Tootfinder

Streaming Sequence-to-Sequence Learning with Delayed Streams Modeling
Neil Zeghidour, Eugene Kharitonov, Manu Orsini, V\'aclav Volhejn, Gabriel de Marmiesse, Edouard Grave, Patrick P\'erez, Laurent Mazar\'e, Alexandre D\'efossez
https://arxiv.org/abs/2509.08753

Streaming Sequence-to-Sequence Learning with Delayed Streams Modeling
We introduce Delayed Streams Modeling (DSM), a flexible formulation for streaming, multimodal sequence-to-sequence learning. Sequence-to-sequence generation is often cast in an offline manner, where the model consumes the complete input sequence before generating the first output timestep. Alternatively, streaming sequence-to-sequence rely on learning a policy for choosing when to advance on the input stream, or write to the output stream. DSM instead models already time-aligned streams with a …

Bidirectional Representations Augmented Autoregressive Biological Sequence Generation:Application in De Novo Peptide Sequencing
Xiang Zhang, Jiaqi Wei, Zijie Qiu, Sheng Xu, Zhi Jin, ZhiQiang Gao, Nanqing Dong, Siqi Sun
https://arxiv.org/abs/2510.08169

Bidirectional Representations Augmented Autoregressive Biological Sequence Generation:Application in De Novo Peptide Sequencing
Autoregressive (AR) models, common in sequence generation, are limited in many biological tasks such as de novo peptide sequencing and protein modeling by their unidirectional nature, failing to capture crucial global bidirectional token dependencies. Non-Autoregressive (NAR) models offer holistic, bidirectional representations but face challenges with generative coherence and scalability. To transcend this, we propose a hybrid framework enhancing AR generation by dynamically integrating rich c…

A Spectral Sequence for Equidimensional Actions of Compact Lie Groups
Pawe{\l} Ra\'zny
https://arxiv.org/abs/2510.07903 https://arxiv.org/pdf/2510.0790…

A Spectral Sequence for Equidimensional Actions of Compact Lie Groups
In this article we provide a version of the Leray-Serre spectral sequence for equidimensional (i.e. smooth with all orbits of the same dimension) actions of compact connected Lie groups on compact manifolds. The main part of this article consists of the proof of the description of the second page of said spectral sequence. This description provides a link between the cohomology of the orbit space (basic cohomology of the foliation by orbits) the Lie algebra cohomology of the appropriate pair $(…

Open Hurwitz numbers and the mKP hierarchy
Alexandr Buryak, Ran J. Tessler, Mikhail Troshkin
https://arxiv.org/abs/2510.08038 https://arxiv.org/pdf/2510.08…

Open Hurwitz numbers and the mKP hierarchy
We give a natural definition of open Hurwitz numbers, where the weight of each ramified covering includes an integer parameter $N$ taken to the power that is equal to the number of boundary components of a Riemann surface with boundary mapping to $\mathbb{CP}^1$. We prove that the resulting sequence of partition functions, depending on $N\in\mathbb{Z}$, is a tau-sequence of the mKP hierarchy, or in other words it is a sequence of tau-functions of the KP hierarchy where each tau-function is obta…

Solvability of Infinite Systems of Nonlinear Caputo Fractional Differential equations in generalized Hahn Sequence Space
Khurshida Parvin, Bipan Hazarika, Awad A. Bakery
https://arxiv.org/abs/2509.06959

Solvability of Infinite Systems of Nonlinear Caputo Fractional Differential equations in generalized Hahn Sequence Space
This paper presents the Hausdorff measure of noncompactness (MNC) within the framework of the generalized Hahn sequence space. By applying the MNC, we explore the existence of solutions for nonlinear Caputo fractional differential equations subject to three-point integral boundary conditions in the generalized Hahn sequence space. We apply certain sufficient conditions to ensure the uniqueness of solutions to the aforementioned problem, utilizing the Banach fixed-point theorem, and discuss the …

COSMOS-Web galaxy groups: Evolution of red sequence and quiescent galaxy fraction
Greta Toni, Matteo Maturi, Gianluca Castignani, Lauro Moscardini, Ghassem Gozaliasl, Alexis Finoguenov, Sina Taamoli, B. Hollis Akins, C. Rafael Arango-Toro, M. Caitlin Casey, E. Nicole Drakos, L. Andreas Faisst, Carter Flayhart, Maximilien Franco, Fabrizio Gentile, Ali Hadi, Santosh Harish, Hossein Hatamnia, Olivier Ilbert, Shuowen Jin, S. Jeyhan Kartaltepe, Ali Ahmad Khostovan, M. Anton Koekemoer, Gavin…

COSMOS-Web galaxy groups: Evolution of red sequence and quiescent galaxy fraction
We investigate the redshift and group richness dependence of the quiescent fraction and red-sequence (RS) parameters in COSMOS galaxy groups from z=0 to z=3.7. We analyzed the deep and well-characterized sample of groups detected with AMICO in the COSMOS(-Web) field. Our study of the quiescent galaxy population is based on a machine-learning classification tool based on rest-frame magnitudes. The algorithm learns from several traditional methods to estimate the probability of a galaxy being qui…

Scots, as a language, is rich in insults; and an ancient one is 'toom (empty) tabard' for a worthless person -- an epithet most notably applied to John de Balliol, who served as King of Scots during the middle period of the wars of independence.
It's interesting to see Grauniad cartoonist Ben Jenkins apply the idea to #Starmer's cabinet.

Testing the Role of Merging Binaries in the Formation of the Split Main Sequence in Young Clusters
Nate Bastian, Sebastian Kamann, Florian Niederhofer, Sara Saracino
https://arxiv.org/abs/2509.07708

Testing the Role of Merging Binaries in the Formation of the Split Main Sequence in Young Clusters
A number of theories have been put forward to explain the bi-modal stellar rotational distribution observed in young massive clusters. These include stellar mergers and interactions induced in binary systems, and the role of angular momentum transfer between a star and its circumstellar disk in its early evolution. Each theory predicts unique rotation distributions in various locations of the colour-magnitude diagram. Specifically, the stellar merger hypothesis posits that the upper end of the …

Controllable Singing Voice Synthesis using Phoneme-Level Energy Sequence
Yerin Ryu, Inseop Shin, Chanwoo Kim
https://arxiv.org/abs/2509.07038 https://arxiv…

Controllable Singing Voice Synthesis using Phoneme-Level Energy Sequence
Controllable Singing Voice Synthesis (SVS) aims to generate expressive singing voices reflecting user intent. While recent SVS systems achieve high audio quality, most rely on probabilistic modeling, limiting precise control over attributes such as dynamics. We address this by focusing on dynamic control--temporal loudness variation essential for musical expressiveness--and explicitly condition the SVS model on energy sequences extracted from ground-truth spectrograms, reducing annotation costs…

The Space-Time Connectivity Theorem for Normal Currents
Paolo Bonicatto, Filip Rindler, Harry Turnbull
https://arxiv.org/abs/2510.08360 https://arxiv.org/p…

The Space-Time Connectivity Theorem for Normal Currents
This work establishes a Space-Time Connectivity Theorem for normal currents. In analogy to classical results by Federer and Fleming as well as a recent theorem for integral currents by the second author, this result allows one to witness the weak* convergence of a uniformly bounded sequence of boundaryless normal currents with a space-time normal current that connects the elements of the sequence with their limit. The space-time setting is distinguished from the classical case in that this conn…

Disintegrating the curve complex
Mladen Bestvina, Kenneth Bromberg, Alexander J. Rasmussen
https://arxiv.org/abs/2510.03980 https://arxiv.org/pdf/2510.0398…

Disintegrating the curve complex
We study a finite sequence of graphs, beginning with the curve graph and ending with a graph quasi-isometric to a tree. There is a Lipschitz map from one graph in the sequence to the next. This sequence was first introduced by Hamenstädt. We prove (as conjectured by Hamenstädt) that the graphs in this sequence are hyperbolic and that the coarse fibers of the maps in the sequence are quasi-trees. This gives an upper bound on the asymptotic dimension of each graph in the sequence and as a resul…

Truth-Aware Decoding: A Program-Logic Approach to Factual Language Generation
Faruk Alpay, Hamdi Alakkad
https://arxiv.org/abs/2510.07331 https://arxiv.org…

Truth-Aware Decoding: A Program-Logic Approach to Factual Language Generation
This paper introduces Truth-Aware Decoding (TAD), a verification-oriented decoding scheme that aligns neural language generation with knowledge bases. Situated in the tradition of probabilistic program semantics for sequence models, TAD augments modern instruction-tuned systems with a lattice of semantic guards that operate at decode time. Our contributions are fourfold: (i) a constraint-based semantics that renders oracle filtering as a program-logic judgment, (ii) a proof that greedy selectio…

