Every story across every category, newest first. Each card links to the original publisher; daily-brief posts open as editorial pages.
arXiv:2511.15615v2 Announce Type: replace-cross Abstract: This paper presents a tractable algorithm for estimating an unknown Lipschitz function from noisy observations and establishes an upper bound on…
arXiv:2607.08789v1 Announce Type: new Abstract: Bayesian and multiplicative-weights updates reweight experts, models, or actions from sequential feedback. We show that the regret of any such update…
arXiv:2004.05813v3 Announce Type: replace-cross Abstract: Suppose that we are given independent, identically distributed random samples $x_1,cdots,x_n$ from a mixture at most $k$ many $d$-dimensional spherical Gaussian…
arXiv:2607.08786v1 Announce Type: new Abstract: With the growing deployment of large language models (LLMs), LLM inference cost has become a key challenge. Pruning techniques that introduce…
arXiv:2606.03631v3 Announce Type: replace Abstract: Multivariate time series classification (MTSC) is pivotal in high-stakes domains, such as clinical diagnosis and industrial fault detection, where safe deployment…
arXiv:2607.08785v1 Announce Type: new Abstract: High-quality data drives machine learning advances across industries. Recognizing the value of data, data transactions are increasingly common, giving rise to…
arXiv:2602.21196v2 Announce Type: replace Abstract: Efficiently processing long sequences with Transformer models usually requires splitting the computations across accelerators via context parallelism. The dominant approaches in…
arXiv:2607.08779v1 Announce Type: new Abstract: The signed integer alphabet contains one more negative representable value than positive. Yet, by convention, the standard symmetric integer quantizer fixes…
arXiv:2607.08780v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models activate only a sparse subset of experts per token, yet consecutive tokens frequently activate different experts -- causing…
arXiv:2607.08781v1 Announce Type: new Abstract: The coupling in flow matching -- the rule pairing noise vectors with data points -- is typically treated as a computational…
arXiv:2607.08783v1 Announce Type: new Abstract: Manifold-valued measurements are prevalent in various machine learning tasks. Recent advances have extended Deep Neural Networks (DNNs) to operate on manifolds,…
arXiv:2607.08782v1 Announce Type: new Abstract: Expert parallelism has become the prevailing paradigm to serve Mixture-of-Experts (MoE) models. Its efficiency depends on the communication and computation latencies…
arXiv:2606.28225v2 Announce Type: replace Abstract: Temporal link prediction (TLP) is typically evaluated by predictive performance on unseen edges, but this criterion can conflate predictive accuracy with…
arXiv:2607.08784v1 Announce Type: new Abstract: Federated continual learning (FCL) evaluates how distributed clients learn from changing data streams while retaining previously learned knowledge. Existing evaluations are…
arXiv:2603.20388v2 Announce Type: replace-cross Abstract: We derive the asymptotic risk function of regularized empirical risk minimization (ERM) estimators tuned by $n$-fold cross-validation (CV). The out-of-sample prediction…
arXiv:2504.18902v3 Announce Type: replace-cross Abstract: In the forthcoming era of 6G networks, characterized by unprecedented data rates, ultra-low latency, and ubiquitous connectivity, effective management of Virtualized…
arXiv:2607.09305v1 Announce Type: cross Abstract: Chest radiography (CXR) remains the most widely used thoracic imaging modality, yet expert interpretation is constrained by a severe shortage of…
arXiv:2509.21725v3 Announce Type: replace Abstract: A bilevel optimization problem consists of two optimization problems nested as an upper- and a lower-level problem, in which the optimality…
arXiv:2607.09645v1 Announce Type: cross Abstract: Many real-world processes can be represented as compositions of functions along a directed acyclic graph (DAG). In causal modelling, these correspond…
arXiv:2604.20730v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown promising capabilities in generating Scalable Vector Graphics (SVG) via direct code synthesis. However, existing…
arXiv:2607.09067v1 Announce Type: new Abstract: Text-to-image diffusion models exhibit unprecedented generative capability and contain rich intermediate representations that can be useful for discriminative vision tasks. Motivated…
arXiv:2601.09881v2 Announce Type: replace Abstract: Large video diffusion and flow models have achieved remarkable success in high-quality video generation, but their use in real-time interactive applications…
arXiv:2607.09061v1 Announce Type: new Abstract: A striking feature of the human visual system is that it ingests visual information through a series of local foveated glimpses,…
arXiv:2504.15650v3 Announce Type: replace Abstract: Building a generalized affordance grounding model to identify actionable regions on objects is vital for real-world applications. Existing methods to train…