Tootfinder

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization
Dingyi Rong, Haotian Lu, Wenzhuo Zheng, Fan Zhang, Shuangjia Zheng, Ning Liu
https://arxiv.org/abs/2506.09496

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization
Designing protein sequences with optimal energetic stability is a key challenge in protein inverse folding, as current deep learning methods are primarily trained by maximizing sequence recovery rates, often neglecting the energy of the generated sequences. This work aims to overcome this limitation by developing a model that directly generates low-energy, stable protein sequences. We propose EnerBridge-DPO, a novel inverse folding framework focused on generating low-energy, high-stability prot…

Predicting function of evolutionarily implausible DNA sequences
Shiyu Jiang, Xuyin Liu, Zitong Jerry Wang
https://arxiv.org/abs/2506.10271 https://

Predicting function of evolutionarily implausible DNA sequences
Genomic language models (gLMs) show potential for generating novel, functional DNA sequences for synthetic biology, but doing so requires them to learn not just evolutionary plausibility, but also sequence-to-function relationships. We introduce a set of prediction tasks called Nullsettes, which assesses a model's ability to predict loss-of-function mutations created by translocating key control elements in synthetic expression cassettes. Across 12 state-of-the-art models, we find that mutation…

Accelerating quantum adiabatic evolution with $\pi$-pulse sequences
Tonghao Xing, Jiang Zhang, Guilu Long
https://arxiv.org/abs/2506.09320 https://

Accelerating quantum adiabatic evolution with $π$-pulse sequences
In quantum information processing, the development of fast and robust control schemes remains a central challenge. Although quantum adiabatic evolution is inherently robust against control errors, it typically demands long evolution times. In this work, we propose to achieve rapid adiabatic evolution, in which nonadiabatic transitions induced by fast changes in the system Hamiltonian are mitigated by flipping the nonadiabatic transition matrix using $π$ pulses. This enables a faster realizatio…

On the Law of the Iterated Logarithm for m-dependent stationary random variables under sub-linear expectations
Wang-Yun Gu, Li-Xin Zhang
https://arxiv.org/abs/2506.10522

On the Law of the Iterated Logarithm for m-dependent stationary random variables under sub-linear expectations
This paper explores the Law of the Iterated Logarithm (LIL) for $m$-dependent sequences under the framework of sub-linear expectations. We first extend existing LIL results to sequences of independent, non-identically distributed random variables under sub-linear expectations. This extension serves as a crucial intermediary step, facilitating the subsequent establishment of the LIL for $m$-dependent stationary sequences. On the other hand, we also establish necessary conditions for $m$-dependen…

Replaced article(s) found for cs.FL. https://arxiv.org/list/cs.FL/new/
[1/1]:
A Family of Sequences Generalizing the Thue Morse and Rudin Shapiro Sequences

Localization sequences for logarithmic topological cyclic homology
John Rognes, Steffen Sagave, Christian Schlichtkrull
https://arxiv.org/abs/2506.08492 ht…

Localization sequences for logarithmic topological cyclic homology
We introduce the notion of an E_k-ring with prelogarithmic structure, define logarithmic topological Hochschild homology and logarithmic topological cyclic homology in this context, and establish localization sequences for these theories. Our approach is based on Thom R-algebras. It extends and strengthens our earlier work on the subject in several regards. Our examples include the fraction field of topological K-theory, the existence of which was suggested by calculations by Ausoni and the fir…

Learning Obfuscations Of LLM Embedding Sequences: Stained Glass Transform
Jay Roberts, Kyle Mylonakis, Sidhartha Roy, Kaan Kale
https://arxiv.org/abs/2506.09452

Learning Obfuscations Of LLM Embedding Sequences: Stained Glass Transform
The high cost of ownership of AI compute infrastructure and challenges of robust serving of large language models (LLMs) has led to a surge in managed Model-as-a-service deployments. Even when enterprises choose on-premises deployments, the compute infrastructure is typically shared across many teams in order to maximize the return on investment. In both scenarios the deployed models operate only on plaintext data, and so enterprise data owners must allow their data to appear in plaintext on a …

Attention on flow control: transformer-based reinforcement learning for lift regulation in highly disturbed flows
Zhecheng Liu, Jeff D. Eldredge
https://arxiv.org/abs/2506.10153

Attention on flow control: transformer-based reinforcement learning for lift regulation in highly disturbed flows
A linear flow control strategy designed for weak disturbances may not remain effective in sequences of strong disturbances due to nonlinear interactions, but it is sensible to leverage it for developing a better strategy. In the present study, we propose a transformer-based reinforcement learning (RL) framework to learn an effective control strategy for regulating aerodynamic lift in gust sequences via pitch control. The transformer addresses the challenge of partial observability from limited …

Stability of the Morse Index for the $p$-harmonic Approximation of Harmonic Maps into Homogeneous Spaces
Dominik Schlagenhauf
https://arxiv.org/abs/2506.10761

Stability of the Morse Index for the $p$-harmonic Approximation of Harmonic Maps into Homogeneous Spaces
In the joint work of the author with Da Lio and Rivière (Morse Index Stability for Sequences of Sacks-Uhlenbeck Maps into a Sphere) we studied the stability of the Morse index for Sacks-Uhlenbeck sequences into spheres as $p\searrow2$. These are critical points of the energy $E_p(u) := \int_Σ\left( 1+|\nabla u|^2\right)^{p/2} \ dvol_Σ,$ where $u:Σ\rightarrow S^n$ is a map from a closed Riemannian surface $Σ$ into a sphere $ S^n$. In this paper we extend the results found in our p…

The Milky Way in context: The formation of galactic discs and chemical sequences from a cosmological perspective
Matthew D. A. Orkney, Chervin F. P. Laporte, Robert J. J. Grand, Volker Springel
https://arxiv.org/abs/2506.07038

The Milky Way in context: The formation of galactic discs and chemical sequences from a cosmological perspective
We study the formation of chemical sequences in the stellar disc of Milky Way (MW)-mass galaxies in a full cosmological context with the Auriga simulations. We focus on the conditions giving rise to bi-modal $α$-chemistry in the MW disc and the potential influence of mergers (e.g. Gaia-Enceladus, GSE). We find a wide diversity of chemical sequences, without correlation between the emergence of dichotomous $α$-chemistry and GSE-like mergers. The transition between multiple $α$-sequences is se…

Hearing Hands: Generating Sounds from Physical Interactions in 3D Scenes
Yiming Dou, Wonseok Oh, Yuqing Luo, Antonio Loquercio, Andrew Owens
https://arxiv.org/abs/2506.09989

Hearing Hands: Generating Sounds from Physical Interactions in 3D Scenes
We study the problem of making 3D scene reconstructions interactive by asking the following question: can we predict the sounds of human hands physically interacting with a scene? First, we record a video of a human manipulating objects within a 3D scene using their hands. We then use these action-sound pairs to train a rectified flow model to map 3D hand trajectories to their corresponding audio. At test time, a user can query the model for other actions, parameterized as sequences of hand pos…

A class of Nakayama algebras with a braid group action on $\tau$-exceptional sequences
H{\aa}vard Utne Terland
https://arxiv.org/abs/2507.07608 https://

A class of Nakayama algebras with a braid group action on $τ$-exceptional sequences
We show that the mutation of $τ$-exceptional sequences over cyclic Nakayama algebras $Λ$ where all projectives have length exactly $|Λ|$ respects the braid group relations.