To Sink or Not to Sink: Visual Information Pathways in Large Vision-Language Models
Jiayun Luo, Wan-Cyuan Fan, Lyuyang Wang, Xiangteng He, Tanzila Rahman, Purang Abolmaesumi, Leonid Sigal
https://arxiv.org/abs/2510.08510

To Sink or Not to Sink: Visual Information Pathways in Large Vision-Language Models
Large Vision Language Models (LVLMs) have recently emerged as powerful architectures capable of understanding and reasoning over both visual and textual information. These models typically rely on two key components: a Vision Transformer (ViT) and a Large Language Model (LLM). ViT encodes visual content into a sequence of image tokens and serves as the perceptual front-end -- the eyes of the model. In contrast, the LLM interprets these tokens to perform high-level reasoning, generates responses…

Equivalence of continuous- and discrete-variable gate-based quantum computers with finite energy
Alex Maltesson, Ludvig Rodung, Niklas Budinger, Giulia Ferrini, Cameron Calcluth
https://arxiv.org/abs/2510.08546

Equivalence of continuous- and discrete-variable gate-based quantum computers with finite energy
We examine the ability of gate-based continuous-variable quantum computers to outperform qubit or discrete-variable quantum computers. Gate-based continuous-variable operations refer to operations constructed using a polynomial sequence of elementary gates from a specific finite set, i.e., those selected from the set of Gaussian operations and cubic phase gates. Our results show that for a fixed energy of the system, there is no superpolynomial computational advantage in using gate-based contin…

Native Hybrid Attention for Efficient Sequence Modeling
Jusen Du, Jiaxi Hu, Tao Zhang, Weigao Sun, Yu Cheng
https://arxiv.org/abs/2510.07019 https://arxiv.…

Native Hybrid Attention for Efficient Sequence Modeling
Transformers excel at sequence modeling but face quadratic complexity, while linear attention offers improved efficiency but often compromises recall accuracy over long contexts. In this work, we introduce Native Hybrid Attention (NHA), a novel hybrid architecture of linear and full attention that integrates both intra \& inter-layer hybridization into a unified layer design. NHA maintains long-term context in key-value slots updated by a linear RNN, and augments them with short-term tokens fro…

Rearrangements of distributions on integers that minimize variance
Aistis Atminas, Valentas Kurauskas
https://arxiv.org/abs/2510.07899 https://arxiv.org/pd…

Rearrangements of distributions on integers that minimize variance
Which permutations of a probability distribution on integers minimize variance? Let $X$ be a random variable on a set of integers $\{x_1, \dots, x_N\}$ such that $\mathbb{P}(X_i = x_i) = p_i$, $i \in \{1,\dots,N\}$. Let $(p^{(1)}, \dots, p^{(N)})$ be the sequence $(p_1, \dots, p_N)$ ordered non-increasingly. Let $X^+$ be the random variable defined by $\mathbb{P}(X=0)=p^{(1)}$, $\mathbb{P}(X=1) = p^{(2)}$, $\mathbb{P}(X=-1)=p^{(3)}, \dots, \mathbb{P}(X=(-1)^N \lfloor \frac {N} 2 \rfloor)=p^{(…

The blow-up of a singularity at the module of derivations
Paul Barajas, Enrique Ch\'avez-Mart\'inez, Agust\'in Romano-Vel\'azquez
https://arxiv.org/abs/2510.07607

The blow-up of a singularity at the module of derivations
We study the problem of resolving singularities via the blow-up of the module of derivations. Our main results are a positive answer for the case of curves and log-canonical surface singularities, i.e., a finite sequence of blow-ups along the module of derivations resolves the singularities of such varieties.

Recursive Aperture Decoded Ultrasound Imaging (READI) With Estimated Motion-Compensated Compounding (EMC2)
Tyler Keith Henry, Darren Dahunsi, Randy Palamar, Negar Majidi, Mohammad Rahim Sobhani, Roger Zemp
https://arxiv.org/abs/2509.08781

Recursive Aperture Decoded Ultrasound Imaging (READI) With Estimated Motion-Compensated Compounding (EMC2)
Fast Orthogonal Row-Column Electronic Scanning (FORCES) is a Hadamard-encoded Synthetic Transmit Aperture (STA) imaging sequence using bias-sensitive Top-Orthogonal to Bottom Electrode (TOBE) arrays. It produces images with a higher Signal-to-Noise Ratio (SNR) and improved penetration depth compared to traditional STA techniques, but suffers from motion sensitivity due to ensemble size and aperture encoding. This work presents Recursive Aperture Decoded Ultrasound Imaging (READI), a novel decod…

Revealing Unresolved White Dwarf-Main Sequence Binaries using Gaia DR3 and GALEX I. A Volume limited study of 100 pc
Prasanta K. Nayak
https://arxiv.org/abs/2509.06910 https://

Revealing Unresolved White Dwarf-Main Sequence Binaries using Gaia DR3 and GALEX I. A Volume limited study of 100 pc
Context. Understanding the demographics of white dwarf - main sequence (WDMS) binaries is key to uncovering the formation of various stellar exotica and refining the details of binary stellar evolution. Despite several dedicated efforts to identify unresolved WDMS binaries, their population remains incomplete, even within a 100 pc volume-limited sample. Aims. This study aims to identify WDMS binaries hidden within the main sequence of the optical color-magnitude diagram (CMD), improving the com…

On the distribution of the Fourier coefficients over two sparse sequences
Venkatasubbareddy Kampamolla
https://arxiv.org/abs/2509.07037 https://arxiv.org/p…

On the distribution of the Fourier coefficients over two sparse sequences
Let $j\geq 3$ be any fixed integer and $f$ be a primitive holomorphic cusp form of even integral weight $κ\geq 2$ for the full modular group $SL(2,\mathbb{Z})$. We write $λ_{{\rm{sym}^j }f}(n)$ for the $n^\text{th}$ normalized Fourier coefficient of $L(s,{\rm{sym}}^j f)$. In this article, we establish asymptotic formulae for the discrete sums of the Fourier coefficients $λ_{\rm{sym}^j f}^2(n)$ over two sparse sequence of integers, which can be written as the sum of four integral squares and …

Detection of mean changes in partially observed functional data
\v{S}\'arka Hudecov\'a, Claudia Kirch
https://arxiv.org/abs/2510.07854 https://arxi…

Detection of mean changes in partially observed functional data
We propose a test for a change in the mean for a sequence of functional observations that are only partially observed on subsets of the domain, with no information available on the complement. The framework accommodates important scenarios, including both abrupt and gradual changes. The significance of the test statistic is assessed via a permutation test. In addition to the classical permutation approach with a fixed number of permutation samples, we also discuss a variant with controlled resa…

PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations
Ruining He, Lukasz Heldt, Lichan Hong, Raghunandan Keshavan, Shifan Mao, Nikhil Mehta, Zhengyang Su, Alicia Tsai, Yueqi Wang, Shao-Chuan Wang, Xinyang Yi, Lexi Baugher, Baykal Cakici, Ed Chi, Cristos Goodrow, Ningren Han, He Ma, Romer Rosales, Abby Van Soest, Devansh Tandon, Su-Lin Wu, Weilong Yang, Yilin Zheng

PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations
Large Language Models (LLMs) pose a new paradigm of modeling and computation for information tasks. Recommendation systems are a critical application domain poised to benefit significantly from the sequence modeling capabilities and world knowledge inherent in these large models. In this paper, we introduce PLUM, a framework designed to adapt pre-trained LLMs for industry-scale recommendation tasks. PLUM consists of item tokenization using Semantic IDs, continued pre-training (CPT) on domain-sp…

Timeline Problems in Temporal Graphs: Vertex Cover vs. Dominating Set
Anton Herrmann, Christian Komusiewicz, Nils Morawietz, Frank Sommer
https://arxiv.org/abs/2510.08124 https:…

Timeline Problems in Temporal Graphs: Vertex Cover vs. Dominating Set
A temporal graph is a finite sequence of graphs, called snapshots, over the same vertex set. Many temporal graph problems turn out to be much more difficult than their static counterparts. One such problem is \textsc{Timeline Vertex Cover} (also known as \textsc{MinTimeline$_\infty$}), a temporal analogue to the classical \textsc{Vertex Cover} problem. In this problem, one is given a temporal graph $\mathcal{G}$ and two integers $k$ and $\ell$, and the goal is to cover each edge of each snapsho…

LSMTCR: A Scalable Multi-Architecture Model for Epitope-Specific T Cell Receptor de novo Design
Ruihao Zhang, Xiao Liu
https://arxiv.org/abs/2509.07627 https://

