit modeling framework as a new approach to modeling. We conclude with some general remarks. Future work will involve the correctness of modeling, the notion of information, and the…

A Theory of Information, Variation, and Artificial Intelligence
Bijean Ghafouri
https://arxiv.org/abs/2508.19264 https://arxiv.org/pdf/2508.19264

A Theory of Information, Variation, and Artificial Intelligence
A growing body of empirical work suggests that the widespread adoption of generative AI produces a significant homogenizing effect on information, creativity, and cultural production. I first develop a novel theoretical framework to explain this phenomenon. I argue that a dynamic of AI-derivative epistemology, in which individuals increasingly defer to AI outputs, allows a centralized AI Prism to function, a technical mechanism whose architecture is designed to reduce variance and converge on t…

Computer-assisted graph theory: a survey
Jorik Jooken
https://arxiv.org/abs/2508.20825 https://arxiv.org/pdf/2508.20825

Computer-assisted graph theory: a survey
Computers and algorithms play an ever-increasing role in obtaining new results in graph theory. In this survey, we present a broad range of techniques used in computer-assisted graph theory, including the exhaustive generation of all pairwise non-isomorphic graphs within a given class, the use of searchable databases containing graphs and invariants as well as other established and emerging algorithmic paradigms. We cover approaches based on mixed integer linear programming, semidefinite progra…

OFMU: Optimization-Driven Framework for Machine Unlearning
Sadia Asif, Mohammad Mohammadi Amiri
https://arxiv.org/abs/2509.22483 https://arxiv.org/pdf/2509…

OFMU: Optimization-Driven Framework for Machine Unlearning
Large language models deployed in sensitive applications increasingly require the ability to unlearn specific knowledge, such as user requests, copyrighted materials, or outdated information, without retraining from scratch to ensure regulatory compliance, user privacy, and safety. This task, known as machine unlearning, aims to remove the influence of targeted data (forgetting) while maintaining performance on the remaining data (retention). A common approach is to formulate this as a multi-ob…

TRACE: Learning to Compute on Graphs
Ziyang Zheng, Jiaying Zhu, Jingyi Zhou, Qiang Xu
https://arxiv.org/abs/2509.21886 https://arxiv.org/pdf/2509.21886

TRACE: Learning to Compute on Graphs
Learning to compute, the ability to model the functional behavior of a computational graph, is a fundamental challenge for graph representation learning. Yet, the dominant paradigm is architecturally mismatched for this task. This flawed assumption, central to mainstream message passing neural networks (MPNNs) and their conventional Transformer-based counterparts, prevents models from capturing the position-aware, hierarchical nature of computation. To resolve this, we introduce \textbf{TRACE},…

Parametric Distributive Laws: uniform monad composition
Lorenzo Perticone
https://arxiv.org/abs/2509.22208 https://arxiv.org/pdf/2509.22208

Parametric Distributive Laws: uniform monad composition
Monads play an important role in both the syntax and semantics of modern functional programming languages. The problem of combining them has been of profound interest at least since the 90s, and different approaches have been employed to tackle it: currently, the most prevalent notion is that of monad transformers. We provide a novel abstract framework to describe such "compositions" which we call parametric distributive laws. Our description of this framework hinges on the theory of 2-categori…

Transformers Can Learn Connectivity in Some Graphs but Not Others
Amit Roy, Abulhair Saparov
https://arxiv.org/abs/2509.22343 https://arxiv.org/pdf/2509.22…

Transformers Can Learn Connectivity in Some Graphs but Not Others
Reasoning capability is essential to ensure the factual correctness of the responses of transformer-based Large Language Models (LLMs), and robust reasoning about transitive relations is instrumental in many settings, such as causal inference. Hence, it is essential to investigate the capability of transformers in the task of inferring transitive relations (e.g., knowing A causes B and B causes C, then A causes C). The task of inferring transitive relations is equivalent to the task of connecti…

Noise-Resilient Quantum Reinforcement Learning
Jing-Ci Yue, Jun-Hong An
https://arxiv.org/abs/2508.20601 https://arxiv.org/pdf/2508.20601

Noise-Resilient Quantum Reinforcement Learning
As a branch of quantum machine learning, quantum reinforcement learning (QRL) aims to solve complex sequential decision-making problems more efficiently and effectively than its classical counterpart by exploiting quantum resources. However, in the noisy intermediate-scale quantum (NISQ) era, its realization is challenged by the ubiquitous noise-induced decoherence. Here, we propose a noise-resilient QRL scheme for a quantum eigensolver. By investigating the non-Markovian decoherence effect on …