Approximation by uniformly distributed sequences
Gerardo Gonz\'alez Robert, Mumtaz Hussain, Nikita Shulga, Benjamin Ward
https://arxiv.org/abs/2507.06583

Approximation by uniformly distributed sequences
We consider approximation properties of real points by uniformly distributed sequences. Under some assumptions on the approximation functions, we prove a Khintchine-type $0$-$1$ dichotomy law. We establish a new connection between uniform distribution and the ubiquity property. Namely, we show that a bound on the discrepancy of the sequence implies the ubiquity property, which helps to obtain divergence results. We further obtain Hausdorff dimension results for weighted sets. The key tools in p…

Preorders on maximal chains: hyperplane arrangements, Cambrian lattices, and maximal green sequences
Mikhail Gorsky, Nicholas J. Williams
https://arxiv.org/abs/2506.08858

Preorders on maximal chains: hyperplane arrangements, Cambrian lattices, and maximal green sequences
We study preorders on (equivalence classes of) maximal chains in the general context of polygonal lattices endowed with suitably nice edge labellings. We show that, given a quotient of polygonal lattices, such edge labellings descend to the quotient, and that there is an induced order-preserving surjective map on the preordered sets of equivalence classes of maximal chains. Under a natural condition ensuring that the domain is a poset, the map is a contraction of preordered sets. We apply this …

Pseudo-random sequences for low-cost operando impedance measurements of Li-ion batteries
Jussi Sihvo, No\"el Hallemans, Ai Hui Tan, David A. Howey, Stephen. R. Duncan, Tomi Roinila
https://arxiv.org/abs/2506.07519

Pseudo-random sequences for low-cost operando impedance measurements of Li-ion batteries
Operando impedance measurements are promising for monitoring batteries in the field. In this work, we present pseudo-random sequences for low-cost operando battery impedance measurements. The quadratic-residue ternary sequence and direct-synthesis ternary sequence exhibit specific properties related to eigenvectors of the discrete Fourier transform matrix that allow computationally efficient compensation for drifts and transients in operando impedance measurements. We describe the application o…

BEAST: Efficient Tokenization of B-Splines Encoded Action Sequences for Imitation Learning
Hongyi Zhou, Weiran Liao, Xi Huang, Yucheng Tang, Fabian Otto, Xiaogang Jia, Xinkai Jiang, Simon Hilber, Ge Li, Qian Wang, \"Omer Erdin\c{c} Ya\u{g}murlu, Nils Blank, Moritz Reuss, Rudolf Lioutikov
https://arxiv.org/abs/2506.06072

BEAST: Efficient Tokenization of B-Splines Encoded Action Sequences for Imitation Learning
We present the B-spline Encoded Action Sequence Tokenizer (BEAST), a novel action tokenizer that encodes action sequences into compact discrete or continuous tokens using B-splines. In contrast to existing action tokenizers based on vector quantization or byte pair encoding, BEAST requires no separate tokenizer training and consistently produces tokens of uniform length, enabling fast action sequence generation via parallel decoding. Leveraging our B-spline formulation, BEAST inherently ensures…

Tangent Cones of Concatenated Numerical Semigroups
Ranjana Mehta, Joydip Saha, Indranath Sengupta
https://arxiv.org/abs/2506.09400 https://

Tangent Cones of Concatenated Numerical Semigroups
We study the tangent cone at the origin and the Hilbert series for a family of numerical semigroups generated by concatenation of arithmetic sequences. We prove that all the concatenation classes have Cohen-Macaulay tangent cones except the symmetric class, however, the symmetric class does satisfy Rossi's conjecture.

Dirichlet kernel density estimation for strongly mixing sequences on the simplex
Hanen Daayeb, Salah Khardani, Fr\'ed\'eric Ouimet
https://arxiv.org/abs/2506.08816

Dirichlet kernel density estimation for strongly mixing sequences on the simplex
This paper investigates the theoretical properties of Dirichlet kernel density estimators for compositional data supported on simplices, for the first time addressing scenarios involving time-dependent observations characterized by strong mixing conditions. We establish rigorous results for the asymptotic normality and mean squared error of these estimators, extending previous findings from the independent and identically distributed (iid) context to the more general setting of strongly mixing …

Diffusion Sequence Models for Enhanced Protein Representation and Generation
Logan Hallee, Nikolaos Rafailidis, David B. Bichara, Jason P. Gleghorn
https://arxiv.org/abs/2506.08293

Diffusion Sequence Models for Enhanced Protein Representation and Generation
Proteins are fundamental to biology, executing diverse functions through complex physicochemical interactions, and they hold transformative potential across medicine, materials science, and environmental applications. Protein Language Models (pLMs) aim to unlock insights from the vast space of unlabeled protein sequences by learning rich, semantic representations from primary sequences via masked language modeling. However, these models typically exhibit limited generative capacity. In this wor…

This https://arxiv.org/abs/2408.08208 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

LLM4DSR: Leveraging Large Language Model for Denoising Sequential Recommendation
Sequential Recommenders generate recommendations based on users' historical interaction sequences. However, in practice, these collected sequences are often contaminated by noisy interactions, which significantly impairs recommendation performance. Accurately identifying such noisy interactions without additional information is particularly challenging due to the absence of explicit supervisory signals indicating noise. Large Language Models (LLMs), equipped with extensive open knowledge and se…

Self-organized first-order transition from foreshock to mainshock in earthquake sequences induced by heat, fluid pressure, and porosity
Takehito Suzuki, Hiroshi Matsukawa
https://arxiv.org/abs/2507.05546

Self-organized first-order transition from foreshock to mainshock in earthquake sequences induced by heat, fluid pressure, and porosity
Earthquake cycles are studied by taking into account the interactions among slip, fluid pressure, temperature, and porosity on the fault planes, which are known to play a crucial role in earthquake dynamics. The spring-block model with a single block is employed. A first-order transition from foreshock to mainshock occurring spontaneously in earthquake sequences is discovered both analytically and numerically. This transition is induced by these interactions. It is shown that the function of th…

Online Regularized Learning Algorithms in RKHS with $\beta$- and $\phi$-Mixing Sequences
Priyanka Roy, Susanne Saminger-Platz
https://arxiv.org/abs/2507.05929

Online Regularized Learning Algorithms in RKHS with $β$- and $ϕ$-Mixing Sequences
In this paper, we study an online regularized learning algorithm in a reproducing kernel Hilbert spaces (RKHS) based on a class of dependent processes. We choose such a process where the degree of dependence is measured by mixing coefficients. As a representative example, we analyze a strictly stationary Markov chain, where the dependence structure is characterized by the \(ϕ\)- and \(β\)-mixing coefficients. Under these assumptions, we derive probabilistic upper bounds as well as convergence…

Existence, equivalence and spectrality of infinite convolutions in $\R^d$
Junjie Miao, Hongbo Zhao
https://arxiv.org/abs/2506.06670 https://

Existence, equivalence and spectrality of infinite convolutions in $\R^d$
In this paper, we study existence, equivalence and spectrality of infinite convolutions which may not be compactly supported in $d$-dimensional Euclidean space by manipulating various techniques in probability theory. First, we define the equivalent sequences, and we prove that the infinite convolutions converges simultaneously if they are generated by equivalent sequences. Moreover, the equi-positivity keeps unchanged for infinite convolutions generated by equivalent sequences. Next, we study …

Effective criteria for entanglement witnesses in small dimensions
{\L}ukasz Grzelka, {\L}ukasz Skowronek, Karol \.Zyczkowski
https://arxiv.org/abs/2506.09298

Effective criteria for entanglement witnesses in small dimensions
We present an effective set of necessary and sufficient criteria for block-positivity of matrices of order $4$ over $\mathbb{C}$. The approach is based on Sturm sequences and quartic polynomial positivity conditions presented in recent literature. The procedure allows us to test whether a given $4\times 4$ complex matrix corresponds to an entanglement witness, and it is exact when the matrix coefficients belong to the rationals, extended by $\mathrm{i}$. The method can be generalized to $\mathc…

Low-Perplexity LLM-Generated Sequences and Where To Find Them
Arthur Wuhrmann, Anastasiia Kucherenko, Andrei Kucharavy
https://arxiv.org/abs/2507.01844 htt…

Low-Perplexity LLM-Generated Sequences and Where To Find Them
As Large Language Models (LLMs) become increasingly widespread, understanding how specific training data shapes their outputs is crucial for transparency, accountability, privacy, and fairness. To explore how LLMs leverage and replicate their training data, we introduce a systematic approach centered on analyzing low-perplexity sequences - high-probability text spans generated by the model. Our pipeline reliably extracts such long sequences across diverse topics while avoiding degeneration, the…

Note on the negative base xor sequence $n\oplus_{-b}(-n)$
H A Verrill
https://arxiv.org/abs/2506.09509 https://arxiv.org/pdf/2506.095…

Note on the negative base xor sequence $n\oplus_{-b}(-n)$
We prove a relationship between certain integer expressions involving operators similar to the binary exclusive or. This gives a proof and generalization of a result conjectured about sequence A178729 in Sloane's Online Encyclopedia of Integer Sequences. We use transducers to prove this result.