LSMTCR: A Scalable Multi-Architecture Model for Epitope-Specific T Cell Receptor de novo Design
Designing full-length, epitope-specific TCR α\b{eta} remains challenging due to vast sequence space, data biases and incomplete modeling of immunogenetic constraints. We present LSMTCR, a scalable multi-architecture framework that separates specificity from constraint learning to enable de novo, epitope-conditioned generation of paired, full-length TCRs. A diffusion-enhanced BERT encoder learns time-conditioned epitope representations; conditional GPT decoders, pretrained on CDR3\b{eta} and tr…

Trust-Region Method for Optimization of Set-Valued Maps Given by Finitely Many Functions
Suprova Ghosh, Debdas Ghosh, Christiane Tammer, Xiaopeng Zhao
https://arxiv.org/abs/2509.07836

Trust-Region Method for Optimization of Set-Valued Maps Given by Finitely Many Functions
In this article, we develop a trust-region technique to find critical points of unconstrained set optimization problems with the objective set-valued map defined by finitely many twice continuously differentiable functions. The technique is globally convergent and has the descent property. To ensure the descent property, a new rule of trust-region reduction ratio is introduced for the considered set-valued maps. In the derived method, to find the sequence of iteration points, we need to perform…

On the generating series of the degree sequence
Quang-Khai Nguyen
https://arxiv.org/abs/2510.06142 https://arxiv.org/pdf/2510.06142

On the generating series of the degree sequence
We study the generating series associated with the degree sequence of a monomial self-map of a projective toric variety. We establish conditions under which this series has its circle of convergence as a natural boundary, and hence is a transcendental, non-holonomic function. In the case of toric surfaces, our results are sharp; moreover, we answer a question of Bell by proving that their reductions modulo $p$ are transcendental for all but finitely many prime numbers $p$.

Today I found out that ffmpeg can process an input image sequence not only using the printf-style pattern (i.e. frame.d.jpg) but also using a glob pattern. It needs the parameter "-pattern_type glob" before your -i argument.
The advantage of glob patterns is the fact that it will skip over missing numbers. You can use this to turn a bunch of numbered photos from your location scouting into a movie clip that you can show to the client or upload as a preview to an asset libr…

Real-time CBCT reconstructions using Krylov solvers in repeated scanning procedures
Fred Vickers Hastings, S M Ragib Shahriar Islam, Malena Sabat\'e Landman, Sepideh Hatamikia, Carola-Bibiane Sch\"onlieb, Ander Biguri
https://arxiv.org/abs/2509.08574

Real-time CBCT reconstructions using Krylov solvers in repeated scanning procedures
This work introduces a new efficient iterative solver for the reconstruction of real-time cone-beam computed tomography (CBCT), which is based on the Prior Image Constrained Compressed Sensing (PICCS) regularization and leverages the efficiency of Krylov subspace methods. In particular, we focus on the setting where a sequence of under-sampled CT scans are taken on the same object with only local changes (e.g. changes in a tumour size or the introduction of a surgical tool). This is very common…

Counter-example to continuity of measure in uncountable unions
Simranjeet Bilkhu, Noah Mills Forman
https://arxiv.org/abs/2509.07168 https://arxiv.org/pdf/…

Counter-example to continuity of measure in uncountable unions
Continuity of measure asserts that the measure of the union of an increasing sequence of sets is equal to the supremum of the measures of those sets. We provide counter examples in the case of uncountable unions. We construct the first counter example on the ordinal numbers, and we show that counterexamples also exist in the reals if we assume the continuum hypothesis.

Decoding the dark proteome: Deep learning-enabled discovery of druggable enzymes in Wuchereria bancrofti
Shawnak Shivakumar, Jefferson Hernandez
https://arxiv.org/abs/2510.07337

Decoding the dark proteome: Deep learning-enabled discovery of druggable enzymes in Wuchereria bancrofti
Wuchereria bancrofti, the parasitic roundworm responsible for lymphatic filariasis, permanently disables over 36 million people and places 657 million at risk across 39 countries. A major bottleneck for drug discovery is the lack of functional annotation for more than 90 percent of the W. bancrofti dark proteome, leaving many potential targets unidentified. In this work, we present a novel computational pipeline that converts W. bancrofti's unannotated amino acid sequence data into precise four…

Object Classification from JWST Catalogs
B. L. Crompvoets, H. Kirk, R. Gutermuth, J. Di Francesco
https://arxiv.org/abs/2510.07747 https://arxiv.org/pdf/25…

Object Classification from JWST Catalogs
JWST's exquisite data have opened the doors to new possibilities in detecting broad classes of astronomical objects, but also to new challenges in classifying those objects. In this work, we introduce SESHAT, the Stellar Evolutionary Stage Heuristic Assessment Tool for the identification of Young Stellar Objects, field stars (main sequence through asymptotic giant branch), brown dwarfs, white dwarfs, and galaxies, from any JWST observation. This identification is done using the machine learning…

Learning What's Missing: Attention Dispersion and EMA Stabilization in Length Generalization
P\'al Zs\'amboki, Benjamin Levi, David Ansel Josef Smith, Mitansh Kagalwala, Arlington Kell, Samuel Liechty, Cong Wang
https://arxiv.org/abs/2510.08341

Learning What's Missing: Attention Dispersion and EMA Stabilization in Length Generalization
We study length generalization in transformers through the set complement task, where a model must predict a uniform distribution over tokens absent from an input sequence -- an ability central to board-game style reasoning. Our main theoretical result establishes two statements. First, we prove tight bounds on embedding and value dimensions for single-layer attention-only transformers. Second, we show that if such a model achieves balanced logit displacement at lengths 1 and 2, then it must ge…

gnutella: Gnutella p2p networks (2002)
A sequence of 9 snapshots of the Gnutella peer-to-peer file sharing network from 5-31 August 2002. Nodes are hosts in the Gnutella network topology and edges are connections between them.
This network has 6301 nodes and 20777 edges.
Tags: Technological, Peer-to-peer, Unweighted
https://

CAZAC sequence generation of any length with iterative projection onto unit circle: principle and first results
Karine Amis, Eloi Boutillon, Emmanuel Boutillon
https://arxiv.org/abs/2509.05097

CAZAC sequence generation of any length with iterative projection onto unit circle: principle and first results
Constant amplitude zero-autocorrelation (CAZAC) sequences are mainly used for synchronization in communication and radar applications. The state-of-the-art proposes analytical derivation of specific families whose major limitation comes from the alphabet which only represents a fraction of the whole, the longer the sequences, the smaller the fraction. The objective of the paper is threefold, first to present the construction of constant amplitude zero-circular autocorrelation sequences of any l…

The Star-forming Main Sequence and Bursty Star-formation Histories at $z>1.4$ in JADES and AURORA
Leonardo Clarke, Alice E. Shapley, Natalie Lam, Michael W. Topping, Gabriel B. Brammer, Ryan L. Sanders, Naveen A. Reddy, Shreya Karthikeyan
https://arxiv.org/abs/2510.06681

The Star-forming Main Sequence and Bursty Star-formation Histories at $z>1.4$ in JADES and AURORA
We analyze JWST spectroscopic and HST+JWST photometric observations of 659 star-forming galaxies at $1.4 < z < 9$ from DR3 of the JADES survey and the AURORA Cycle 1 program. We measure the star-forming main sequence (SFMS) for galaxies above $10^{8.5}\rm\ M_\odot$ where the sample is largely representative, estimating star-formation rates (SFRs) using the H$α$ line flux and rest-frame far UV (1600Å) continuum measurements, each independently corrected for dust attenuation. We find that the i…

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video
David Stotko, Reinhard Klein
https://arxiv.org/abs/2509.08828 ht…

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video
The reconstruction of three-dimensional dynamic scenes is a well-established yet challenging task within the domain of computer vision. In this paper, we propose a novel approach that combines the domains of 3D geometry reconstruction and appearance estimation for physically based rendering and present a system that is able to perform both tasks for fabrics, utilizing only a single monocular RGB video sequence as input. In order to obtain realistic and high-quality deformations and renderings, …

Chain-of-Trigger: An Agentic Backdoor that Paradoxically Enhances Agentic Robustness
Jiyang Qiu, Xinbei Ma, Yunqing Xu, Zhuosheng Zhang, Hai Zhao
https://arxiv.org/abs/2510.08238

Chain-of-Trigger: An Agentic Backdoor that Paradoxically Enhances Agentic Robustness
The rapid deployment of large language model (LLM)-based agents in real-world applications has raised serious concerns about their trustworthiness. In this work, we reveal the security and robustness vulnerabilities of these agents through backdoor attacks. Distinct from traditional backdoors limited to single-step control, we propose the Chain-of-Trigger Backdoor (CoTri), a multi-step backdoor attack designed for long-horizon agentic control. CoTri relies on an ordered sequence. It starts with…

Totally normal night:
1. Scratching the cat.
2. The first continuous sleep, ending with a #nightmare. I've dreamt that my first return train was delayed, and I'm likely to be stuck in Głogów. On top of that, the train looked looked like a nightmare contraption, with a sequence of cubic compartments with no seats, and weirdly shaped holes in the walls instead of doors.
3. Toilet.
4. Checking blood sugar, just in case.
5. Looking for a spot in the bed that's free of sweat.
6. Scratching the cat.
7. A series of nightmares. The most interesting one was about getting up in the morning, in middle of a gale. The mains voltage was so low I couldn't turn the lights on, and instead of getting myself ready to go out, I was trying hard to measure it, helping myself with a flashlight.
My working theory is that these are side effects of my current medication. One week to go.