Security Friction Quotient for Zero Trust Identity Policy with Empirical Validation
Michel Youssef
https://arxiv.org/abs/2509.22663 https://arxiv.org/pdf/2…

Security Friction Quotient for Zero Trust Identity Policy with Empirical Validation
We define a practical method to quantify the trade-off between security and operational friction in modern identity-centric programs. We introduce the Security Friction Quotient (SFQ), a bounded composite index that combines a residual-risk estimator with empirically grounded friction terms (latency, failure rate, and helpdesk impact). We establish clarity properties (boundedness, monotonic response, and weight identifiability) with short proofs, then evaluate widely used Conditional Access pol…

General Pruning Criteria for Fast SBL
Jakob M\"oderl, Erik Leitinger, Bernard Henri Fleury
https://arxiv.org/abs/2509.21572 https://arxiv.org/pdf/2509…

General Pruning Criteria for Fast SBL
Sparse Bayesian learning (SBL) associates to each weight in the underlying linear model a hyperparameter by assuming that each weight is Gaussian distributed with zero mean and precision (inverse variance) equal to its associated hyperparameter. The method estimates the hyperparameters by marginalizing out the weights and performing (marginalized) maximum likelihood (ML) estimation. SBL returns many hyperparameter estimates to diverge to infinity, effectively setting the estimates of the corres…

What is "Spatial" about Spatial Computing?
Yibo Wang, Yuhan Luo, Janghee Cho, Junnan Yu
https://arxiv.org/abs/2508.20477 https://arxiv.org/pdf/25…

What is "Spatial" about Spatial Computing?
Recent advancements in geographic information systems and mixed reality technologies have positioned spatial computing as a transformative paradigm in computational science. However, the field remains conceptually fragmented, with diverse interpretations across disciplines like Human-Computer Interaction, Geographic Information Science, and Computer Science, which hinders a comprehensive understanding of spatial computing and poses challenges for its coherent advancement and interdisciplinary i…

Learning from Delayed Feedback in Games via Extra Prediction
Yuma Fujimoto, Kenshi Abe, Kaito Ariu
https://arxiv.org/abs/2509.22426 https://arxiv.org/pdf/2…

Learning from Delayed Feedback in Games via Extra Prediction
This study raises and addresses the problem of time-delayed feedback in learning in games. Because learning in games assumes that multiple agents independently learn their strategies, a discrepancy in optimization often emerges among the agents. To overcome this discrepancy, the prediction of the future reward is incorporated into algorithms, typically known as Optimistic Follow-the-Regularized-Leader (OFTRL). However, the time delay in observing the past rewards hinders the prediction. Indeed,…

Uniform Tur\'an density beyond 3-graphs
Ander Lamaison
https://arxiv.org/abs/2508.20696 https://arxiv.org/pdf/2508.20696…

Uniform Turán density beyond 3-graphs
In the 1980s, Erdős and Sós first introduced an extremal problem on hypergraphs with density constraints. Given an $r$-uniform hypergraph $F$ (or $r$-graph for short), its uniform Turán density $π_u(F)$ is the smallest value of $d$ in which every hypergraph $H$ in which every linear-sized subhypergraph of $H$ has edge density at least $d$ contains $F$ as a subgraph. The first non-zero value of $π_u(F)$ was not found until 30 years later. Progress in studying the set of values of the unif…

Array-Based Monte Carlo Tree Search
James Ragan, Fred Y. Hadaegh, Soon-Jo Chung
https://arxiv.org/abs/2508.20140 https://arxiv.org/pdf/2508.20140

Array-Based Monte Carlo Tree Search
Monte Carlo Tree Search is a popular method for solving decision making problems. Faster implementations allow for more simulations within the same wall clock time, directly improving search performance. To this end, we present an alternative array-based implementation of the classic Upper Confidence bounds applied to Trees algorithm. Our method preserves the logic of the original algorithm, but eliminates the need for branch prediction, enabling faster performance on pipelined processors, and …

Survey of Specialized Large Language Model
Chenghan Yang, Ruiyu Zhao, Yang Liu, Ling Jiang
https://arxiv.org/abs/2508.19667 https://arxiv.org/pdf/2508.1966…