Inter-event time statistics of earthquakes as a gauge of volcano activity
Sumanta Kundu, Anca Opris, Yosuke Aoki, Takahiro Hatano
https://arxiv.org/abs/2506.09203

Inter-event time statistics of earthquakes as a gauge of volcano activity
The probability distribution of inter-event time (IET) between two consecutive earthquakes is a measure for the uncertainty in the occurrence time of earthquakes in a region of interest. It is well known that the IET distribution for regular earthquakes is commonly characterized by a power law with the exponent of 0.3. However, less is known about other classes of earthquakes, such as volcanic earthquakes, which do not manifest mainshock-aftershocks sequences. Since volcanic earthquakes are cau…

Morse Index Stability of Branched Willmore Immersions
Alexis Michelat
https://arxiv.org/abs/2506.09005 https://arxiv.org/pdf/2506.090…

Morse Index Stability of Branched Willmore Immersions
We show the Morse index stability for sequences of Willmore immersions of bounded energy without assuming that the limiting immersion and the bubbles are free of branch points.

Chance and Mass Interpretations of Probabilities in Markov Decision Processes (Extended Version)
Yun Chen Tsai, Kittiphon Phalakarn, S. Akshay, Ichiro Hasuo
https://arxiv.org/abs/2506.10377

Chance and Mass Interpretations of Probabilities in Markov Decision Processes (Extended Version)
Markov decision processes (MDPs) are a popular model for decision-making in the presence of uncertainty. The conventional view of MDPs in verification treats them as state transformers with probabilities defined over sequences of states and with schedulers making random choices. An alternative view, especially well-suited for modeling dynamical systems, defines MDPs as distribution transformers with schedulers distributing probability masses. Our main contribution is a unified semantical framew…

A Probabilistic Framework for Imputing Genetic Distances in Spatiotemporal Pathogen Models
Haley Stone, Jing Du, Hao Xue, Matthew Scotch, David Heslop, Andreas Z\"ufle, Chandini Raina MacIntyre, Flora Salim
https://arxiv.org/abs/2506.09076

A Probabilistic Framework for Imputing Genetic Distances in Spatiotemporal Pathogen Models
Pathogen genome data offers valuable structure for spatial models, but its utility is limited by incomplete sequencing coverage. We propose a probabilistic framework for inferring genetic distances between unsequenced cases and known sequences within defined transmission chains, using time-aware evolutionary distance modeling. The method estimates pairwise divergence from collection dates and observed genetic distances, enabling biologically plausible imputation grounded in observed divergence …

Channel Estimation with Asynchronous Reception for User-Centric Cell-Free MIMO Systems
Xuyang Sun, Hussein A. Ammar, Raviraj Adve, Israfil Bahceci, Gary Boudreau
https://arxiv.org/abs/2506.05496

Channel Estimation with Asynchronous Reception for User-Centric Cell-Free MIMO Systems
The user-centric, cell-free wireless network is a promising next-generation communication system, but signal synchronization issues arise due to distributed access points and lack of cellular structure. We propose a novel method to recover synchronous pilot reception by introducing new pilot sequences and a matched filter window, enabling orthogonality even with asynchronous reception. Our approach mimics synchronous transmission by extending training sequences. Analysis shows asynchronous rece…

Controllable Sequences of Minimal Length for Discrete-Time Switched Linear Control Systems
Paolo Mason (L2S), Antoine Girard (L2S)
https://arxiv.org/abs/2507.04731

Controllable Sequences of Minimal Length for Discrete-Time Switched Linear Control Systems
In this paper, we provide a novel characterization of the reachable set of discrete-time switched linear control systems and a Kalman-type criterion for controllability, assuming that the switching parameter can be used as a control parameter in addition to the actual control variable. For controllable switched linear control systems it turns out that there always exists a switching sequence such that the reachable set of the corresponding linear time-variant system covers the whole state space…

Made a pass on this script, and see where I have two scenes/sequences still to write. But really liked reading it after a long time away from it. I needed that today.
#script #film #screenwriting

Protriever: End-to-End Differentiable Protein Homology Search for Fitness Prediction
Ruben Weitzman, Peter M{\o}rch Groth, Lood Van Niekerk, Aoi Otani, Yarin Gal, Debora Marks, Pascal Notin
https://arxiv.org/abs/2506.08954

Protriever: End-to-End Differentiable Protein Homology Search for Fitness Prediction
Retrieving homologous protein sequences is essential for a broad range of protein modeling tasks such as fitness prediction, protein design, structure modeling, and protein-protein interactions. Traditional workflows have relied on a two-step process: first retrieving homologs via Multiple Sequence Alignments (MSA), then training models on one or more of these alignments. However, MSA-based retrieval is computationally expensive, struggles with highly divergent sequences or complex insertions &…

PenTest2.0: Towards Autonomous Privilege Escalation Using GenAI
Haitham S. Al-Sinani, Chris J. Mitchell
https://arxiv.org/abs/2507.06742 https://

PenTest2.0: Towards Autonomous Privilege Escalation Using GenAI
Ethical hacking today relies on highly skilled practitioners executing complex sequences of commands, which is inherently time-consuming, difficult to scale, and prone to human error. To help mitigate these limitations, we previously introduced 'PenTest++', an AI-augmented system combining automation with generative AI supporting ethical hacking workflows. However, a key limitation of PenTest++ was its lack of support for privilege escalation, a crucial element of ethical hacking. In this paper…

On the Use of Bj\"orck Sequences in LEO-based PNT Systems
Harish K. Dureppagari, Chiranjib Saha, R. Michael Buehrer, Harpreet S. Dhillon
https://arxiv.org/abs/2506.00706

On the Use of Björck Sequences in LEO-based PNT Systems
In this paper, we investigate the use of Björck sequences, a class of constant amplitude zero autocorrelation (CAZAC) sequences, as a potential candidate for the design of positioning reference signals (PRS) in Low Earth Orbit (LEO)-based positioning, navigation, and timing (PNT) systems. Unlike legacy systems such as Global Navigation Satellite Systems (GNSS) or terrestrial networks (TNs), LEO-based systems experience large Doppler shifts and delay spreads, where traditional orthogonalization…

Replaced article(s) found for cs.DM. https://arxiv.org/list/cs.DM/new
[1/1]:
- On the order of the shortest solution sequences for the pebble motion problems
Tomoki Nakamigawa, Tadashi Sakuma

Confidence sequences with informative, bounded-influence priors
Stefano Cortinovis, Valentin Kilian, Fran\c{c}ois Caron
https://arxiv.org/abs/2506.22925 ht…

Confidence sequences with informative, bounded-influence priors
Confidence sequences are collections of confidence regions that simultaneously cover the true parameter for every sample size at a prescribed confidence level. Tightening these sequences is of practical interest and can be achieved by incorporating prior information through the method of mixture martingales. However, confidence sequences built from informative priors are vulnerable to misspecification and may become vacuous when the prior is poorly chosen. We study this trade-off for Gaussian o…

SZ Sequences: Binary-Based $(0, 2^q)$-Sequences
Abdalla G. M. Ahmed, Matt Pharr, Victor Ostromoukhov, Hui Huang
https://arxiv.org/abs/2505.20434 https://…