A doubly composite Chernoff-Stein lemma and its applications
Ludovico Lami
https://arxiv.org/abs/2510.06342 https://arxiv.org/pdf/2510.06342

A doubly composite Chernoff-Stein lemma and its applications
Given a sequence of random variables $X^n=X_1,\ldots, X_n$, discriminating between two hypotheses on the underlying probability distribution is a key task in statistics and information theory. Of interest here is the Stein exponent, i.e. the largest rate of decay (in $n$) of the type II error probability for a vanishingly small type I error probability. When the hypotheses are simple and i.i.d., the Chernoff-Stein lemma states that this is given by the relative entropy between the single-copy p…

Sequence-Based Deep Learning for Handover Optimization in Dense Urban Cellular Network
Muhammad Kabeer, Rosdiadee Nordin, Mehran Behjati, Lau Sian Lun
https://arxiv.org/abs/2510.02958

Sequence-Based Deep Learning for Handover Optimization in Dense Urban Cellular Network
Efficient handover management remains a critical challenge in dense urban cellular networks, where high cell density, user mobility, and diverse service demands increase the likelihood of unnecessary handovers and ping-pong effects. This paper leverages a real-world, multi-operator drive-test dataset of 30,925 labelled records collected within a 2 km area around Sunway City to investigate sequence-based deep learning approaches for handover detection and avoidance. We formulate handover predict…

Ambidextrous Degree Sequence Bounds for Pessimistic Cardinality Estimation
Yu-Ting Lin, Hsin-Po Wang
https://arxiv.org/abs/2510.04249 https://arxiv.org/pdf…

Ambidextrous Degree Sequence Bounds for Pessimistic Cardinality Estimation
In a large database system, upper-bounding the cardinality of a join query is a crucial task called $\textit{pessimistic cardinality estimation}$. Recently, Abo Khamis, Nakos, Olteanu, and Suciu unified related works into the following dexterous framework. Step 1: Let $(X_1, \dotsc, X_n)$ be a random row of the join, equating $H(X_1, \dotsc, X_n)$ to the log of the join cardinality. Step 2: Upper-bound $H(X_1, \dotsc, X_n)$ using Shannon-type inequalities such as $H(X, Y, Z) \le H(X) + H(Y|…

from my link log —
Middle-square Weyl sequence PRNG.
https://arxiv.org/abs/1704.00358
saved 2025-10-28 https://dotat.at/:/GS290.html

Middle-Square Weyl Sequence RNG
In this article, we propose a new implementation of John von Neumann's middle-square random number generator (RNG). A Weyl sequence keeps the generator running through a long period.

Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding
Tam Thuc Do, Philip A. Chou, Gene Cheung
https://arxiv.org/abs/2509.08685 https://

Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding
Given encoded 3D point cloud geometry available at the decoder, we study the problem of lossy attribute compression in a multi-resolution B-spline projection framework. A target continuous 3D attribute function is first projected onto a sequence of nested subspaces $\mathcal{F}^{(p)}_{l_0} \subseteq \cdots \subseteq \mathcal{F}^{(p)}_{L}$, where $\mathcal{F}^{(p)}_{l}$ is a family of functions spanned by a B-spline basis function of order $p$ at a chosen scale and its integer shifts. The projec…

Lossless Vocabulary Reduction for Auto-Regressive Language Models
Daiki Chijiwa, Taku Hasegawa, Kyosuke Nishida, Shin'ya Yamaguchi, Tomoya Ohba, Tamao Sakao, Susumu Takeuchi
https://arxiv.org/abs/2510.08102

Lossless Vocabulary Reduction for Auto-Regressive Language Models
Tokenization -- the process of decomposing a given text into a sequence of subwords called tokens -- is one of the key components in the development of language models. Particularly, auto-regressive language models generate texts token by token, i.e., by predicting the next-token distribution given the previous ones, and thus tokenization directly affects their efficiency in text generation. Since each language model has their own vocabulary as a set of possible tokens, they struggle to coopera…

System size and boundaries determine the patterning dynamics of attracting active particles
Jan Rombouts, Michael L Zhao, Alexander Aulehla, Anna Erzberger
https://arxiv.org/abs/2509.08533

System size and boundaries determine the patterning dynamics of attracting active particles
Pattern formation often occurs in confined systems, yet how boundaries shape patterning dynamics is unclear. We develop techniques to analyze confinement effects in nonlocal advection-diffusion equations, which generically capture the collective dynamics of active self-attracting particles. We identify a sequence of size-controlled transitions that generate characteristic slow modes, leading to exponential increase of patterning timescales. Experimental measurements of multicellular dynamics co…

Compressibility Measures and Succinct Data Structures for Piecewise Linear Approximations
Paolo Ferragina, Filippo Lari
https://arxiv.org/abs/2509.07827 https://

Compressibility Measures and Succinct Data Structures for Piecewise Linear Approximations
We study the problem of deriving compressibility measures for \emph{Piecewise Linear Approximations} (PLAs), i.e., error-bounded approximations of a set of two-dimensional {\em increasing} data points using a sequence of segments. Such approximations are widely used tools in implementing many \emph{learned data structures}, which mix learning models with traditional algorithmic design blocks to exploit regularities in the underlying data distribution, providing novel and effective space-time tr…

Optimal Smooth Coverage Trajectory Planning for Quadrotors in Cluttered Environment
Duanjiao Li, Yun Chen, Ying Zhang, Junwen Yao, Dongyue Huang, Jianguo Zhang, Ning Ding
https://arxiv.org/abs/2510.03169

Optimal Smooth Coverage Trajectory Planning for Quadrotors in Cluttered Environment
For typical applications of UAVs in power grid scenarios, we construct the problem as planning UAV trajectories for coverage in cluttered environments. In this paper, we propose an optimal smooth coverage trajectory planning algorithm. The algorithm consists of two stages. In the front-end, a Genetic Algorithm (GA) is employed to solve the Traveling Salesman Problem (TSP) for Points of Interest (POIs), generating an initial sequence of optimized visiting points. In the back-end, the sequence is…

The Keychain Problem: On Minimizing the Opportunity Cost of Uncertainty
Ramiro N. Deo-Campo Vuong, Robert Kleinberg, Aditya Prasad, Eric Xiao, Haifeng Xu
https://arxiv.org/abs/2509.06187

The Keychain Problem: On Minimizing the Opportunity Cost of Uncertainty
In this paper, we introduce a family of sequential decision-making problems, collectively called the Keychain Problem, that involve exploring a set of actions to maximize expected payoff when only a subset of actions are available in each stage. In an instance of the Keychain Problem, a locksmith faces a sequence of choices, each of which involves selecting one key from a specified subset (a keychain) to attempt to open a lock. Given a Bayesian prior on the effectiveness of keys, the locksmith'…

DeepStream: Prototyping Deep Joint Source-Channel Coding for Real-Time Multimedia Transmissions
Kaiyi Chi, Yinghui He, Qianqian Yang, Zhiping Jiang, Yuanchao Shu, Zhiqin Wang, Jun Luo, Jiming Chen
https://arxiv.org/abs/2509.05971

DeepStream: Prototyping Deep Joint Source-Channel Coding for Real-Time Multimedia Transmissions
Deep learning-based joint source-channel coding (DeepJSCC) has emerged as a promising technique in 6G for enhancing the efficiency and reliability of data transmission across diverse modalities, particularly in low signal-to-noise ratio (SNR) environments. This advantage is realized by leveraging powerful neural networks to learn an optimal end-to-end mapping from the source data directly to the transmit symbol sequence, eliminating the need for separate source coding, channel coding, and modul…

