arXiv:2601.16242v1 Announce Type: new Abstract: This paper presents a novel and scalable screw-theoretic multibody synthesis framework for PDE-based dynamic modeling of serial robotic manipulators with an arbitrary number of flexible links in three-dimensional space. The proposed approach systematically constructs screw-theoretic PDE models for individual flexible links and rigorously enforces holonomic joint constraints through interaction forces. The dynamics of each link are formulated using a set of dual screws expressed in body-fixed coordinates: one describing the motion of the […]

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arXiv:2601.02492v1 Announce Type: new Abstract: We introduce variational spectral learning (VSL), a machine learning framework for solving partial differential equations (PDEs) that operates directly in the coefficient space of spectral expansions. VSL offers a principled bridge between variational PDE theory, spectral discretization, and contemporary machine learning practice. The core idea is to recast a given PDE [ mathcal{L}u = f quad text{in} quad Q=Omegatimes(0,T), ] together with boundary and initial conditions, into differentiable space–time energies built from strong-form […]

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arXiv:2602.15239v1 Announce Type: new Abstract: Transformers have achieved remarkable success across domains, motivating the rise of Graph Transformers (GTs) as attention-based architectures for graph-structured data. A key design choice in GTs is the use of Graph Neural Network (GNN)-based positional encodings to incorporate structural information. In this work, we study GTs through the lens of manifold limit models for graph sequences and establish a theoretical connection between GTs with GNN positional encodings and Manifold Neural Networks (MNNs). Building […]

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Hi r/MachineLearning, I’m looking for guidance on a journal submission for a paper that sits between disciplinary lines: ML, robotics, and research data infrastructures. I’d really appreciate your perspective. Context: We recently received an editorial reject from an IEEE journal after a long review process. The decision was frustrating mainly because the reviewer feedback was largely positive, and from our side it felt like one more revision round would have been sufficient. Before blindly resubmitting elsewhere, I’m trying […]

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Key Highlights: Liquid AI Launches New On-Device AI Models for Phones, Cars, and Smart Devices AI startup Liquid AI announced on January 5, 2026, that it is launching a new family of models called LFM2.5-1.2B, designed to run artificial intelligence directly on devices such as smartphones, vehicles, and Internet-connected hardware. The launch was detailed in a blog post published by the company, outlining its latest push toward on-device AI systems. Instead of relying on cloud servers, these models […]

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Table of Links ABSTRACT 1 INTRODUCTION 2 INTERACTIVE WORLD SIMULATION 3 GAMENGEN 3.1 DATA COLLECTION VIA AGENT PLAY 3.2 TRAINING THE GENERATIVE DIFFUSION MODEL 4 EXPERIMENTAL SETUP 4.1 AGENT TRAINING 4.2 GENERATIVE MODEL TRAINING 5 RESULTS 5.1 SIMULATION QUALITY 5.2 ABLATIONS 6 RELATED WORK 7 DISCUSSION, ACKNOWLEDGEMENTS AND REFERENCES 2 INTERACTIVE WORLD SIMULATION An Interactive Environment E consists of a space of latent states S, a space of partial projections of the latent space O, a partial projection […]

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arXiv:2601.05347v1 Announce Type: new Abstract: Maintaining spatial data (points in two or three dimensions) is crucial and has a wide range of applications, such as graphics, GIS, and robotics. To handle spatial data, many data structures, called spatial indexes, have been proposed, e.g. kd-trees, oct/quadtrees (also called Orth-trees), R-trees, and bounding volume hierarchies (BVHs). In real-world applications, spatial datasets tend to be highly dynamic, requiring batch updates of points with low latency. This calls for efficient parallel batch […]

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arXiv:2602.00877v1 Announce Type: new Abstract: Low speed does not always guarantee safety in off-road driving. For instance, crossing a ditch may be risky at a low speed due to the risk of getting stuck, yet safe at a higher speed with a controlled, accelerated jump. Achieving such behavior requires path planning that explicitly models complex motion dynamics, whereas existing methods often neglect this aspect and plan solely based on positions or a fixed velocity. To address this gap, […]

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