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Related Articles from SNS
Amortized Nonlinear Model Predictive Control
arXiv:2606.05840v1 Announce Type: new Abstract: Nonlinear Model Predictive Control requires solving a constrained nonlinear program (NLP) in real-time at every sampling instant, a computational bottleneck that limits deployment on resource-constrained hardware or at high sampling rates. We address this challenge for the broad class of input-affine nonlinear systems to show that the optimal control move can be approximated by a state-dependent quadratic program (QP) whose cost parameters...
QPredSGG: Hybrid Quantum Predicate Learning for Long-Tailed Scene Graph Generation
arXiv:2606.04689v1 Announce Type: cross Abstract: Scene Graph Generation (SGG) requires relational reasoning over objects and their interactions, but performance is often limited by severe long-tail predicate imbalance. Classical SGG models frequently rely on dataset statistics, leading to biased predictions toward frequent relations rather than fine-grained semantic predicates. Although existing debiasing strategies improve mean recall, predicate classification in current frameworks still...
Evolution of Coronal Mass Ejection Properties through Superposed Epoch Analysis from 0.2 to 2.2 au
Announce Type: new Abstract: Coronal mass ejections (CMEs) are explosive and energetic events consisting of strong magnetic structures erupting from the solar corona. We use superposed epoch analysis to investigate the general properties of CMEs as measured {\it in situ} from 0.2 to 2.2 au based on over 1600 events obtained from the HELIO4CAST catalog. We examine the dependence of the CME global properties on solar cycle phase, and compare the CME parameters derived in the active phase (AP)...
Tunable Real-Time Safety Filters via Set-Based Control Barrier Functions
arXiv:2507.07805v3 Announce Type: replace Abstract: Safety filters for industrial constrained systems are required to combine certified constraint satisfaction, predictable online computation, and a transparent tuning interface. Existing set-based filters are based on a well-established control invariant set design that scales favorably with state and input constraints, but typically intervene only at the set boundary. Control barrier function (CBF)-based filters, by contrast, provide...
Impedance MPC for Physical Human-Robot Interaction: Predictive Disturbance Rejection with Joint-Limit Safety
arXiv:2606.08281v1 Announce Type: new Abstract: Physical human-robot interaction (pHRI) demands simultaneous trajectory accuracy and compliant safety under unplanned contact. Classical impedance control incurs a nonzero steady-state position error under sustained human force -- the applied force divided by the task stiffness -- which integral action reduces only within a narrow stable-gain budget. We present a two-layer Impedance MPC that resolves this tension.
An Efficient, Reliable and Observable Collective Communication Library in Large-scale GPU Training Clusters
Announce Type: replace Abstract: Large-scale LLM training requires collective communication libraries to exchange data among distributed GPUs. As a company dedicated to building and operating large-scale GPU training clusters, we encounter several practical limitations of NCCL in production, including 1) SM competition between computation and communication, 2) expensive restart costs under link failures, and 3) insufficient observability of transient collective communication anomalies. To...
Multi-ResNets for Subspace Preconditioning in Constrained Optimization
Announce Type: new Abstract: We propose MResOpt, a staged residual neural network architecture for constrained optimization problems. Our architecture fits within predict-complete-correct pipelines and decomposes constraint satisfaction by priority through intermediate re-completion and stage-aware losses. The framework enables domain-informed ordered constraint satisfaction which allows the network to utilize ordinal structure when present.