Customizing the Inductive Biases of Softmax Attention using Structured Matrices
Yilun Kuang, Noah Amsel, Sanae Lotfi, Shikai Qiu, Andres Potapczynski, Andrew Gordon Wilson
https://arxiv.org/abs/2509.07963

Customizing the Inductive Biases of Softmax Attention using Structured Matrices
The core component of attention is the scoring function, which transforms the inputs into low-dimensional queries and keys and takes the dot product of each pair. While the low-dimensional projection improves efficiency, it causes information loss for certain tasks that have intrinsically high-dimensional inputs. Additionally, attention uses the same scoring function for all input pairs, without imposing a distance-dependent compute bias for neighboring tokens in the sequence. In this work, we …

Cowboys victory was forged in this key sequence, potential 21-point swing vs Jets https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2025/10/05/the-dallas-cowboys-used-a-lat…

On the Theory of Continual Learning with Gradient Descent for Neural Networks
Hossein Taheri, Avishek Ghosh, Arya Mazumdar
https://arxiv.org/abs/2510.05573 https://

On the Theory of Continual Learning with Gradient Descent for Neural Networks
Continual learning, the ability of a model to adapt to an ongoing sequence of tasks without forgetting the earlier ones, is a central goal of artificial intelligence. To shed light on its underlying mechanisms, we analyze the limitations of continual learning in a tractable yet representative setting. In particular, we study one-hidden-layer quadratic neural networks trained by gradient descent on an XOR cluster dataset with Gaussian noise, where different tasks correspond to different clusters…

Hitting times of shrinking targets: Transversality and an ergodic theorem
Vicente Saavedra-Araya
https://arxiv.org/abs/2510.07450 https://arxiv.org/pdf/251…

Hitting times of shrinking targets: Transversality and an ergodic theorem
In this paper, we investigate ergodic and fractal properties of the sets $$Λ_y:=\Big\{n\in\mathbb{N}:\ \{u_ny\}\in I_n\Big\},$$ where $\{\cdot\}$ denotes the fractional part function, $(u_n)_{n\in\mathbb{N}}$ is an increasing sequence of real numbers, $y\in [0,1]$ and each $I_n$ is a finite union of intervals with decreasing Lebesgue measure. Our main result shows that, under suitable conditions, the set $Λ_y$ is good for pointwise convergence of ergodic averages for Lebesgue almost every $y\…

Retrieving the structure of probabilistic sequences from EEG data during the goalkeeper game
P. R. Cabral-Passos, P. S. Azevedo, V. H. Moraes, B. L. Ramalho, A. Duarte, C. D. Vargas
https://arxiv.org/abs/2510.06344

Retrieving the structure of probabilistic sequences from EEG data during the goalkeeper game
This work draws on the conjecture that fingerprints of stochastic event sequences can be retrieved from electroencephalographic data (EEG) recorded during a behavioral task. To test this, we used the Goalkeeper Game (game.numec.prp.usp.br). Acting as a goalkeeper, the participant predicted each kick in a probabilistic sequence while EEG activity was recorded. At each trial, driven by a context tree, the kicker chose one of three options: left, center, or right. The goalkeeper then predicted the…

🔊 #NowPlaying on #BBCRadio3:
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- Sherelle's Listening Chair
Elizabeth Alker serves up a sublime sequence of ambient and experimental music. Plus British DJ-producer Sherelle shares a more downtempo side to her musical personality.
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https://www.bbc.co.uk/programmes/m002cbtz

Canonicalization of the E value from BLAST similarity search -- dissimilarity measure and distance function for a metric space of protein sequences
Boryeu Mao
https://arxiv.org/abs/2509.06849

Canonicalization of the E value from BLAST similarity search -- dissimilarity measure and distance function for a metric space of protein sequences
Sequence matching algorithms such as BLAST and FASTA have been widely used in searching for evolutionary origin and biological functions of newly discovered nucleic acid and protein sequences. As parts of these search tools, alignment scores and E values are useful indicators of the quality of search results from querying a database of annotated sequences, whereby a high alignment score (and inversely a low E value) reflects significant similarity between the query and the subject (target) sequ…

Determining the impact of post-main-sequence stellar evolution on the transiting giant planet population: #planets: https://ras.ac.uk/news-and-press/research-highlights/ageing-stars-may-be-destroying-their-closest-planets

Some new results on $\Delta$-spaces
I. Juh\'asz, J. van Mill, L. Soukup, Z. Szentmikl\'ossy
https://arxiv.org/abs/2510.04242 https://arxiv.org/pdf/…

Some new results on $Δ$-spaces
A topological space $X$ is a $Δ$-space (or $X \in Δ$) if for any decreasing sequence $\{A_n : n < ω\}$ of subsets of $X$ with empty intersection there is a (decreasing) sequence $\{U_n : n < ω\}$ of open sets with empty intersection such that $A_n \subset U_n$ for all $n < ω$. In this note we prove the following results concerning $Δ$-spaces. 1) Every $T_3$ countably compact $Δ$-space is compact. 2) If there is a $T_1$ crowded Baire $Δ$-space then there is an inner model with a meas…

Revisiting scaling limits for critical inhomogeneous random graphs with finite third moments
Louigi Addario-Berry, Sasha Bell, Prabhanka Deka, Serte Donderwinkel, Sourish Maniyar, Minmin Wang, Anita Winter
https://arxiv.org/abs/2509.08439

Revisiting scaling limits for critical inhomogeneous random graphs with finite third moments
We consider the rank-1 inhomogeneous random graph in the Brownian regime in the critical window. Aldous studied the weights of the components, and showed that this ordered sequence converges in the $\ell^2$-topology to the ordered excursions of a Brownian motion with parabolic drift when appropriately rescaled (http://doi.org/10.1214/aop/1024404421), as the number of vertices $n$ tends to infinity. We show that, under the finite third moment condition, the same conclusion holds for the ordered …

Ratios of two exponents of van der Laan-Padovan numbers
Tomohiro Yamada
https://arxiv.org/abs/2510.06192 https://arxiv.org/pdf/2510.06192

Ratios of two exponents of van der Laan-Padovan numbers
The van der Laan-Padovan sequence $P_n ~ (n=0, 1, \ldots)$ is defined by $P_0=1, P_1=P_2=0$, and $P_{n+3}=P_{n+1}+P_n$ for $n=0, 1, \ldots$. We determine all pairs $(P_m, P_n)$ satisfying $P_m^b/P_n^a=2^{g_1} 3^{g_2} 5^{g_3} 7^{g_4}$ for some integers $g_1, g_2, g_3, g_4$, $a$, and $b$. More generally, for a linear recurrence sequence $u_n$ satisfying the dominant root condition and a given set of primes $p_1, \ldots, p_k$, there exist only finitely many pairs $(u_m, u_n)$ satisfying $u_m^b/u_n…

Linear Recurrences from Counting Schreier-Type Multisets
Hung Viet Chu, Yubo Geng, Julian King, Steven J. Miller, Garrett Tresch, Zachary Louis Vasseur
https://arxiv.org/abs/2509.05158

Linear Recurrences from Counting Schreier-Type Multisets
A nonempty set $F$ is Schreier if $\min F\ge |F|$. Bird observed that counting Schreier sets in a certain way produces the Fibonacci sequence. Since then, various connections between variants of Schreier sets and well-known sequences have been discovered. Building on these works, we prove a linear recurrence for the sequence that counts multisets $F$ with $\min F\ge p|F|$. In particular, if we let $$\mathcal{A}^{(s)}_{p, n}\ :=\ \{F\subset \{\underbrace{1, \ldots, 1}_{s}, \l…

Probing accretion and stellar properties in the Orion Nebula with VLT/X-Shooter
L. Piscarreta, G. Beccari, R. A. B. Claes, C. F. Manara, H. M. J. Boffin, T. Jerabkova, B. Ercolano, A. Natta, S. E. van Terwisga
https://arxiv.org/abs/2509.08784

Probing accretion and stellar properties in the Orion Nebula with VLT/X-Shooter
Multiple photometric studies have reported the presence of seemingly older accreting pre-main sequence stars (PMS) in optical colour-magnitude diagrams (CMDs). We investigate this phenomenon in the Orion Nebula, which harbors a subset of stars that show infrared excess detected by Spitzer and Halpha excess emission, yet display significantly older isochronal ages (>10 Myr) compared to the bulk population (~1-3 Myr) in the r, (r-i) CMD. We perform a detailed spectroscopic analysis of 40 Orion Ne…

Variable Matrix-Weighted Besov Spaces
Dachun Yang, Wen Yuan, Zongze Zeng
https://arxiv.org/abs/2509.07786 https://arxiv.org/pdf/2509.07786

