AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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1,183 papers
A fixed encoder is studied in a fixed encoder and trajectory reachability metrics (TRM), a small temporal pairwise cost trained from logged trajectories and used to rank predicted endpoints of a candidate action sequence against a goal is introduced.
This work introduces Constrained GRPO, a Lagrangian-based extension of GRPO for constrained policy optimization, and addresses the coupling induced by reward scalarization by scalarizing standardized advantages rather than rewards.
This work removes a model's camera input and replaces it with memories from prior drives at the same location, suggesting that a high NAVSIM score does not require a planner to react to the current traffic scene and should be treated with caution.
Motus2 is presented, a self-evolving general world model for dexterous manipulation that combines egocentric data scaling and closed-loop general world model scaling to provide a general path toward self-evolving dexterous manipulation.
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A paradigm for tactile-enabled embodied manipulation, which integrates tactile sensing hardware, large-scale multimodal data, tactile representation learning, and standardized evaluation is presented, aiming at supporting future work on tactile-enabled embodied manipulation.
A novel metric derived from the flow matching trajectory curvature is introduced to quantify action generation confidence during inference and enables the dynamic reduction of inference steps and the adaptive adjustment of MLP pruning ratios through an efficiently computed importance evaluation, requiring no access to...
A proof-of-concept Brain-Language-Action (BLA) model for drone control using motor-imagery EEG from the BCI Competition IV 2a dataset is developed, providing an initial demonstration that language conditioning can expand the effective control range of EEG-based robotic interfaces without requiring a corresponding incre...
Adversarial Calibration Attack (ACA), the first physical attack against camera-LiDAR online calibration, is presented and demonstrated that online calibration is a practical and safety-critical attack surface for AVs.
This work proposes a unified autoregressive diffusion-based graph generative model that jointly learns structure and features, constructing complete 3DSGs bottom-up from observed vertical planes across arbitrary hierarchy depths, and proposes an adaptation of the Fused Gromov--Wasserstein distance for principled graph-...
Control performance guarantee is first established by deriving tracking error bound for the in-network control architecture, while accounting for computational delays, and an explicit expression of the proposed event-trigger condition for exponentially stabilizable systems is derived.
This work proposes an asynchronous cooperative learning strategy that explicitly accounts for prediction accuracy, query point variations and delay effects, and a distributed control law based on an adjoint MAS is developed to ensure the desired control performance.
This work proposes a fully distributed continuous-time algorithm for shared linear equality constraints that converges without multiplier exchange and reaches any GNE, reducing communication overhead and improving privacy.
Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and support more advanced physical AI workloads. The post Offloaded inference for real-world physical AI robotics appeared first on Microsoft Research.
A Blog post by Amazon on Hugging Face
Director of CSAIL and MIT professor honored for her contributions to robotics, artificial intelligence, and autonomous systems.
Gemini Robotics ER 2 helps robots reason, collaborate, and solve real-world tasks. It represents a step change in video understanding, tool orchestration, and multi-robot collaboration for robotic applications.
From feet to fingertips — we are teaching robots intelligent whole-body control, fine dexterity, and teamwork to complete a broad range of complex tasks.
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