SZ Sequences: Binary-Based $(0, 2^q)$-Sequences
Low-discrepancy sequences have seen widespread adoption in computer graphics thanks to their superior convergence rates. Since rendering integrals often comprise products of lower-dimensional integrals, recent work has focused on developing sequences that are also well-distributed in lower-dimensional projections. To this end, we introduce a novel construction of binary-based (0, 4)-sequences; that is, progressive fully multi-stratified sequences of 4D points, and extend the idea to higher powe…

Introduction to the theory of generalized locally Toeplitz sequences and its applications
Carlo Garoni
https://arxiv.org/abs/2506.02151 https://

Introduction to the theory of generalized locally Toeplitz sequences and its applications
The theory of generalized locally Toeplitz (GLT) sequences was conceived as an apparatus for computing the spectral distribution of matrices arising from the numerical discretization of differential equations (DEs). The purpose of this review is to introduce the reader to the theory of GLT sequences and to present some of its applications to the computation of the spectral distribution of DE discretization matrices. We mainly focus on the applications, whereas the theory is presented in a self-…

Ordering According to Size of Disks in a Narrow Channel
Dan Liu, Michael Karbach, Gerhard M\"uller
https://arxiv.org/abs/2507.07266 https://

Ordering According to Size of Disks in a Narrow Channel
A long and narrow channel confines disks of two sizes. The disks are randomly agitated in a widened channel under moderate pressure, then jammed according to a tunable protocol. We present exact results that characterize jammed macrostates (volume, entropy, jamming patterns). The analysis divides jammed disk sequences into overlapping tiles out of which statistically interacting quasiparticles are constructed. The fractions of small and large disks are controlled by a chemical potential adapted…

Binomial Convolution of Sequences
Kunle Adegoke
https://arxiv.org/abs/2507.04179 https://arxiv.org/pdf/2507.04179

Binomial Convolution of Sequences
Given any two sequences of complex numbers, we establish simple relations between their binomial convolution and the binomial convolution of their individual binomial transforms. We employ these relations to derive new identities involving Fibonacci numbers, Bernoulli numbers, harmonic numbers, odd harmonic numbers and binomial coefficients.

Towards an Analysis of Proofs in Arithmetic
Alexander Leitsch, Anela Loli\'c, Stella Mahler
https://arxiv.org/abs/2506.05837 https://

Towards an Analysis of Proofs in Arithmetic
Inductive proofs can be represented as proof schemata, i.e. as parameterized sequences of proofs defined in a primitive recursive way. Applications of proof schemata can be found in the area of automated proof analysis where the schemata admit (schematic) cut-elimination and the construction of Herbrand systems. This work focuses on the expressivity of proof schemata. We show that proof schemata can simulate primitive recursive arithmetic. The translation of proofs in arithmetic to proof schema…

It's like a 3D puzzle. This 18th-century Italian safe has the most unique unlocking sequences ever.

Sequences of LCD AG codes and LCP of AG Codes attaining the Tsfasman-Vladut-Zink bound
Adler Marques, Luciane Quoos
https://arxiv.org/abs/2505.23937 https:…

Sequences of LCD AG codes and LCP of AG Codes attaining the Tsfasman-Vladut-Zink bound
Since Massey introduced linear complementary dual (LCD) codes in 1992 and Bhasin et al. later formalized linear complementary pairs (LCPs) of codes - structures with important cryptographic applications - these code families have attracted significant interest. We construct infinite sequences $(C_i)_{i \geq 1}$ of LCD codes and of LCPs $(C', D')_{i \geq 1}$ over $\mathbb{F}_{q^2}$ obtained from the Garcia-Stichtenoth tower of function fields, where we describe suitable non-special divisors of s…

This https://arxiv.org/abs/2405.10723 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Eddeep: Fast eddy-current distortion correction for diffusion MRI with deep learning
Modern diffusion MRI sequences commonly acquire a large number of volumes with diffusion sensitization gradients of differing strengths or directions. Such sequences rely on echo-planar imaging (EPI) to achieve reasonable scan duration. However, EPI is vulnerable to off-resonance effects, leading to tissue susceptibility and eddy-current induced distortions. The latter is particularly problematic because it causes misalignment between volumes, disrupting downstream modelling and analysis. The e…

This https://arxiv.org/abs/2505.15992 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDS_…

On the Complexity of Finding Approximate LCS of Multiple Strings
Finding an Approximate Longest Common Substring (ALCS) within a given set $S=\{s_1,s_2,\ldots,s_m\}$ of $m \ge 2$ strings is a problem of particular importance in computational biology (e.g., identifying related mutations across multiple genetic sequences). In this paper, we study several ALCS problems that, for given integers $k$ and $t \le m$, require finding a longest string $u$ -- or a longest substring $u$ of any string in $S$ -- that lies within distance $k$ of at least one substring in $…

HiBerNAC: Hierarchical Brain-emulated Robotic Neural Agent Collective for Disentangling Complex Manipulation
Hongjun Wu, Heng Zhang, Pengsong Zhang, Jin Wang, Cong Wang
https://arxiv.org/abs/2506.08296

HiBerNAC: Hierarchical Brain-emulated Robotic Neural Agent Collective for Disentangling Complex Manipulation
Recent advances in multimodal vision-language-action (VLA) models have revolutionized traditional robot learning, enabling systems to interpret vision, language, and action in unified frameworks for complex task planning. However, mastering complex manipulation tasks remains an open challenge, constrained by limitations in persistent contextual memory, multi-agent coordination under uncertainty, and dynamic long-horizon planning across variable sequences. To address this challenge, we propose \…

This https://arxiv.org/abs/2407.00976 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

ODIN: Open Data In Neurophysiology: Advancements, Solutions & Challenges
Across the life sciences, an ongoing effort over the last 50 years has made data and methods more reproducible and transparent. This openness has led to transformative insights and vastly accelerated scientific progress. For example, structural biology and genomics have undertaken systematic collection and publication of protein sequences and structures over the past half-century, and these data have led to scientific breakthroughs that were unthinkable when data collection first began. We beli…

Go to Zero: Towards Zero-shot Motion Generation with Million-scale Data
Ke Fan, Shunlin Lu, Minyue Dai, Runyi Yu, Lixing Xiao, Zhiyang Dou, Junting Dong, Lizhuang Ma, Jingbo Wang
https://arxiv.org/abs/2507.07095

Go to Zero: Towards Zero-shot Motion Generation with Million-scale Data
Generating diverse and natural human motion sequences based on textual descriptions constitutes a fundamental and challenging research area within the domains of computer vision, graphics, and robotics. Despite significant advancements in this field, current methodologies often face challenges regarding zero-shot generalization capabilities, largely attributable to the limited size of training datasets. Moreover, the lack of a comprehensive evaluation framework impedes the advancement of this t…

This https://arxiv.org/abs/2412.13751 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Notions of entropy for unitary representations
Several notions of entropy are studied widely in the ergodic theory of probability-preserving actions of countable groups. These include the generalization of Kolmogorov--Sinai entropy for amenable groups using Følner sequences, percolative entropy entropy for general countable groups, and Bowen's sofic entropy for sofic groups. In this work we pursue these notions across the analogy between ergodic theory and representation theory. We arrive at new quantities associated to unitary represent…

New orientable sequences
Chris J Mitchell, Peter R Wild
https://arxiv.org/abs/2507.02526 https://arxiv.org/pdf/2507.02526

New orientable sequences
Orientable sequences of order n are infinite periodic sequences with symbols drawn from a finite alphabet of size k with the property that any particular subsequence of length n occurs at most once in a period in either direction. They were introduced in the early 1990s in the context of possible applications in position sensing. Bounds on the period of such sequences and a range of methods of construction have been devised, although apart from very small cases a significant gap remains between…

A Linear Time Algorithm for Finding Minimum Flip Sequences between Plane Spanning Paths in Convex Point Sets
Oswin Aichholzer, Joseph Dorfer
https://arxiv.org/abs/2507.02740