Survey of Specialized Large Language Model
The rapid evolution of specialized large language models (LLMs) has transitioned from simple domain adaptation to sophisticated native architectures, marking a paradigm shift in AI development. This survey systematically examines this progression across healthcare, finance, legal, and technical domains. Besides the wide use of specialized LLMs, technical breakthrough such as the emergence of domain-native designs beyond fine-tuning, growing emphasis on parameter efficiency through sparse comput…

Symmetric monoidal extensions and graph cobordisms between finite sets
Andrea Bianchi
https://arxiv.org/abs/2509.22575 https://arxiv.org/pdf/2509.22575

Symmetric monoidal extensions and graph cobordisms between finite sets
Given a symmetric monoidal $(\infty,n)$-category $\mathcal{C}$ and a space $X$, we address the problem of explicitly describing the symmetric monoidal $(\infty,n)$-category freely obtained from $\mathcal{C}$ by adjoining $X$ new $n$-morphisms with prescribed sources and targets. We develop an apparatus of tools that allow one to detect in concrete situations such a free symmetric monoidal extension. As motivating application, we introduce a symmetric monoidal $(\infty,2)$-category ${\mathbb{G}\…

On a discrete version of the position-momentum commutation relation
Nicolae Cotfas
https://arxiv.org/abs/2509.22753 https://arxiv.org/pdf/2509.22753…

On a discrete version of the position-momentum commutation relation
The usual position-momentum commutation relation plays a fundamental role in the mathematical description of continuous-variable quantum systems. In the case of a qudit described by a Hilbert space of a high enough dimension, there exists a discrete version of the position-momentum commutation relation approximately satisfied by a large part of the pure quantum states. Our purpose is to explore in more details the set of these states. We show that it contains a family of discrete-variable Gauss…

Multi-Agent Penetration Testing AI for the Web
Isaac David, Arthur Gervais
https://arxiv.org/abs/2508.20816 https://arxiv.org/pdf/2508.20816

Multi-Agent Penetration Testing AI for the Web
AI-powered development platforms are making software creation accessible to a broader audience, but this democratization has triggered a scalability crisis in security auditing. With studies showing that up to 40% of AI-generated code contains vulnerabilities, the pace of development now vastly outstrips the capacity for thorough security assessment. We present MAPTA, a multi-agent system for autonomous web application security assessment that combines large language model orchestration with …

Metrics for Parametric Families of Networks
Mario G\'omez, Guanqun Ma, Tom Needham, Bei Wang
https://arxiv.org/abs/2509.22549 https://arxiv.org/pdf/250…

Metrics for Parametric Families of Networks
We introduce a general framework for analyzing data modeled as parameterized families of networks. Building on a Gromov-Wasserstein variant of optimal transport, we define a family of parameterized Gromov-Wasserstein distances for comparing such parametric data, including time-varying metric spaces induced by collective motion, temporally evolving weighted social networks, and random graph models. We establish foundational properties of these distances, showing that they subsume several existin…

Neural Feature Geometry Evolves as Discrete Ricci Flow
Moritz Hehl, Max von Renesse, Melanie Weber
https://arxiv.org/abs/2509.22362 https://arxiv.org/pdf/2…

Neural Feature Geometry Evolves as Discrete Ricci Flow
Deep neural networks learn feature representations via complex geometric transformations of the input data manifold. Despite the models' empirical success across domains, our understanding of neural feature representations is still incomplete. In this work we investigate neural feature geometry through the lens of discrete geometry. Since the input data manifold is typically unobserved, we approximate it using geometric graphs that encode local similarity structure. We provide theoretical resul…

Single Agent Robust Deep Reinforcement Learning for Bus Fleet Control
Yifan Zhang
https://arxiv.org/abs/2508.20784 https://arxiv.org/pdf/2508.20784

Single Agent Robust Deep Reinforcement Learning for Bus Fleet Control
Bus bunching remains a challenge for urban transit due to stochastic traffic and passenger demand. Traditional solutions rely on multi-agent reinforcement learning (MARL) in loop-line settings, which overlook realistic operations characterized by heterogeneous routes, timetables, fluctuating demand, and varying fleet sizes. We propose a novel single-agent reinforcement learning (RL) framework for bus holding control that avoids the data imbalance and convergence issues of MARL under near-realis…

Data-Driven and Participatory Approaches toward Neuro-Inclusive AI
Naba Rizvi
https://arxiv.org/abs/2507.21077 https://arxiv.org/pdf/2507.21077

