AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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iDriveVLA is proposed, a multi-modal planning framework that improves the candidate trajectory space while enabling more reliable and context-aware trajectory evaluation and develops an oracle-aligned progressive training strategy consisting of candidate imitation pretraining, candidate space refinement, and semantic r...
This work presents NeuralParker, a reinforcement learning-based hybrid planner for arbitrary-pose parking that encodes full-environment obstacle and boundary geometry in a target-relative vertex representation, allowing the policy to retain route-defining context throughout the approach.
A unified temporal-credit view of token-level OPD and sequence-level OPD is established, showing that practical token-level OPD can be interpreted as a temporal approximation to the sequence-level reverse-KL gradient.
This survey examines RL-based AD in modular and end-to-end pipelines and relates reported methods to task formulation and deployment evidence and examines deployment barriers, including safety, Sim2Real generalization, data efficiency, computation, embodied alignment, and evaluation readiness.
This paper proposes exchange policy optimization (EPO), an algorithmic framework that achieves optimal policy performance with provably bounded safety guarantees and derives an upper bound on the required number of iterations and quantifies the gap between the obtained policy and the true optimum.
An AIM framework based on residual-penalty variable splitting, which interprets momentum as a multiplier-like correction driven by the splitting residual, and RADAR, which combines relativistic adaptive geometry, decoupled residual correction, and second-order momentum filtering to improve the update direction and mome...
A joint identifiability condition for controlled world models with Gaussian latent states with Gaussian latent states is presented, which consists of two coupled components: representation identifiability and transition identifiability, and it is proved that when this condition holds, minimizing the LeJEPA-style predic...
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