A Linear Time Algorithm for Finding Minimum Flip Sequences between Plane Spanning Paths in Convex Point Sets
We provide a linear time algorithm to determine the flip distance between two plane spanning paths on a point set in convex position. At the same time, we show that the happy edge property does not hold in this setting. This has to be seen in contrast to several results for reconfiguration problems where the absence of the happy edge property implies algorithmic hardness of the flip distance problem. Further, we show that our algorithm can be adapted for (1) compatible flips (2) local flips and…

More than One Step at a Time: Designing Procedural Feedback for Non-visual Makeup Routines
Franklin Mingzhe Li, Akihiko Oharazawa, Chloe Qingyu Zhu, Misty Fan, Daisuke Sato, Chieko Asakawa, Patrick Carrington
https://arxiv.org/abs/2507.03942

More than One Step at a Time: Designing Procedural Feedback for Non-visual Makeup Routines
Makeup plays a vital role in self-expression, identity, and confidence - yet remains an underexplored domain for assistive technology, especially for people with vision impairments. While existing tools support isolated tasks such as color identification or product labeling, they rarely address the procedural complexity of makeup routines: coordinating step sequences, managing product placement, and assessing the final look with accessible feedback. To understand the real-world process, we cond…

Conformance Checking for Less: Efficient Conformance Checking for Long Event Sequences
Eli Bogdanov, Izack Cohen, Avigdor Gal
https://arxiv.org/abs/2505.21506

Conformance Checking for Less: Efficient Conformance Checking for Long Event Sequences
Long event sequences (termed traces) and large data logs that originate from sensors and prediction models are becoming increasingly common in our data-rich world. In such scenarios, conformance checking-validating a data log against an expected system behavior (the process model) can become computationally infeasible due to the exponential complexity of finding an optimal alignment. To alleviate scalability challenges for this task, we propose ConLES, a sliding-window conformance checking appr…

Frequency-Domain Joint Monitoring of Differential Group Delay and Dependent Loss of Optical Singleand Few-Mode Fiber Channels Based on CAZAC Sequences
Linsheng Fan, Gao Ye, Zhongliang Sun, Lingguo Cao, Hao Shi, Jianwei Tang, Shunfeng Wang, Hengying Xu, Chenglin Bai, Jian Zhao, Weisheng Hu, Jinlong Wei
https://arxiv.org/abs/2505.…

Frequency-Domain Joint Monitoring of Differential Group Delay and Dependent Loss of Optical Singleand Few-Mode Fiber Channels Based on CAZAC Sequences
This paper addresses the challenges of monitoring optical-fiber channels subject to complex, multidimensional impairments-such as dynamic interference across polarization or modal dimensions-where conventional methods suffer from high equipment costs, poor impairment discrimination and limited scalability. We propose an in-service, frequency-domain joint monitoring scheme based on constant-amplitude zero-autocorrelation (CAZAC) sequences. Exploiting their flat spectra and ideal autocorrelation,…

Preparing spin-squeezed states in Rydberg atom arrays via quantum optimal control
Edison S. Carrera, Harold Erbin, Gr\'egoire Misguich
https://arxiv.org/abs/2507.07875

Preparing spin-squeezed states in Rydberg atom arrays via quantum optimal control
We present a quantum optimal control protocol to generate highly spin-squeezed states in Rydberg atom arrays coupled via Ising-type Van der Waals interactions. Using gradient-based optimization techniques we construct time-dependent pulse sequences that steer an initial product state toward highly entangled, spin-squeezed states with predefined magnetization and squeezing axes. We focus on the Wineland parameter $ξ_W^2$ to measure spin squeezing and our approach achieves near-optimal spin sque…

Cellular Automata as Generators of Interleaving Sequences
Sara D. Cardell
https://arxiv.org/abs/2506.18848 https://arxiv.org/pdf/2506…

Cellular Automata as Generators of Interleaving Sequences
An interleaving sequence is obtained by combining or intertwining elements from two or more sequences. On the other hand, cellular automata are known to be generators for keystream sequences. In this paper we present two families of one-dimensional cellular automata as generators of interleaving sequences. This study aims to close a notable gap within the current body of literature by exploring the capacity of cellular automata to generate interleaving sequences. While previous works have separ…

$C^{\infty}$-structures approach to travelling wave solutions to the gKdV equation
Antonio J. Pan-Collantes
https://arxiv.org/abs/2507.07112 https://

$C^{\infty}$-structures approach to travelling wave solutions to the gKdV equation
We present a geometric method for finding travelling wave solutions to the generalized Korteweg--de Vries (gKdV) equation $$ u_t + u_{xxx} + a(u)u_x = 0, $$ where $a(u)$ is a smooth function characterizing the nonlinearity. Using the travelling wave ansatz, the gKdV equation reduces to an ordinary differential equation (ODE), which we analyze via the $\mathcal{C}^\infty$-structure-based method, a geometric framework involving sequences of involutive distributions and Pfaffian equations. Startin…

Large Deviations for Sequential Tests of Statistical Sequence Matching
Lin Zhou, Qianyun Wang, Yun Wei, Jingjing Wang
https://arxiv.org/abs/2506.03976 http…

Large Deviations for Sequential Tests of Statistical Sequence Matching
We revisit the problem of statistical sequence matching initiated by Unnikrishnan (TIT 2015) and derive theoretical performance guarantees for sequential tests that have bounded expected stopping times. Specifically, in this problem, one is given two databases of sequences and the task is to identify all matched pairs of sequences. In each database, each sequence is generated i.i.d. from a distinct distribution and a pair of sequences is said matched if they are generated from the same distribu…

Persistence probabilities for MA(1) sequences with uniform innovations
Frank Aurzada, Kilian Raschel
https://arxiv.org/abs/2507.04427 https://

Persistence probabilities for MA(1) sequences with uniform innovations
We study the persistence probabilities of a moving average process of order one with uniform innovations. We identify a number of regions, characterized by the location of the uniform distribution and the coupling parameter of the process, where the persistence probabilities have qualitatively different behaviour. We obtain the generating functions of the persistence probabilities explicitly in all possible regions. In some of the regions, the persistence probabilities can be expressed explicit…

This https://arxiv.org/abs/2401.16508 has been replaced.
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A synthetic approach to detecting $v_1$-periodic families
We provide a simple proof that the unit map from the sphere spectrum to the connective image-of-$J$ spectrum $\mathrm{j}$ is surjective on homotopy groups. This is achieved using a novel $t$-structure on the category of $E$-synthetic spectra and a specific construction of $\mathbf{F}_p$- and BP-synthetic lifts of $\mathrm{j}$. These synthetic lifts then easily produce modified Adams and Adams--Novikov spectral sequences for $\mathrm{j}$ which we use the prove the above detection statement, all …

Local Ambiguity Shaping for Doppler-Resilient Sequences Under Spectral and PAPR Constraints
Shi He, Lingsheng Meng, Yao Ge, Yong Liang Guan, David Gonz\'alez G., Zilong Liu
https://arxiv.org/abs/2506.01637

Local Ambiguity Shaping for Doppler-Resilient Sequences Under Spectral and PAPR Constraints
This paper focuses on designing Doppler-resilient sequences with low local Ambiguity Function (AF) sidelobes, subject to certain spectral and Peak-to-Average Power Ratio (PAPR) constraints. To achieve this, we propose two distinctoptimization algorithms: (i) an Alternating Minimization (AM) algorithm for superior Weighted Peak Sidelobe Level (WPSL) minimization, and (ii) a low-complexity Augmented Lagrangian-assisted Majorization Minimization (ALaMM) algorithm with effective WPSL suppression. T…

Research on E-Commerce Long-Tail Product Recommendation Mechanism Based on Large-Scale Language Models
Qingyi Lu, Haotian Lyu, Jiayun Zheng, Yang Wang, Li Zhang, Chengrui Zhou
https://arxiv.org/abs/2506.06336

Research on E-Commerce Long-Tail Product Recommendation Mechanism Based on Large-Scale Language Models
As e-commerce platforms expand their product catalogs, accurately recommending long-tail items becomes increasingly important for enhancing both user experience and platform revenue. A key challenge is the long-tail problem, where extreme data sparsity and cold-start issues limit the performance of traditional recommendation methods. To address this, we propose a novel long-tail product recommendation mechanism that integrates product text descriptions and user behavior sequences using a large-…

Total sequences and the lower frame inequality
Narutaka Ozawa
https://arxiv.org/abs/2507.04899 https://arxiv.org/pdf/2507.04899

Total sequences and the lower frame inequality
We prove that every total sequence in a Hilbert space satisfies the lower frame inequality after scaling. This solves A. Kulikov's "exercise" at mathoverflow.

