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arXiv:2602.13461v1 Announce Type: new Abstract: The Positional Burrows--Wheeler Transform (PBWT) is a data structure designed for efficiently representing and querying large collections of sequences, such...
arXiv:2602.13466v1 Announce Type: new Abstract: The ability of machine learning models to store input information in hidden layer vector embeddings, analogous to the concept of...
arXiv:2602.13468v1 Announce Type: new Abstract: This paper investigates the algebraic structure of free convolutional codes over the finite local ring Z_{p^r}. We introduce a new...
arXiv:2602.13469v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are changing how Blind and Low Vision (BLV) people access visual information in their daily...
arXiv:2602.13473v1 Announce Type: new Abstract: Although foundation models have demonstrated remarkable success in general domains, the application of these models to electroencephalography (EEG) analysis is...
arXiv:2602.13476v1 Announce Type: new Abstract: Robotic foundation models achieve strong generalization by leveraging internet-scale vision-language representations, but their massive computational cost creates a fundamental bottleneck:...
arXiv:2602.13477v1 Announce Type: new Abstract: As Large Language Model (LLM) agents become more capable, their coordinated use in the form of multi-agent systems is anticipated...
arXiv:2602.13479v1 Announce Type: new Abstract: Video Large Language Models (Video LLMs) have shown remarkable progress in understanding and reasoning about visual content, particularly in tasks...
arXiv:2602.13480v1 Announce Type: new Abstract: Launchpads have become the dominant mechanism for issuing memecoins on blockchains due to their fully automated, no-code creation process. This...
arXiv:2602.13482v1 Announce Type: new Abstract: Selecting an optimal classification model requires a robust and comprehensive understanding of the performance of the model. This paper provides...
arXiv:2602.13483v1 Announce Type: new Abstract: Understanding the internal circuits that language models use to solve tasks remains a central challenge in mechanistic interpretability. Most prior...
arXiv:2602.13484v1 Announce Type: new Abstract: Filters are ubiquitous in computer science, enabling space-efficient approximate membership testing. Since Bloom filters were introduced in 1970, decades of...
arXiv:2602.13485v1 Announce Type: new Abstract: Networks of modern industrial systems are increasingly monitored by distributed sensors, where each system comprises multiple subsystems generating high dimensional...
arXiv:2602.13486v1 Announce Type: new Abstract: Federated low-rank adaptation (FedLoRA) has facilitated communication-efficient and privacy-preserving fine-tuning of foundation models for downstream tasks. In practical federated learning...
arXiv:2602.13488v1 Announce Type: new Abstract: Pilot studies (PS) are ubiquitous in HCI research. CHI papers routinely reference 'pilot studies', 'pilot tests', or 'preliminary studies' to...
arXiv:2602.13493v1 Announce Type: new Abstract: We show that under convergence in measure of probability density functions, differential entropy converges whenever the entropy integrands $f_n |\log...
arXiv:2602.13496v1 Announce Type: new Abstract: 1. Many ecological decisions are slowed by the gap between collecting and analysing biodiversity data. Edge computing moves processing closer...
arXiv:2602.13498v1 Announce Type: new Abstract: Muon-style optimizers leverage Newton-Schulz (NS) iterations to orthogonalize updates, yielding update geometries that often outperform Adam-series methods. However, this orthogonalization...
arXiv:2602.13502v1 Announce Type: new Abstract: An important goal for personalized diet systems is to improve nutritional quality without compromising convenience or affordability. We present an...
arXiv:2602.13504v1 Announce Type: new Abstract: The rapid integration of large language models into newsroom workflows has raised urgent questions about the prevalence of AI-generated content...
arXiv:2602.13505v1 Announce Type: new Abstract: In this paper, we introduce a construction of quantum convolutional codes (QCCs) based on difference triangle sets (DTSs). To construct...
arXiv:2602.13506v1 Announce Type: new Abstract: Optimizing monotone non-convex functions is a fundamental challenge across machine learning and combinatorial optimization. We introduce and study $\gamma$-weakly $\theta$-up-concavity,...
arXiv:2602.13507v1 Announce Type: new Abstract: Remote, video-based assessments offer a scalable pathway for Parkinson's disease (PD) screening. While traditional approaches rely on handcrafted features mimicking...
arXiv:2602.13511v1 Announce Type: new Abstract: Given a set of entities each holding a Boolean state, the Density Classification Task (DCT) asks them to converge to...