Variable Matrix-Weighted Besov Spaces
In this article, applying matrix ${\mathcal A}_{p(\cdot),\infty}$ weights introduced in our previous work, we introduce the matrix-weighted variable Besov space via the matrix weight $W$ or the reducing operators ${\mathbb{A}}$ of order $p(\cdot)$ for $W$, Then we show that, defined either by the matrix weight $W$ or the reducing operators ${\mathbb{A}}$ of order $p(\cdot)$ for $W$, the matrix-weighted variable Besov spaces (respectively, the matrix-weighted variable Besov sequence spaces) are …

Embedding calculus and Vassiliev spectral sequence
Syunji Moriya
https://arxiv.org/abs/2509.23766 https://arxiv.org/pdf/2509.23766

Embedding calculus and Vassiliev spectral sequence
Vassiliev spectral sequence and Sinha spectral sequence are both related to cohomology of the space of long knots $\mathbb{R}\to \mathbb{R}^3$. Although they have different origins, the Vassiliev $E_1$-page and the Sinha $E_2$-page are isomorphic (up to a degree shift). In this paper, we prove that they have isomorphic $E_\infty$-pages if the coefficient ring is a field. Together with degeneracy of the Sinha sequence, this implies that the Vassiliev sequence degenerates at $E_1$-page over $\mat…

Experimental demonstration of genuine quantum information transmission through completely depolarizing channels in a superposition of cyclic orders
Yaxin Wang, Linxiang Zhou, Tianfeng Feng, Hanlin Nie, Ying Xia, Tianqi Xiao, Juntao Li, Vlatko Vedral, Xiaoqi Zhou
https://arxiv.org/abs/2510.07127

Experimental demonstration of genuine quantum information transmission through completely depolarizing channels in a superposition of cyclic orders
A major challenge in quantum communication is addressing the negative effects of noise on channel capacity, especially for completely depolarizing channels, where information transmission is inherently impossible. The concept of indefinite causal order provides a promising solution by allowing control over the sequence in which channels are applied. We experimentally demonstrate the activation of quantum communication through completely depolarizing channels using a programmable silicon photoni…

The Splitting of Generalisations of the Fadell-Neuwirth short exact sequence
Daciberg Lima Gon\c{c}alves, John Guaschi, Carolina de Miranda e Pereiro
https://arxiv.org/abs/2509.02707

The Splitting of Generalisations of the Fadell-Neuwirth short exact sequence
We study some generalisations to mixed braid groups of the Fadell-Neuwirth short exact sequence and the possible splitting of this sequence. In certain cases, we determine conditions under which the projection from the mixed braid group $B_{n_{1},\ldots,n_{k}}(M)$ to $B_{n_{1},\ldots, n_{k-q}}(M)$ admits a section, where $M$ is either the torus or the Klein bottle, $n_{1}, \ldots, n_{k},q \in \mathbb{N}$, and $1\leq q \leq k-1$. For $k\geq 2$ and $q=k-1$, we show that this projection admits a s…

caida_as: CAIDA AS graphs (2004-2007)
A sequence of 122 network snapshots denoting Autonomous System (AS) relationships on the Internet, from 2004-2007, inferred using the Serial-1 method from RouteViews BGP table snapshots and a set of heuristics.
This network has 25696 nodes and 105332 edges.
Tags: Technological, Communication, Unweighted, Temporal

Statistical properties of Markov shifts (part I)
Yeor Hafouta
https://arxiv.org/abs/2510.07757 https://arxiv.org/pdf/2510.07757

Statistical properties of Markov shifts (part I)
We prove central limit theorems, Berry-Esseen type theorems, almost sure invariance principles, large deviations and Livsic type regularity for partial sums of the form $S_n=\sum_{j=0}^{n-1}f_j(...,X_{j-1},X_j,X_{j+1},...)$, where $(X_j)$ is an inhomogeneous Markov chain satisfying some mixing assumptions and $f_j$ is a sequence of sufficiently regular functions. Even though the case of non-stationary chains and time dependent functions $f_j$ is more challenging, our results seem to be new alre…

Poolformer: Recurrent Networks with Pooling for Long-Sequence Modeling
Daniel Gallo Fern\'andez
https://arxiv.org/abs/2510.02206 https://arxiv.org/pdf/…

Poolformer: Recurrent Networks with Pooling for Long-Sequence Modeling
Sequence-to-sequence models have become central in Artificial Intelligence, particularly following the introduction of the transformer architecture. While initially developed for Natural Language Processing, these models have demonstrated utility across domains, including Computer Vision. Such models require mechanisms to exchange information along the time dimension, typically using recurrent or self-attention layers. However, self-attention scales quadratically with sequence length, limiting …

DeRainMamba: A Frequency-Aware State Space Model with Detail Enhancement for Image Deraining
Zhiliang Zhu, Tao Zeng, Tao Yang, Guoliang Luo, Jiyong Zeng
https://arxiv.org/abs/2510.06746

DeRainMamba: A Frequency-Aware State Space Model with Detail Enhancement for Image Deraining
Image deraining is crucial for improving visual quality and supporting reliable downstream vision tasks. Although Mamba-based models provide efficient sequence modeling, their limited ability to capture fine-grained details and lack of frequency-domain awareness restrict further improvements. To address these issues, we propose DeRainMamba, which integrates a Frequency-Aware State-Space Module (FASSM) and Multi-Directional Perception Convolution (MDPConv). FASSM leverages Fourier transform to d…

UniOTalign: A Global Matching Framework for Protein Alignment via Optimal Transport
Yue Hu, Zanxia Cao, Yingchao Liu
https://arxiv.org/abs/2510.06554 https://

UniOTalign: A Global Matching Framework for Protein Alignment via Optimal Transport
Protein sequence alignment is a cornerstone of bioinformatics, traditionally approached using dynamic programming (DP) algorithms that find an optimal sequential path. This paper introduces UniOTalign, a novel framework that recasts alignment from a fundamentally different perspective: global matching via Optimal Transport (OT). Instead of finding a path, UniOTalign computes an optimal flow or transport plan between two proteins, which are represented as distributions of residues in a high-dime…

Degree Realization by Bipartite Cactus Graphs
Amotz Bar-Noy, Toni Bohnlein, David Peleg, Yingli Ran, Dror Rawitz
https://arxiv.org/abs/2509.06194 https://a…

Degree Realization by Bipartite Cactus Graphs
The \textsc{Degree Realization} problem with respect to a graph family $\mathcal{F}$ is defined as follows. The input is a sequence $d$ of $n$ positive integers, and the goal is to decide whether there exists a graph $G \in \mathcal{F}$ whose degrees correspond to $d$. The main challenges are to provide a precise characterization of all the sequences that admit a realization in $\mathcal{F}$ and to design efficient algorithms that construct one of the possible realizations, if one exists. Thi…

Sequence Reconstruction Problem for Ternary Deletion Channels
Xiang Wang, Han Li, Fang-Wei Fu
https://arxiv.org/abs/2509.24237 https://arxiv.org/pdf/2509.2…

Sequence Reconstruction Problem for Ternary Deletion Channels
The sequence reconstruction problem was proposed by Levenshtein in 2001. In this model, a sequence from a code is transmitted over several channels, and the decoder receives the distinct outputs from each channel. The main problem is to determine the minimum number of channels required to reconstruct the transmitted sequence. In the combinatorial context, the sequence reconstruction problem is equivalent to finding the value of $N_q(n,d,t)$, defined as the size of the largest intersection of tw…

Planning from Point Clouds over Continuous Actions for Multi-object Rearrangement
Kallol Saha, Amber Li, Angela Rodriguez-Izquierdo, Lifan Yu, Ben Eisner, Maxim Likhachev, David Held
https://arxiv.org/abs/2509.04645

Planning from Point Clouds over Continuous Actions for Multi-object Rearrangement
Long-horizon planning for robot manipulation is a challenging problem that requires reasoning about the effects of a sequence of actions on a physical 3D scene. While traditional task planning methods are shown to be effective for long-horizon manipulation, they require discretizing the continuous state and action space into symbolic descriptions of objects, object relationships, and actions. Instead, we propose a hybrid learning-and-planning approach that leverages learned models as domain-spe…

On the Clemens-Schmid exact sequence
R. Virk
https://arxiv.org/abs/2509.03700 https://arxiv.org/pdf/2509.03700

On the Clemens-Schmid exact sequence
A treatment of (generalized) Clemens-Schmid exact sequences from the perspective of weights.