ProtInvTree: Deliberate Protein Inverse Folding with Reward-guided Tree Search
Mengdi Liu, Xiaoxue Cheng, Zhangyang Gao, Hong Chang, Cheng Tan, Shiguang Shan, Xilin Chen
https://arxiv.org/abs/2506.00925

ProtInvTree: Deliberate Protein Inverse Folding with Reward-guided Tree Search
Designing protein sequences that fold into a target 3D structure, known as protein inverse folding, is a fundamental challenge in protein engineering. While recent deep learning methods have achieved impressive performance by recovering native sequences, they often overlook the one-to-many nature of the problem: multiple diverse sequences can fold into the same structure. This motivates the need for a generative model capable of designing diverse sequences while preserving structural consistenc…

When Trackers Date Fish: A Benchmark and Framework for Underwater Multiple Fish Tracking
Weiran Li, Yeqiang Liu, Qiannan Guo, Yijie Wei, Hwa Liang Leo, Zhenbo Li
https://arxiv.org/abs/2507.06400

When Trackers Date Fish: A Benchmark and Framework for Underwater Multiple Fish Tracking
Multiple object tracking (MOT) technology has made significant progress in terrestrial applications, but underwater tracking scenarios remain underexplored despite their importance to marine ecology and aquaculture. We present Multiple Fish Tracking Dataset 2025 (MFT25), the first comprehensive dataset specifically designed for underwater multiple fish tracking, featuring 15 diverse video sequences with 408,578 meticulously annotated bounding boxes across 48,066 frames. Our dataset captures var…

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From Pixels to Predicates: Learning Symbolic World Models via Pretrained Vision-Language Models
Our aim is to learn to solve long-horizon decision-making problems in complex robotics domains given low-level skills and a handful of short-horizon demonstrations containing sequences of images. To this end, we focus on learning abstract symbolic world models that facilitate zero-shot generalization to novel goals via planning. A critical component of such models is the set of symbolic predicates that define properties of and relationships between objects. In this work, we leverage pretrained …

Some computational aspects of spectral sequences in \v{C}ech cohomology
Matthias Zach
https://arxiv.org/abs/2506.02636 https://arxiv.…

Some computational aspects of spectral sequences in Čech cohomology
Sheaf cohomology or, more generally, higher direct images of coherent sheaves along proper morphisms are central to modern algebraic geometry. However, the computation of these objects is a non-trivial and expensive task which easily challenges the capacities of modern computers. We describe an algorithm and its implementation to compute a spectral sequence converging to the higher direct images of a bounded complex of sheaves on a product of projective spaces $\mathbb P = \mathbb P^{r_1}\times…

Minimal residual rational Krylov subspace method for sequences of shifted linear systems
Hussam Al Daas, Davide Palitta
https://arxiv.org/abs/2507.00267 ht…

Minimal residual rational Krylov subspace method for sequences of shifted linear systems
The solution of sequences of shifted linear systems is a classic problem in numerical linear algebra, and a variety of efficient methods have been proposed over the years. Nevertheless, there still exist challenging scenarios witnessing a lack of performing solvers. For instance, state-of-the-art procedures struggle to handle nonsymmetric problems where the shifts are complex numbers that do not come as conjugate pairs. We design a novel projection strategy based on the rational Krylov subspace…

Correcting Errors Through Partitioning and Burst-Deletion Correction
Yubo Sun, Gennian Ge
https://arxiv.org/abs/2506.07609 https://ar…

Correcting Errors Through Partitioning and Burst-Deletion Correction
In this paper, we propose a partitioning technique that decomposes a pair of sequences with overlapping $t$-deletion $s$-substitution balls into sub-pairs, where the $^{\leq}t$-burst-deletion balls of each sub-pair intersect. This decomposition facilitates the development of $t$-deletion $s$-substitution correcting codes that leverage approaches from $^{\leq}t$-burst-deletion correction. Building upon established approaches in the $^{\leq}t$-burst-deletion correction domain, we construct $t$-de…

On the Maximization of Real Sequences
Assal\'e Adj\'e
https://arxiv.org/abs/2506.18409 https://arxiv.org/pdf/2506.18409

On the Maximization of Real Sequences
In this paper, we study a maximization problem on real sequences. More precisely, for a given sequence, we are interesting in computing the supremum of the sequence and an index for which the associated term is maximal. We propose a general methodology to solve this maximization problem. The method is based on upper approximations constructed from pairs of eventually decreasing sequences of strictly increasing continuous functions on $[0,1]$ and of scalars in $(0,1)$. Then, we can associate int…

A Family of Sequences Generalizing the Thue Morse and Rudin Shapiro Sequences
Russell Jay Hendel
https://arxiv.org/abs/2505.20547 https://

A Family of Sequences Generalizing the Thue Morse and Rudin Shapiro Sequences
For $m \ge 1,$ let $P_m =1^m,$ the binary string of $m$ ones. Further define the infinite sequence $s_m$ by $s_{m,n} = 1$ iff the number of (possibly overlapping) occurrences of $P_m$ in the binary representation of $n$ is odd, $n \ge 0.$ For $m=1,2$ respectively $s_m$ is the Thue-Morse and Rudin-Shapiro sequences. This paper shows: (i) $s_m$ is automatic; (ii) the minimal, DFA (deterministic finite automata) accepting $s_m$ has $2m$ states; (iii) it suffices to use prefixes of length $2^{m-1}$…

A Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization
Muhammed Ustaomeroglu, Guannan Qu
https://arxiv.org/abs/2506.06179

A Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization
Self-attention has emerged as a core component of modern neural architectures, yet its theoretical underpinnings remain elusive. In this paper, we study self-attention through the lens of interacting entities, ranging from agents in multi-agent reinforcement learning to alleles in genetic sequences, and show that a single layer linear self-attention can efficiently represent, learn, and generalize functions capturing pairwise interactions, including out-of-distribution scenarios. Our analysis r…

Memory cost of quantum contextuality with Pauli observables
Stefan Trandafir, Colm Kelleher, Ad\'an Cabello
https://arxiv.org/abs/2506.06869 https://…

Memory cost of quantum contextuality with Pauli observables
Classically simulating the quantum contextual correlations produced by sequences of ideal measurements of compatible observables requires the measured system to have an internal memory. Computing the minimum amount of memory needed is, in general, challenging. Here, building upon the work of Kleinmann et al. [New J. Phys. 13, 113011 (2011)], we prove that the memory cost for simulating the contextuality produced by the $10$ three-qubit observables of Mermin's pentagram is only $\log_2(5) \appro…

Doob's type optional sampling theorems and a central limit theorem for demimartingales with applications to associated sequences
Milto Hadjikyriakou, B. L. S Prakasa Rao
https://arxiv.org/abs/2507.05023

Doob's type optional sampling theorems and a central limit theorem for demimartingales with applications to associated sequences
This paper extends classical probabilistic results to the broader class of demimartingales and demisubmartingales. We establish variants of Doob's-type optional sampling theorem under minimal structural conditions on stopping times, relying on monotonicity properties of indicator functions. Building on these foundations, we derive maximal inequalities, moment bounds, and a concentration inequality of Azuma- Hoeffding type for demimartingales with bounded increments. A central limit theorem and …

On Base, Normal and Near-normal Sequences
Xu Wang, Jiayi Zhu
https://arxiv.org/abs/2506.20296 https://arxiv.org/pdf/2506.20296…