Data-Driven and Participatory Approaches toward Neuro-Inclusive AI
Biased data representation in AI marginalizes up to 75 million autistic people worldwide through medical applications viewing autism as a deficit of neurotypical social skills rather than an aspect of human diversity, and this perspective is grounded in research questioning the humanity of autistic people. Turing defined artificial intelligence as the ability to mimic human communication, and as AI development increasingly focuses on human-like agents, this benchmark remains popular. In contras…

On Generalized Rickart $*$-rings
Anil Khairnar, Sanjay More
https://arxiv.org/abs/2508.20842 https://arxiv.org/pdf/2508.20842

On Generalized Rickart $*$-rings
A ring $R$ with an involution $*$ is a generalized Rickart $*$-ring if for all $x\in R$ the right annihilator of $x^n$ is generated by a projection for some positive integer $n$ depending on $x$. In this work, we introduce generalized right projection of an element in a $*$-ring and prove that every element in a generalized Rickart $*$-ring has generalized right projection. Various characterizations of generalized Rickart $*$-rings are obtained. We introduce the concept of generalized weakly Ri…

Adaptive Federated Distillation for Multi-Domain Non-IID Textual Data
Jiahao Xiao, Jiangming Liu
https://arxiv.org/abs/2508.20557 https://arxiv.org/pdf/250…

Adaptive Federated Distillation for Multi-Domain Non-IID Textual Data
The widespread success of pre-trained language models has established a new training paradigm, where a global PLM is fine-tuned using task-specific data from local clients. The local data are highly different from each other and can not capture the global distribution of the whole data in real world. To address the challenges of non-IID data in real environments, privacy-preserving federated distillation has been proposed and highly investigated. However, previous experimental non-IID scenarios…

Physical constraints on effective non-Hermitian systems
Aaron Kleger, Rufus Boyack
https://arxiv.org/abs/2508.21067 https://arxiv.org/pdf/2508.21067…

Physical constraints on effective non-Hermitian systems
Interacting and open quantum systems can be formulated in terms of an effective non-Hermitian Hamiltonian (NHH), however, there are important constraints that must be satisfied by the effective action and the associated Green's functions. One common approach to many-body non-Hermitian (NH) systems is to incorporate the anti-Hermitian part of the Hamiltonian directly in the Matsubara Green's function. Here, we show that such an approach is incompatible with the standard framework for systems wit…

An Investigation on Group Query Hallucination Attacks
Kehao Miao, Xiaolong Jin
https://arxiv.org/abs/2508.19321 https://arxiv.org/pdf/2508.19321

An Investigation on Group Query Hallucination Attacks
With the widespread use of large language models (LLMs), understanding their potential failure modes during user interactions is essential. In practice, users often pose multiple questions in a single conversation with LLMs. Therefore, in this study, we propose Group Query Attack, a technique that simulates this scenario by presenting groups of queries to LLMs simultaneously. We investigate how the accumulated context from consecutive prompts influences the outputs of LLMs. Specifically, we obs…

SpinGPT: A Large-Language-Model Approach to Playing Poker Correctly
Narada Maugin, Tristan Cazenave
https://arxiv.org/abs/2509.22387 https://arxiv.org/pdf/…

SpinGPT: A Large-Language-Model Approach to Playing Poker Correctly
The Counterfactual Regret Minimization (CFR) algorithm and its variants have enabled the development of pokerbots capable of beating the best human players in heads-up (1v1) cash games and competing with them in six-player formats. However, CFR's computational complexity rises exponentially with the number of players. Furthermore, in games with three or more players, following Nash equilibrium no longer guarantees a non-losing outcome. These limitations, along with others, significantly restric…

Estimating the Empowerment of Language Model Agents
Jinyeop Song, Jeff Gore, Max Kleiman-Weiner
https://arxiv.org/abs/2509.22504 https://arxiv.org/pdf/2509…

Estimating the Empowerment of Language Model Agents
As language model (LM) agents become more capable and gain broader access to real-world tools, there is a growing need for scalable evaluation frameworks of agentic capability. However, conventional benchmark-centric evaluations are costly to design and require human designers to come up with valid tasks that translate into insights about general model capabilities. In this work, we propose information-theoretic evaluation based on empowerment, the mutual information between an agent's actions …

IndiSeek learns information-guided disentangled representations
Yu Gui, Cong Ma, Zongming Ma
https://arxiv.org/abs/2509.21584 https://arxiv.org/pdf/2509.21…