Tribonacci-Lucas numbers that are palindromic concatenations of two distinct repdigits
Mahadi Ddamulira
https://arxiv.org/abs/2509.05984 https://arxiv.org/…

Tribonacci-Lucas numbers that are palindromic concatenations of two distinct repdigits
The Tribonacci-Lucas sequence $\{S_n\}_{n\ge 0}$ is defined by the linear recurrence relation $S_{n+3} = S_{n+2} + S_{n+1} + S_n$, for $ n\ge 0 $, with the initial conditions $S_0 =S_2= 3$ and $S_1 = 1$. A palindromic number is a number that remains the same when its digits are reversed. This paper uses Baker's theory for nozero lower bounds for linear forms in logarithms of algebraic numbers, and reduction methods involving the theory of continued fraction to determine all Tribonacci-Lucas num…

A Comparative Analysis of Contextual Representation Flow in State-Space and Transformer Architectures
Nhat M. Hoang, Do Xuan Long, Cong-Duy Nguyen, Min-Yen Kan, Luu Anh Tuan
https://arxiv.org/abs/2510.06640

A Comparative Analysis of Contextual Representation Flow in State-Space and Transformer Architectures
State Space Models (SSMs) have recently emerged as efficient alternatives to Transformer-Based Models (TBMs) for long-sequence processing, offering linear scaling and lower memory use. Yet, how contextual information flows across layers and tokens in these architectures remains understudied. We present the first unified, token- and layer-level analysis of representation propagation in SSMs and TBMs. Using centered kernel alignment, stability metrics, and probing, we characterize how representat…

Breaking the Euclidean Barrier: Hyperboloid-Based Biological Sequence Analysis
Sarwan Ali, Haris Mansoor, Murray Patterson
https://arxiv.org/abs/2510.01118 https://

Breaking the Euclidean Barrier: Hyperboloid-Based Biological Sequence Analysis
Genomic sequence analysis plays a crucial role in various scientific and medical domains. Traditional machine-learning approaches often struggle to capture the complex relationships and hierarchical structures of sequence data when working in high-dimensional Euclidean spaces. This limitation hinders accurate sequence classification and similarity measurement. To address these challenges, this research proposes a method to transform the feature representation of biological sequences into the hy…

Crosslisted article(s) found for astro-ph.SR. https://arxiv.org/list/astro-ph.SR/new
[1/1]:
- Comparing LSTM-Based Sequence-to-Sequence Forecasting Strategies for 24-Hour Solar Proton Flux Pr...
Kangwoo Yi, Bo Shen, Qin Li, Haimin Wang, Yong-Jae Moon, Jaewon Lee, Hwanhee Lee

Frequencies of letters in infinite $k$-balanced sequences
Lubom\'ira Dvo\v{r}\'akov\'a, Edita Pelantov\'a
https://arxiv.org/abs/2509.05812 https://

Frequencies of letters in infinite $k$-balanced sequences
Frequency of letters in a symbolic sequence ${\bf u}$ over a finite alphabet is one of the basic characteristics of ${\bf u}$. The notion of $k$-balancedness captures the property that the number of any letter occurring in two arbitrary factors of ${\bf u}$ of equal length differs at most by $k$. For a fixed integer $k$ and alphabet size $d\in \mathbb N$, we discuss possible frequencies of letters in $k$-balanced $d$-ary sequences. For the size $d$ of the alphabet, we introduce the notion of ba…

Products of Tribonacci Numbers that are the Products of Factorials
Pranabesh Das, J. C. Saunders
https://arxiv.org/abs/2510.06520 https://arxiv.org/pdf/251…

Products of Tribonacci Numbers that are the Products of Factorials
In 2014 Marques and Lengyel gave all of the solutions to the equation $T_n=m!$, where $T_n$ is the $n$th term of the Tribonacci sequence $0,1,1,2,4,7,13,24,\ldots$. In 2023 Alahmadi and Luca generalized their result to the equation $T_n=m_1!m_2!\cdots m_k!$ for every $k\in\mathbb{N}$, where $m_1\leq m_2\leq\ldots\leq m_k$ listing all the solutions to this equation. Here we generalize these results further and give all the solutions to $T_nT_{n+1}T_{n+2}\cdots T_{n+r}=m_1!m_2!\cdots m_k!$ and $ …

Hybrid Sequential Quantum Computing
Pranav Chandarana, Sebasti\'an V. Romero, Alejandro Gomez Cadavid, Anton Simen, Enrique Solano, Narendra N. Hegade
https://arxiv.org/abs/2510.05851

Hybrid Sequential Quantum Computing
We introduce hybrid sequential quantum computing (HSQC), a paradigm for combinatorial optimization that systematically integrates classical and quantum methods within a structured, stage-wise workflow. HSQC may involve an arbitrary sequence of classical and quantum processes, as long as the global result outperforms the standalone components. Our testbed begins with classical optimizers to explore the solution landscape, followed by quantum optimization to refine candidate solutions, and conclu…

Crosslisted article(s) found for astro-ph.SR. https://arxiv.org/list/astro-ph.SR/new
[1/1]:
- Comparing LSTM-Based Sequence-to-Sequence Forecasting Strategies for 24-Hour Solar Proton Flux Pr...
Kangwoo Yi, Bo Shen, Qin Li, Haimin Wang, Yong-Jae Moon, Jaewon Lee, Hwanhee Lee

Evolutionary Profiles for Protein Fitness Prediction
Jigang Fan, Xiaoran Jiao, Shengdong Lin, Zhanming Liang, Weian Mao, Chenchen Jing, Hao Chen, Chunhua Shen
https://arxiv.org/abs/2510.07286

Evolutionary Profiles for Protein Fitness Prediction
Predicting the fitness impact of mutations is central to protein engineering but constrained by limited assays relative to the size of sequence space. Protein language models (pLMs) trained with masked language modeling (MLM) exhibit strong zero-shot fitness prediction; we provide a unifying view by interpreting natural evolution as implicit reward maximization and MLM as inverse reinforcement learning (IRL), in which extant sequences act as expert demonstrations and pLM log-odds serve as fitne…

The limit of repetition thresholds of rich sequences
Lubom\'ira Dvo\v{r}\'akov\'a, Edita Pelantov\'a
https://arxiv.org/abs/2509.06104 https://

The limit of repetition thresholds of rich sequences
The repetition threshold of a class of sequences is the smallest number $r$ such that a sequence from the class contains no repetition with exponent $> r$. We focus on the class $\mathcal{C}_d$ of $d$-ary sequences rich in palindromes. In 2020, Currie, Mol, and Rampersad determined the repetition threshold for $\mathcal{C}_2$. In 2024, Currie, Mol and Peltomäki found the repetition threshold for $\mathcal{C}_3$ and conjectured that the repetition threshold for $\mathcal{C}_d$ tends to 2 with $…

Why Stop at Words? Unveiling the Bigger Picture through Line-Level OCR
Shashank Vempati, Nishit Anand, Gaurav Talebailkar, Arpan Garai, Chetan Arora
https://arxiv.org/abs/2508.21693

Why Stop at Words? Unveiling the Bigger Picture through Line-Level OCR
Conventional optical character recognition (OCR) techniques segmented each character and then recognized. This made them prone to error in character segmentation, and devoid of context to exploit language models. Advances in sequence to sequence translation in last decade led to modern techniques first detecting words and then inputting one word at a time to a model to directly output full words as sequence of characters. This allowed better utilization of language models and bypass error-prone…

HTMformer: Hybrid Time and Multivariate Transformer for Time Series Forecasting
Tan Wang, Yun Wei Dong, Tao Zhang, Qi Wang
https://arxiv.org/abs/2510.07084 https://

HTMformer: Hybrid Time and Multivariate Transformer for Time Series Forecasting
Transformer-based methods have achieved impressive results in time series forecasting. However, existing Transformers still exhibit limitations in sequence modeling as they tend to overemphasize temporal dependencies. This incurs additional computational overhead without yielding corresponding performance gains. We find that the performance of Transformers is highly dependent on the embedding method used to learn effective representations. To address this issue, we extract multivariate features…

On Recurrence of the Infinite Server Queue
Sergey Foss, Peter Glynn
https://arxiv.org/abs/2509.06075 https://arxiv.org/pdf/2509.06075

On Recurrence of the Infinite Server Queue
This paper concerns the recurrence structure of the infinite server queue, as viewed through the prism of the maximum dater sequence, namely the time to drain the current work in the system as seen at arrival epochs. Despite the importance of this model in queueing theory, we are aware of no complete analysis of the stability behavior of this model, especially in settings in which either or both the inter arrival and service time distributions have infinite mean. In this paper, we fully develop…

Elucidating the Design Space of Decay in Linear Attention
Zhen Qin, Xuyang Shen, Yiran Zhong
https://arxiv.org/abs/2509.05282 https://arxiv.org/pdf/2509.05…

