arXiv:2604.04670v1 Announce Type: cross
Abstract: The rapid rise of LLMs over the last few years has promoted growing experimentation with LLM-driven AI tutors. However, the details of implementation, as well as the benefit in a teaching environment, …
arXiv:2604.04264v1 Announce Type: new
Abstract: Expectation Propagation (EP) is a widely used iterative message-passing algorithm that decomposes a global inference problem into multiple local ones. It approximates marginal distributions as “beliefs’…
arXiv:2604.04726v1 Announce Type: new
Abstract: Tensor-valued data arise naturally in multidimensional signal and imaging problems, such as biomedical imaging. When incorporated into generalized linear models (GLMs), naive vectorization can destroy th…
arXiv:2604.03985v1 Announce Type: cross
Abstract: Damped sinusoidal oscillations are widely observed in many physical systems, and their analysis provides access to underlying physical properties. However, parameter estimation becomes difficult when t…
arXiv:2604.04802v1 Announce Type: cross
Abstract: We study compressed sensing when the sampling vectors are chosen from the rows of a unitary matrix. In the literature, these sampling vectors are typically chosen randomly; the use of randomness has en…
arXiv:2604.03623v1 Announce Type: new
Abstract: With the growing demand for large-scale and high-quality data in edge intelligence systems, mobile robots are increasingly deployed to collect data proactively, particularly in complex environments. Howe…
arXiv:2512.19010v3 Announce Type: replace-cross
Abstract: The tactile properties of tissue, such as elasticity and stiffness, often play an important role in surgical oncology when identifying tumors and pathological tissue boundaries. Though extremel…
arXiv:2604.02513v1 Announce Type: cross
Abstract: Sparse Bayesian Learning is one of the most popular sparse signal recovery methods, and various algorithms exist under the SBL paradigm. However, given a performance metric and a sparse recovery proble…
arXiv:2604.01441v1 Announce Type: cross
Abstract: Modern real-time systems require accurate characterization of task timing behavior to ensure predictable performance, particularly on complex hardware architectures. Existing methods, such as worst-cas…
arXiv:2601.17641v2 Announce Type: replace
Abstract: Brain motor decoding aims to interpret and translate neural activity into behaviors. Decoding models should generalize across variations, such as recordings from different brain sites, experimental s…