IndiSeek learns information-guided disentangled representations
Learning disentangled representations is a fundamental task in multi-modal learning. In modern applications such as single-cell multi-omics, both shared and modality-specific features are critical for characterizing cell states and supporting downstream analyses. Ideally, modality-specific features should be independent of shared ones while also capturing all complementary information within each modality. This tradeoff is naturally expressed through information-theoretic criteria, but mutual-i…

Curves in projective space and RSK
Carl Lian, Saskia Solotko
https://arxiv.org/abs/2508.19503 https://arxiv.org/pdf/2508.19503

Curves in projective space and RSK
The geometric Tevelev degrees of projective space enumerate general, pointed algebraic curves interpolating through the maximal possible number of points. Previous work expresses these invariants in terms of Schubert calculus. Extending ideas of Gillespie--Reimer-Berg, we use the RSK correspondence to give a positive interpretation of these counts in terms of the combinatorics of words.

BiListing: Modality Alignment for Listings
Guillaume Guy, Mihajlo Grbovic, Chun How Tan, Han Zhao
https://arxiv.org/abs/2508.20396 https://arxiv.org/pdf/25…

BiListing: Modality Alignment for Listings
Airbnb is a leader in offering travel accommodations. Airbnb has historically relied on structured data to understand, rank, and recommend listings to guests due to the limited capabilities and associated complexity arising from extracting meaningful information from text and images. With the rise of representation learning, leveraging rich information from text and photos has become easier. A popular approach has been to create embeddings for text documents and images to enable use cases of co…

Any gate of a quantum computer can be certified device-independently
Shubhayan Sarkar
https://arxiv.org/abs/2508.20185 https://arxiv.org/pdf/2508.20185

Any gate of a quantum computer can be certified device-independently
Device-independent (DI) certification allows the verification of quantum systems based solely on observed statistics, without assumptions about their internal structure. While self-testing, the strongest DI certification, of a wide range of quantum states and measurements is done, the self-testing of quantum operations remains underdeveloped. Here, we show in a proof-of-principle way that any quantum unitary can be self-tested within the DI paradigm. For our purpose, we utilise the framework of…

A Graph-Based Test-Harness for LLM Evaluation
Jessica Lundin, Guillaume Chabot-Couture
https://arxiv.org/abs/2508.20810 https://arxiv.org/pdf/2508.20810

A Graph-Based Test-Harness for LLM Evaluation
We present a first known prototype of a dynamic, systematic benchmark of medical guidelines for 400+ questions, with 3.3+ trillion possible combinations, covering 100\% of guideline relationships. We transformed the WHO IMCI handbook into a directed graph with 200+ nodes (conditions, symptoms, treatments, follow-ups, severities) and 300+ edges, then used graph traversal to generate questions that incorporated age-specific scenarios and contextual distractors to ensure clinical relevance. Our gr…

Publish to Perish: Prompt Injection Attacks on LLM-Assisted Peer Review
Matteo Gioele Collu, Umberto Salviati, Roberto Confalonieri, Mauro Conti, Giovanni Apruzzese
https://arxiv.org/abs/2508.20863

Publish to Perish: Prompt Injection Attacks on LLM-Assisted Peer Review
Large Language Models (LLMs) are increasingly being integrated into the scientific peer-review process, raising new questions about their reliability and resilience to manipulation. In this work, we investigate the potential for hidden prompt injection attacks, where authors embed adversarial text within a paper's PDF to influence the LLM-generated review. We begin by formalising three distinct threat models that envision attackers with different motivations -- not all of which implying malicio…

Sequential 1-bit Mean Estimation with Near-Optimal Sample Complexity
Ivan Lau, Jonathan Scarlett
https://arxiv.org/abs/2509.21940 https://arxiv.org/pdf/250…

Sequential 1-bit Mean Estimation with Near-Optimal Sample Complexity
In this paper, we study the problem of distributed mean estimation with 1-bit communication constraints. We propose a mean estimator that is based on (randomized and sequentially-chosen) interval queries, whose 1-bit outcome indicates whether the given sample lies in the specified interval. Our estimator is $(ε, δ)$-PAC for all distributions with bounded mean ($-λ\le \mathbb{E}(X) \le λ$) and variance ($\mathrm{Var}(X) \le σ^2$) for some known parameters $λ$ and $σ$. We derive a sample c…

On the chromatic numbers of Johnson type graphs
Danila Cherkashin
https://arxiv.org/abs/2508.19775 https://arxiv.org/pdf/2508.19775

On the chromatic numbers of Johnson type graphs
A Johnson type graph $J_{\pm}(n,k,t)$ is a graph whose vertex set consists of vectors from $\{-1,0,1\}^n$ of the length $\sqrt{k}$ and edges connect vertices with scalar product $t$. The paper determines the order of growth of the chromatic numbers of graphs $J_\pm(n,2,-1)$ and $J_\pm(n,3,-1)$ (logarithmic on $n$), and also $J_\pm(n,3,-2)$ (double logarithmic on $n$).

