arXiv:2602.16758v1 Announce Type: new Abstract: This paper presents a smooth trajectory generation method for a four-degree-of-freedom parallel kinematic milling robot. The proposed approach integrates B-spline and Quaternion interpolation techniques to manage decoupled position and orientation data points. The synchronization of orientation and arc-length-parameterized position data is achieved through the fitting of smooth piece-wise Bezier curves, which describe the non-linear relationship between path length and tool orientation, solved via sequential quadratic programming. By leveraging the convex hull properties of […]

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arXiv:2602.13906v1 Announce Type: new Abstract: Stochastic approximation (SA) is a method for finding the root of an operator perturbed by noise. There is a rich literature establishing the asymptotic normality of rescaled SA iterates under fairly mild conditions. However, these asymptotic results do not quantify the accuracy of the Gaussian approximation in finite time. In this paper, we establish explicit non-asymptotic bounds on the Wasserstein distance between the distribution of the rescaled iterate at time k and the […]

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Building used to be the bottleneck. Now it’s everything that comes after. Image sourced from Abhiram Kakarla’s LinkedIn You ship a working product in twelve hours. Auth, payments, a clean dashboard, even some halfway-decent onboarding copy. The model keeps up, you keep prompting, and somewhere around hour ten you start feeling that specific kind of high — the one where you’re convinced this is the thing. You post the link. You lean back. You wait. Three days later, your only signups are you, […]

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Welcome to HackerNoon’s Meet the Writer Interview series, where we learn a bit more about the contributors that have written some of our favorite stories. Let’s start! Tell us a bit about yourself (name, profession, and personal interests). My name is Norm Bond. I help founders, operators and creators think clearly in an environment that keeps accelerating. My work tracks the intersection of tech, markets and meaning**.** I focus on what happens when systems become powerful faster than […]

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arXiv:2602.10235v1 Announce Type: new Abstract: While sign language translation systems promise to enhance deaf people’s access to information and communication, they have been met with strong skepticism from deaf communities due to risks of misrepresenting and oversimplifying the richness of signed communication in technologies. This article provides empirical evidence of the complexity of translation work involved in deaf communication through interviews with 13 deaf Chinese content creators who actively produce and share sign language content on video sharing […]

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Forgetting a subset in machine unlearning is rarely an isolated task. Often, retained samples that are closely related to the forget set can be unintentionally affected, particularly when they share correlated features from pretraining or exhibit strong semantic similarities. To address this challenge, we propose a novel two-phase optimization framework specifically designed to handle such retai-forget entanglements. In the first phase, an augmented Lagrangian method increases the loss on the forget set while preserving accuracy on less-related retained […]

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The deployment of deep neural networks in safety-critical systems necessitates reliable and efficient uncertainty quantification (UQ). A practical and widespread strategy for UQ is repurposing stochastic regularizers as scalable approximate Bayesian inference methods, such as Monte Carlo Dropout (MCD) and MC-DropBlock (MCDB). However, this paradigm remains under-explored for Stochastic Depth (SD), a regularizer integral to the residual-based backbones of most modern architectures. While prior work demonstrated its empirical promise for segmentation, a formal theoretical connection to Bayesian variational […]

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arXiv:2603.00594v1 Announce Type: new Abstract: In this paper, we consider the integrating factor midpoint method for wave-type equations and derive optimal order a posteriori error estimates. We first introduce an integrating factor midpoint approximation defined by the piecewise linear approximate solutions, and derive suboptimal order residual-based error estimates using the energy technique. Hence the key is introducing a continuous, piecewise quadratic time reconstruction to establish optimal order error bounds. Based on the reliable a posteriori error control, we […]

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The problem almost nobody warns you about If you’ve tried training a manipulation policy in Isaac Sim or MuJoCo on assets pulled from Sketchfab, TurboSquid, Objaverse, or your team’s internal CAD library, you’ve probably hit one or more of these: Gripper passes through the object. Object has “infinite mass” and refuses to move. Stacking collapses in bizarre non-physical ways. Contact forces spike to NaN and the sim explodes. Your policy trains to 99% success in sim and faceplants […]

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arXiv:2602.07125v1 Announce Type: new Abstract: Universal Multimodal Retrieval (UMR) seeks any-to-any search across text and vision, yet modern embedding models remain brittle when queries require latent reasoning (e.g., resolving underspecified references or matching compositional constraints). We argue this brittleness is often data-induced: when images carry “silent” evidence and queries leave key semantics implicit, a single embedding pass must both reason and compress, encouraging spurious feature matching. We propose a data-centric framework that decouples these roles by externalizing reasoning […]

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