On Base, Normal and Near-normal Sequences
The base sequences BS(n+1,n) are four sequences of $\pm1$ and lengths n+1,n+1,n,n with zero auto correlation. The base sequence conjecture states that BS(n+1,n) exists for all integers $n>0$ and has been verified for $n\le40$. We present our algorithm and gives construction of BS(n+1,n) for $n=41,42,43$. The Normal sequences NS (n) and the Near-normal sequences NNS (n) are subclasses of BS(n+1,n). Yang conjecture asserts that there is a NNS(n) for each even integer n and has been verified for…

On coprimality of consecutive elements in certain sequences
Jean-Marc Deshouillers, Sunil Naik
https://arxiv.org/abs/2506.20948 https://

On coprimality of consecutive elements in certain sequences
The study of finding blocks of primes in certain arithmetic sequences is one of the classical problems in number theory. It is also very interesting to study blocks of consecutive elements in such sequences that are pairwise coprime. In this context, we show that if $f$ is a twice continuously differentiable real-valued function on $[1, \infty)$ such that $f''(x) \to 0$ as $x \to \infty$ and $\limsup_{x \to \infty} f'(x) = \infty$, then there exist arbitrarily long blocks of pairwise coprime co…

On the Fixed-Length-Burst Levenshtein Ball with Unit Radius
Yuanxiao Xi, Yubo Sun, Gennian Ge
https://arxiv.org/abs/2506.07817 https://

On the Fixed-Length-Burst Levenshtein Ball with Unit Radius
Consider a length-$n$ sequence $\bm{x}$ over a $q$-ary alphabet. The \emph{fixed-length Levenshtein ball} $\mathcal{L}_t(\bm{x})$ of radius $t$ encompasses all length-$n$ $q$-ary sequences that can be derived from $\bm{x}$ by performing $t$ deletions followed by $t$ insertions. Analyzing the size and structure of these balls presents significant challenges in combinatorial coding theory. Recent studies have successfully characterized fixed-length Levenshtein balls in the context of a single del…

BecomingLit: Relightable Gaussian Avatars with Hybrid Neural Shading
Jonathan Schmidt, Simon Giebenhain, Matthias Niessner
https://arxiv.org/abs/2506.06271

BecomingLit: Relightable Gaussian Avatars with Hybrid Neural Shading
We introduce BecomingLit, a novel method for reconstructing relightable, high-resolution head avatars that can be rendered from novel viewpoints at interactive rates. Therefore, we propose a new low-cost light stage capture setup, tailored specifically towards capturing faces. Using this setup, we collect a novel dataset consisting of diverse multi-view sequences of numerous subjects under varying illumination conditions and facial expressions. By leveraging our new dataset, we introduce a new …

A Note on Single-Cut Full-Open Protocols
Kazumasa Shinagawa, Koji Nuida
https://arxiv.org/abs/2507.03323 https://arxiv.org/pdf/2507.0…

A Note on Single-Cut Full-Open Protocols
Card-based cryptography is a research area that realizes cryptographic protocols such as secure computation by applying shuffles to sequences of cards that encode input values. A single-cut full-open protocol is one that obtains an output value by applying a random cut to an input sequence of cards, after which all cards are opened. In this paper, we propose three single-cut full-open protocols: two protocols for three-variable functions and one protocol for a four-variable function.

On 102-avoiding inversion sequences
JiSun Huh, Sangwook Kim, Seunghyun Seo, Heesung Shin
https://arxiv.org/abs/2506.02985 https://arx…

On 102-avoiding inversion sequences
In this article, we provide a bijection between the set of inversion sequences avoiding the pattern 102 and the set of 2-Schröder paths having neither peaks nor valleys and ending with a diagonal step. To achieve this, we introduce two intermediate objects, called UVD paths and labeled $F$-paths, and establish bijections among all four families. For each of these combinatorial objects, we define a natural statistic and enumerate the corresponding structures with respect to this statistic. In a…

Topological Sequence Analysis of Genomes: Delta Complex approaches
Jian Liu, Li Shen, Dong Chen, Guo-Wei Wei
https://arxiv.org/abs/2507.05452 https://

Topological Sequence Analysis of Genomes: Delta Complex approaches
Algebraic topology has been widely applied to point cloud data to capture geometric shapes and topological structures. However, its application to genome sequence analysis remains rare. In this work, we propose topological sequence analysis (TSA) techniques by constructing $Δ$-complexes and classifying spaces, leading to persistent homology, and persistent path homology on genome sequences. We also develop $Δ$-complex-based persistent Laplacians to facilitate the topological spectral analysis…

Heterogeneous Sequel-Aware Graph Neural Networks for Sequential Learning
Anushka Tiwari, Haimonti Dutta, Shahrzad Khanizadeh
https://arxiv.org/abs/2506.05625

Heterogeneous Sequel-Aware Graph Neural Networks for Sequential Learning
Graph-based recommendation systems use higher-order user and item embeddings for next-item predictions. Dynamically adding collaborative signals from neighbors helps to use similar users' preferences during learning. While item-item correlations and their impact on recommendations have been studied, the efficacy of temporal item sequences for recommendations is much less explored. In this paper, we examine temporal item sequence (sequel-aware) embeddings along with higher-order user embeddings …

Guided Generation for Developable Antibodies
Siqi Zhao, Joshua Moller, Porfi Quintero-Cadena, Lood van Niekerk
https://arxiv.org/abs/2507.02670 https://

Guided Generation for Developable Antibodies
Therapeutic antibodies require not only high-affinity target engagement, but also favorable manufacturability, stability, and safety profiles for clinical effectiveness. These properties are collectively called `developability'. To enable a computational framework for optimizing antibody sequences for favorable developability, we introduce a guided discrete diffusion model trained on natural paired heavy- and light-chain sequences from the Observed Antibody Space (OAS) and quantitative developa…

Coprimality of elements in regular sequences with polynomial growth
Jean-Marc Deshouillers, Sunil Naik
https://arxiv.org/abs/2506.20956 https://

Coprimality of elements in regular sequences with polynomial growth
The investigation of primes in certain arithmetic sequences is one of the fundamental problems in number theory and especially, finding blocks of distinct primes has gained a lot of attention in recent years. In this context, we prove the existence of long blocks of $k$-wise coprime elements in certain regular sequences. More precisely, we prove that for any positive integers $H \geq k \geq 2$ and for a real-valued $k$-times continuously differentiable function $f \in \mathcal{C}^k\left( [1, \i…

AI-based Environment-Aware XL-MIMO Channel Estimation with Location-Specific Prior Knowledge Enabled by CKM
Yuelong Qiu, Di Wu, Yong Zeng, Yanqun Tang, Nan Cheng, Chenhao Qi
https://arxiv.org/abs/2507.06066

AI-based Environment-Aware XL-MIMO Channel Estimation with Location-Specific Prior Knowledge Enabled by CKM
Accurate and efficient acquisition of wireless channel state information (CSI) is crucial to enhance the communication performance of wireless systems. However, with the continuous densification of wireless links, increased channel dimensions, and the use of higher-frequency bands, channel estimation in the sixth generation (6G) and beyond wireless networks faces new challenges, such as insufficient orthogonal pilot sequences, inadequate signal-to-noise ratio (SNR) for channel training, and mor…

Constructions of Optimal Frequency-Hopping Sequences with Controlled Minimum Gaps
Chen Li, Chunlei Li, Xiangyong Zeng, Dian Li
https://arxiv.org/abs/2506.00945

Constructions of Optimal Frequency-Hopping Sequences with Controlled Minimum Gaps
Frequency-hopping sequences (FHSs) with low Hamming correlation and wide gaps significantly contribute to the anti-interference performance in FH communication systems. This paper investigates FHSs with optimal Hamming correlation and controlled minimum gaps. We start with the discussion of the upper bounds on the minimum gaps of uniform FHSs and then propose a general construction of optimal uniform wide-gap FHSs with length 2l and 3l, which includes the work by Li et al. in IEEE Trans. Inf. T…