AI reasoning effort mirrors human decision time on content moderation tasks
Thomas Davidson
https://arxiv.org/abs/2508.20262 https://arxiv.org/pdf/2508.202…

AI reasoning effort mirrors human decision time on content moderation tasks
Large language models can now generate intermediate reasoning steps before producing answers, improving performance on difficult problems. This study uses a paired conjoint experiment on a content moderation task to examine parallels between human decision times and model reasoning effort. Across three frontier models, reasoning effort consistently predicts human decision time. Both humans and models expended greater effort when important variables were held constant, suggesting similar sensiti…

Non-spatial symmetries in quantum nonlinear spectroscopy
Li Sun, Chong Chen, Ren-Bao Liu
https://arxiv.org/abs/2508.20445 https://arxiv.org/pdf/2508.20445

Non-spatial symmetries in quantum nonlinear spectroscopy
Nonlinear spectroscopy is a powerful approach to extracting information, in particular higher-order correlations of physical quantities. Quantum nonlinear spectroscopy (QNS) can access exponentially more types of correlations than its classical counterpart, since the responses to ``classical forces'' correspond to contour-time-ordered correlations (CTOCs) that involve only commutators, while in QNS ``quantum forces'' from a quantum sensor induce responses corresponding to CTOCs that involve bot…

Stochastic Gradients under Nuisances
Facheng Yu, Ronak Mehta, Alex Luedtke, Zaid Harchaoui
https://arxiv.org/abs/2508.20326 https://arxiv.org/pdf/2508.2032…

Stochastic Gradients under Nuisances
Stochastic gradient optimization is the dominant learning paradigm for a variety of scenarios, from classical supervised learning to modern self-supervised learning. We consider stochastic gradient algorithms for learning problems whose objectives rely on unknown nuisance parameters, and establish non-asymptotic convergence guarantees. Our results show that, while the presence of a nuisance can alter the optimum and upset the optimization trajectory, the classical stochastic gradient algorithm …

The incidence matrix of a $q$-ary graph
Michela Ceria, Relinde Jurrius
https://arxiv.org/abs/2508.19964 https://arxiv.org/pdf/2508.19964

The incidence matrix of a $q$-ary graph
In this short note we will propose a definition of a $q$-ary graph. Furthermore, we describe how to make an incidence matrix for it, with an eye on the corresponding $q$-matroid.

Engineering Non-Gaussian Bosonic Gates through Quantum Signal Processing
Pak-Tik Fong, Hoi-Kwan Lau
https://arxiv.org/abs/2508.20261 https://arxiv.org/pdf/…

Engineering Non-Gaussian Bosonic Gates through Quantum Signal Processing
Non-Gaussian operations are essential for most bosonic quantum technologies. Yet, realizable non-Gaussian gates are rather limited in type and generally suffer from accuracy-duration trade-offs. In this work, we propose to use quantum signal processing (QSP) techniques to engineer non-Gaussian gates on hybrid qumode-qubit systems. For systems with dispersive coupling, our scheme can generate a new non-Gaussian gate that produces a phase shift depending on the modulus of the boson number. This g…

Effective Asymptotics of Combinatorial Systems
Carine Pivoteau, Bruno Salvy
https://arxiv.org/abs/2508.20008 https://arxiv.org/pdf/2508.20008

Effective Asymptotics of Combinatorial Systems
Analytic combinatorics studies asymptotic properties of families of combinatorial objects using complex analysis on their generating functions. In their reference book on the subject, Flajolet and Sedgewick describe a general approach that allows one to derive precise asymptotic expansions starting from systems of combinatorial equations. In the situation where the combinatorial system involves only cartesian products and disjoint unions, the generating functions satisfy polynomial systems with…

Majority Edge Colouring of Hypergraph
Jiangdong Ai, Feiyu Nan
https://arxiv.org/abs/2509.22157 https://arxiv.org/pdf/2509.22157