Elucidating the Design Space of Decay in Linear Attention
This paper presents a comprehensive investigation into the decay mechanisms inherent in linear complexity sequence models. We systematically delineate the design space of decay mechanisms across four pivotal dimensions: parameterization strategy, which refers to the computational methodology for decay; parameter sharing, which involves the utilization of supplementary parameters for decay computation; decay granularity, comparing scalar versus vector-based decay; and compatibility with relative…

Dynamic Regret Bounds for Online Omniprediction with Long Term Constraints
Yahav Bechavod, Jiuyao Lu, Aaron Roth
https://arxiv.org/abs/2510.07266 https://a…

Dynamic Regret Bounds for Online Omniprediction with Long Term Constraints
We present an algorithm guaranteeing dynamic regret bounds for online omniprediction with long term constraints. The goal in this recently introduced problem is for a learner to generate a sequence of predictions which are broadcast to a collection of downstream decision makers. Each decision maker has their own utility function, as well as a vector of constraint functions, each mapping their actions and an adversarially selected state to reward or constraint violation terms. The downstream dec…

Behavior of The Extremal Bounds on the $\sigma$-Irregularity
Jasem Hamoud, Duaa Abdullah
https://arxiv.org/abs/2510.06845 https://arxiv.org/pdf/2510.06845

Behavior of The Extremal Bounds on the $σ$-Irregularity
In this paper, we establishe the extremal bounds of the topological indices -Sigma index- focusing on analyzing the sharp upper bounds and the lower bounds of the Sigma index, which is known $σ(G)=\sum_{uv\in E(G)}(d_G(u)-d_G(v))^2$. We establish precise lower and upper bounds for the Sigma index, leveraging a non-increasing degree sequence $\mathscr{D} = (d_1, d_2, \dots, d_n)$, A fundamental challenge in the study of topological indices lies in establishing precise bounds, as such findings i…

Carbon-Enhanced Dwarf Stars Are Predominantly a Halo Population
Jay Farihi, Jason L. Sanders, Sophia Lilleengen, Lewis J. Whitehouse, Denis Erkal
https://arxiv.org/abs/2509.06829

Carbon-Enhanced Dwarf Stars Are Predominantly a Halo Population
This paper reports a Galactic kinematical and dynamical analysis of 1003 main-sequence carbon stars. The sample is drawn from the Sloan Digital Sky Survey, and cross-matched with Gaia DR3 to obtain 6-dimensional positions and velocities using a Bayesian framework. The study provides the first reliable distances for a large sample of dwarf carbon stars, which are then analyzed using both space motions and actions. The results are combined with dynamical equilibrium models for the three primary G…

Non-periodicity of the sequence of the last nonzero digits of factorials and its applications to transcendence
Kohta Gejima, Fumichika Takamizo
https://arxiv.org/abs/2509.21948 …

Non-periodicity of the sequence of the last nonzero digits of factorials and its applications to transcendence
We prove that the sequence of the last nonzero digits of factorials in every integer base $b>2$ is not eventually periodic. We also extend the Adamczewski--Bugeaud criterion, originally formulated for integer base expansions, to Cantor base expansions associated with a periodic Cantor base. As an application, we show that a certain real number expressed through a Cantor base expansion is transcendental when the Cantor base and the digit sequence satisfy suitable conditions.

Golden Ratio Growth and Phase Transitions in Chromatic Counts of Circular Chord Graphs
Rogelio N. Lopez-Bonilla, Julian Allagan, Shawn M. Langley, Angel J. Clinton
https://arxiv.org/abs/2509.05845

Golden Ratio Growth and Phase Transitions in Chromatic Counts of Circular Chord Graphs
We study generalized circular chord graphs $\mathcal C^{(k)}_n$, formed from a cycle $C_n$ by adding fixed-offset chords of length $k$ and, for even $n$, diameters. Using transfer matrix methods, we derive exact formulas for 3-colorings when $k=3$: for odd $n$, we obtain \[ P(\mathcal{C}_n^{(3)},3) = L_n + 2\cos\left(\frac{2πn}{3}\right) + 2s_n + 2 \] where $L_n$ is the Lucas sequence and $(s_n)$ satisfies $s_{n+3} = -s_{n+2} - s_n$, yielding golden-ratio asymptotic growth $φ^n + O(ρ^n)$ alo…

Lithium Abundances of Main-Sequence Stars in the Old Open Cluster NGC 188: Probes of Stellar Evolution Beyond the Solar Age
Qinghui Sun, Constantine P. Deliyannis, Bruce A. Twarog, Barbara J. Anthony-Twarog
https://arxiv.org/abs/2509.02931

Lithium Abundances of Main-Sequence Stars in the Old Open Cluster NGC 188: Probes of Stellar Evolution Beyond the Solar Age
We present lithium abundances for 119 main-sequence stars in the 6.3 Gyr open cluster NGC 188, using high-resolution, high signal-to-noise ratio spectra from WIYN/Hydra. We observe the stars over multiple nights and measure radial velocities for each night, which we combine with Gaia proper motions to identify multiplicity and cluster membership. We identify 95 single members, 14 binary members, 9 members with uncertain multiplicity, and 1 single likely member. We determine effective temperatur…

SpikingBrain Technical Report: Spiking Brain-inspired Large Models
Yuqi Pan, Yupeng Feng, Jinghao Zhuang, Siyu Ding, Zehao Liu, Bohan Sun, Yuhong Chou, Han Xu, Xuerui Qiu, Anlin Deng, Anjie Hu, Peng Zhou, Man Yao, Jibin Wu, Jian Yang, Guoliang Sun, Bo Xu, Guoqi Li
https://arxiv.org/abs/2509.05276

SpikingBrain Technical Report: Spiking Brain-inspired Large Models
Mainstream Transformer-based large language models face major efficiency bottlenecks: training computation scales quadratically with sequence length, and inference memory grows linearly, limiting long-context processing. Building large models on non-NVIDIA platforms also poses challenges for stable and efficient training. To address this, we introduce SpikingBrain, a family of brain-inspired models designed for efficient long-context training and inference. SpikingBrain leverages the MetaX GPU …

TASP: Topology-aware Sequence Parallelism
Yida Wang (Capital Normal University, Infinigence-AI), Ke Hong (Tsinghua University, Infinigence-AI), Xiuhong Li (Infinigence-AI), Yuanchao Xu (Capital Normal University), Wenxun Wang (Tsinghua University), Guohao Dai (Infinigence-AI, Shanghai Jiao Tong University), Yu Wang (Tsinghua University)
https://

TASP: Topology-aware Sequence Parallelism
Long-context large language models (LLMs) face constraints due to the quadratic complexity of the self-attention mechanism. The mainstream sequence parallelism (SP) method, Ring Attention, attempts to solve this by distributing the query into multiple query chunks across accelerators and enable each Q tensor to access all KV tensors from other accelerators via the Ring AllGather communication primitive. However, it exhibits low communication efficiency, restricting its practical applicability. …

Discovery of the pre-main-sequence eclipsing binary MML 48
Y. G\'omez Maqueo Chew, L. Hebb, H. C. Stempels, F. M. Walter, D. J. James, G. A. Feiden, R. Petrucci, T. Lister, I. Baraffe, M. Brodheim, F. Faedi, D. R. Anderson, R. A. Street, C. Hellier, K. G. Stassun
https://arxiv.org/abs/2509.03831

Discovery of the pre-main-sequence eclipsing binary MML 48
We present the discovery of the eclipsing binary MML 48, which is a member of Upper Centaurus Lupus, has an associated age of 16 Myr, and is composed of two young, low-mass stars. We used space- and ground-based observations to characterize the system with both time-series photometry and spectroscopy. Given the extreme mass ratio between the stars, q_EB = 0.209 +- 0.014, we modeled a single-lined spectroscopic and eclipsing binary system. The orbital period, 2.0171068 +- 0.0000004 d, is measure…

Spiking Decision Transformers: Local Plasticity, Phase-Coding, and Dendritic Routing for Low-Power Sequence Control
Vishal Pandey, Debasmita Biswas
https://arxiv.org/abs/2508.21505

Spiking Decision Transformers: Local Plasticity, Phase-Coding, and Dendritic Routing for Low-Power Sequence Control
Reinforcement learning agents based on Transformer architectures have achieved impressive performance on sequential decision-making tasks, but their reliance on dense matrix operations makes them ill-suited for energy-constrained, edge-oriented platforms. Spiking neural networks promise ultra-low-power, event-driven inference, yet no prior work has seamlessly merged spiking dynamics with return-conditioned sequence modeling. We present the Spiking Decision Transformer (SNN-DT), which embeds Lea…