This https://arxiv.org/abs/2506.03999 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Large deviations for scaled families of Schrödinger bridges with reflection
In this paper, we show a large deviation principle for certain sequences of static Schrödinger bridges, typically motivated by a scale-parameter decreasing towards zero, extending existing large deviation results to cover a wider range of reference processes. Our results provide a theoretical foundation for studying convergence of such Schrödinger bridges to their limiting optimal transport plans. Within generative modeling, Schrödinger bridges, or entropic optimal transport problems, consti…

Noise-Canceling Quantum Feedback: non-Hermitian Dynamics with Applications to State Preparation and Magic State Distillation
Tathagata Karmakar, Philippe Lewalle, Yipei Zhang, K. Birgitta Whaley
https://arxiv.org/abs/2507.05611

Noise-Canceling Quantum Feedback: non-Hermitian Dynamics with Applications to State Preparation and Magic State Distillation
Time-continuous quantum measurement allows for the tracking of a quantum system in real time via sequences of short, and individually weak, measurement intervals. Such measurements are necessarily invasive, imparting backaction to the system, and allowing the observer to update their state estimate based on stochastic measurement outcomes. Feedback control then involves real-time interventions by an observer, conditioned on the time-continuous measurement signal that they receive. We here consi…

TransAct V2: Lifelong User Action Sequence Modeling on Pinterest Recommendation
Xue Xia, Saurabh Vishwas Joshi, Kousik Rajesh, Kangnan Li, Yangyi Lu, Nikil Pancha, Dhruvil Deven Badani, Jiajing Xu, Pong Eksombatchai
https://arxiv.org/abs/2506.02267

TransAct V2: Lifelong User Action Sequence Modeling on Pinterest Recommendation
Modeling user action sequences has become a popular focus in industrial recommendation system research, particularly for Click-Through Rate (CTR) prediction tasks. However, industry-scale CTR models often rely on short user sequences, limiting their ability to capture long-term behavior. Additionally, these models typically lack an integrated action-prediction task within a point-wise ranking framework, reducing their predictive power. They also rarely address the infrastructure challenges invo…

Deterministic Cryptographic Seed Generation via Cyclic Modular Inversion over $\mathbb{Z}/3^p\mathbb{Z}$
Michael A. Idowu
https://arxiv.org/abs/2507.03000 …

Deterministic Cryptographic Seed Generation via Cyclic Modular Inversion over $\mathbb{Z}/3^p\mathbb{Z}$
We present a deterministic framework for cryptographic seed generation based on cyclic modular inversion over $\mathbb{Z}/3^p\mathbb{Z}$. The method enforces algebraic admissibility on seed inputs via the identity $d_k \equiv -\left(2^{k-1}\right)^{-1} \bmod 3^p$, thereby producing structured and invertible residue sequences. This mapping yields entropy-rich, cycle-complete seeds well-suited for cryptographic primitives such as DRBGs, KDFs, and post-quantum schemes. To assess the quality of ran…

On the methods of reduction of some types of Marczerwski-Burstin measurable functions to continuous functions on products of perfect sets
Waldemar Ho{\l}ubowski, S{\l}awomir Kusi\'nski
https://arxiv.org/abs/2506.06458

On the methods of reduction of some types of Marczerwski-Burstin measurable functions to continuous functions on products of perfect sets
In this paper we provide product-wise generalizations of certain Marczewski-Burstin bases such as sets with (s)-property and completely Ramsey sets. For each of those we prove - as an analog of classical Luzin's and Eggleston's theorems that functions measurable with respect to those families can be reduced to continuous functions on a product of perfect sets. Moreover we also provide a way to reduce sequences of such functions to continuity, providing generalizations to Laver's extension of Ha…

Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations
Xiang Xu, Lingdong Kong, Song Wang, Chuanwei Zhou, Qingshan Liu
https://arxiv.org/abs/2507.05260

Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations
LiDAR representation learning aims to extract rich structural and semantic information from large-scale, readily available datasets, reducing reliance on costly human annotations. However, existing LiDAR representation strategies often overlook the inherent spatiotemporal cues in LiDAR sequences, limiting their effectiveness. In this work, we propose LiMA, a novel long-term image-to-LiDAR Memory Aggregation framework that explicitly captures longer range temporal correlations to enhance LiDAR r…

Anti-recurrence sequences
Robbert Fokkink, Gandhar Joshi
https://arxiv.org/abs/2506.13337 https://arxiv.org/pdf/2506.13337

Anti-recurrence sequences
We extend previous work on anti-recurrence sequences of Kimberling and Moses, Zaslavsky, and Bosma et al. Kimberling and Moses have formulated several questions on these sequences, which can be combined into the meta-conjecture that anti-recurrence sequences are sums of linear progressions and automatic sequences. We solve this conjecture under a restriction on the linear form that generates the anti-recurrence.

GeneBreaker: Jailbreak Attacks against DNA Language Models with Pathogenicity Guidance
Zaixi Zhang, Zhenghong Zhou, Ruofan Jin, Le Cong, Mengdi Wang
https://arxiv.org/abs/2505.23839

GeneBreaker: Jailbreak Attacks against DNA Language Models with Pathogenicity Guidance
DNA, encoding genetic instructions for almost all living organisms, fuels groundbreaking advances in genomics and synthetic biology. Recently, DNA Foundation Models have achieved success in designing synthetic functional DNA sequences, even whole genomes, but their susceptibility to jailbreaking remains underexplored, leading to potential concern of generating harmful sequences such as pathogens or toxin-producing genes. In this paper, we introduce GeneBreaker, the first framework to systematic…

Metric Poissonian pair correlation for real sequences and energy estimates
Bryce Kerr, Hongliang Wang
https://arxiv.org/abs/2506.17031 https://

Metric Poissonian pair correlation for real sequences and energy estimates
In this paper, we establish new conditions under which a sequence of real numbers has metric Poissonian pair correlation. Our conditions improve upon results of Aistleitner, El-Baz and Munsch, and resolve one of their open problems for sequences that grow faster than a quadratic polynomial. As applications, we show that quantitatively convex and polynomial sequences are metric Poissonian.

On the Maximum Size of Codes Under the Damerau-Levenshtein Metric
Zuo Ye, Gennian Ge
https://arxiv.org/abs/2507.04806 https://arxiv.o…

On the Maximum Size of Codes Under the Damerau-Levenshtein Metric
The Damerau-Levenshtein distance between two sequences is the minimum number of operations (deletions, insertions, substitutions, and adjacent transpositions) required to convert one sequence into another. Notwithstanding a long history of this metric, research on error-correcting codes under this distance has remained limited. Recently, motivated by applications in DNA-based storage systems, Gabrys \textit{et al} and Wang \texit{et al} reinvigorated interest in this metric. In their works, som…

This https://arxiv.org/abs/2407.10026 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

Conditional Entropies of k-Deletion/Insertion Channels
The channel output entropy of a transmitted sequence is the entropy of the possible channel outputs and similarly the channel input entropy of a received sequence is the entropy of all possible transmitted sequences. The goal of this work is to study these entropy values for the k-deletion, k-insertion channels, where exactly k symbols are deleted, inserted in the transmitted sequence, respectively. If all possible sequences are transmitted with the same probability then studying the input and …

Finite State Dimension and The Davenport Erd\H{o}s Theorem
Joe Clanin, Matthew Rayman
https://arxiv.org/abs/2506.02332 https://arxiv.…

Finite State Dimension and The Davenport Erdős Theorem
A 1952 result of Davenport and Erdős states that if $p$ is an integer-valued polynomial, then the real number $0.p(1)p(2)p(3)\dots$ is Borel normal in base ten. A later result of Nakai and Shiokawa extends this result to polynomials with arbitrary real coefficients and all bases $b\geq 2$. It is well-known that finite-state dimension, a finite-state effectivization of the classical Hausdorff dimension, characterizes the Borel normal sequences as precisely those sequences of finite-state dimens…