Majority Edge Colouring of Hypergraph
Let G = (V, E) be a hypergraph. A 1/k-majority (k+1)-edge-colouring of a hypergraph is an edge-colouring with k+1 colours such that for every vertex v and each colour i, at most floor(d(v)/k) hyperedges incident to v receive colour i. Motivated by a recent work of Pękała and Przybyło on majority edge-colouring in graphs, we prove that every hypergraph G with minimum degree delta(G) >= 2 r k^2 admits a 1/k-majority (k+1)-edge-colouring, where r = max_{e in E} |e|, by extending their…

Edge-connectivity and non-negative Lin-Lu-Yau curvature
Shiping Liu, Qing Xia
https://arxiv.org/abs/2508.20950 https://arxiv.org/pdf/2508.20950

Edge-connectivity and non-negative Lin-Lu-Yau curvature
By definition, the edge-connectivity of a connected graph is no larger than its minimum degree. In this paper, we prove that the edge connectivity of a finite connected graph with non-negative Lin-Lu-Yau curvature is equal to its minimum degree. This answers an open question of Chen, Liu and You. Notice that our conclusion would be false if we did not require the graph to be finite. We actually classify all connected graphs with non-negative Lin-Lu-Yau curvature and edge-connectivity smaller th…

Positroidal aspects of non-nesting rook placements
Aryaman Jal
https://arxiv.org/abs/2509.21626 https://arxiv.org/pdf/2509.21626

Positroidal aspects of non-nesting rook placements
Rook matroids were recently introduced by the author and Alexandersson as matroids whose bases arise from certain restricted rook placements on a skew-shaped board. They were shown to be a subclass of transversal matroids and positroids. We further investigate the structural properties of rook matroids with an emphasis on the positroidal point of view. In particular, we characterize rook matroids in terms of Grassmann necklaces of positroids, answering a question of Lam (2024). Along the way, w…

Visibility Polynomial of Some Graph Classes
Tonny K B, Shikhi M
https://arxiv.org/abs/2509.22571 https://arxiv.org/pdf/2509.22571

Visibility Polynomial of Some Graph Classes
Mutual visibility in graphs provides a framework for analysing how vertices can observe one another along shortest paths free of internal obstructions. The visibility polynomial, which enumerates mutual-visibility sets of all orders, has emerged as a central invariant in this study, with both theoretical significance and practical relevance in areas such as surveillance, target tracking, and distributed coordination. While computing this polynomial is computationally demanding, with known compl…

Three Generalizations of Erd\H{o}s Szekeres: $k$-Modal Subsequences
Charles Gong
https://arxiv.org/abs/2508.20360 https://arxiv.org/pdf/2508.20360

Three Generalizations of Erdős Szekeres: $k$-Modal Subsequences
Erdős and Szekeres showed that given a permutation $p$ of $[n]$, and the sequence defined by \newline $(p(1), p(2), \ldots, p(n))$, there exists either a decreasing or increasing subsequence, not necessarily contiguous, of length at least $\sqrt{n}$. Fan Chung considered subsequences that can have at most one change of direction, i.e. an increasing and then decreasing subsequence, or a decreasing and then increasing subsequence. She called these unimodal subsequences, and showed there exists a…

Cubic vertex-transitive graphs of girth seven
Maru\v{s}a Lek\v{s}e, Micael Toledo
https://arxiv.org/abs/2508.19880 https://arxiv.org/pdf/2508.19880

Cubic vertex-transitive graphs of girth seven
In this paper we classify cubic vertex-transitive graphs of girth $7$, based on their signature. Such a graph is either a truncation of an arc-transitive dihedral scheme on a $7$-regular graph, the skeleton of a rotary map of type $\{7,3\}$, a member of an infinite family of Cayley graphs, or is one of the of the generalised Petersen graphs $\text{Pet}(13,5)$, $\text{Pet}(15,4)$, $\text{Pet}(17,4)$ or the Coxeter graph. We show that for a cubic vertex-transitive graphs $Γ$ of girth $7$, if eve…

Limit spaces of vertex and edge replacement systems
Davide Perego, Matteo Tarocchi
https://arxiv.org/abs/2508.20739 https://arxiv.org/pdf/2508.20739…

Limit spaces of vertex and edge replacement systems
We introduce and study VERSs (vertex and edge replacement systems) as a technology of graph expansions. We consider its history graph, an augmented tree that records each graph expansion, and we provide sufficient conditions under which it is hyperbolic. When hyperbolic, its Gromov boundary is what we call the limit space of the VERS. We provide three examples from different areas of mathematics: Schreier graphs and limit spaces of finitely generated contracting self-similar groups, injective p…

A weak regularity lemma for polynomials
Guy Moshkovitz, Dora Woodruff
https://arxiv.org/abs/2509.21536 https://arxiv.org/pdf/2509.21536

A weak regularity lemma for polynomials
A regularity lemma for polynomials provides a decomposition in terms of a bounded number of approximately independent polynomials. Such regularity lemmas play an important role in numerous results, yet suffer from the familiar shortcoming of having tower-type bounds or worse. In this paper we design a new, weaker regularity lemma with strong bounds. The new regularity lemma in particular provides means to quantitatively study the curves contained in the image of a polynomial map, which is beyon…

Most frequent subsequences in a word
Boris Bukh, Aleksandre Saatashvili
https://arxiv.org/abs/2509.22619 https://arxiv.org/pdf/2509.22619

Most frequent subsequences in a word
We prove that every $n$-letter word over $k$-letter alphabet contains some word as a subsequence in at least $k^{n/4k(1+o(1))}$ many ways, and that this is sharp as $k\to\infty$. For fixed $k$, we show that the analogous number deviates from $μ_k^n$, for some constant $μ_k$, by a factor of at most $n$.

Tur\'an's theorem for Dowling geometries
Rutger Campbell, Donggyu Kim, Jorn van der Pol
https://arxiv.org/abs/2508.20843 https://arxiv.org/pdf/2508…

Turán's theorem for Dowling geometries
The Dowling geometry $Q_n(Γ)$, where $Γ$ is a finite group, is a matroid that generalizes the complete-graphic matroid $M(K_{n+1})$. We determine the maximum size of an $N$-free submatroid of $Q_n(Γ)$ for various choices of $N$, including subgeometries $Q_m(Γ')$, lines $U_{2,\ell}$, and graphic matroids $M(H)$. When the group $Γ$ is trivial and $N=M(K_t)$, this problem reduces to Turán's classical result in extremal graph theory. We show that when $Γ$ is nontrivial, a complex dependence …

On the Precise Asymptotics of $ex(n,n,n,K_{2,t})$ for even $t$
Zilin Luo
https://arxiv.org/abs/2509.21756 https://arxiv.org/pdf/2509.21756

On the Precise Asymptotics of $ex(n,n,n,K_{2,t})$ for even $t$
Let $K_{2,t}$ denote the complete bipartite graph. For an integer $n\ge 1$, let $ex(n,n,n,K_{2,t})$ be the maximum number of edges in an $n\times n\times n$ tripartite graph (that is, a 3-partite graph with three parts each of size $n$) containing no copy of $K_{2,t}$. In this paper we prove that, for even $t\ge 2$, $$ ex(n,n,n,K_{2,t}) \ge \frac{3\sqrt{t-1}}{\sqrt{2}}\, n^{3/2} + o(n^{3/2}). $$ Combining our construction with earlier work of Tait and Timmons, we obtain $$ \lim\limits_{n\to\inf…

Chromatic quasisymmetric functions for signed graphs
Jean-Christophe Aval, Raquel Melgar
https://arxiv.org/abs/2508.20200 https://arxiv.org/pdf/2508.20200

Chromatic quasisymmetric functions for signed graphs
In 1995, Stanley introduced the chromatic symmetric function of a graph, which specializes to its chromatic polynomial, and which has been the focus of intense research. In 2017, Shareshian, Wachs, and Ellzey defined a refinement of this function for a directed graph, that appears to be in $QSym$, the algebra of quasisymmetric functions, which is of great interest in algebraic combinatorics. Our goal is to extend this work to signed graphs, taking into account the perspective of the hyperplane …

Vertex-Based Localization of generalized Tur\'{a}n Problems
Rajat Adak, L. Sunil Chandran
https://arxiv.org/abs/2508.20936 https://arxiv.org/pdf/2508.2…

Vertex-Based Localization of generalized Turán Problems
Let $\mathcal{F}$ be a family of graphs. A graph is called $\mathcal{F}$-free if it does not contain any member of $\mathcal{F}$. Generalized Turán problems aim to maximize the number of copies of a graph $H$ in an $n$-vertex $\mathcal{F}$-free graph. This maximum is denoted by $ex(n, H, \mathcal{F})$. When $H \cong K_2$, it is simply denoted by $ex(n,F)$. Erdős and Gallai established the bounds $ex(n, P_{k+1}) \leq \frac{n(k-1)}{2}$ and $ex(n, C_{\geq k+1}) \leq \frac{k(n-1)}{2}$. This was l…