AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A finite-horizon error bound is derived that clarifies three factors and use empirical diagnostics to guide subsystem selection in Cascaded Emulation, a one-way rollout architecture that augments an existing full-state backbone with an independently evolving model of physically specified aggregates.
MechBench is introduced, a benchmark that explicitly separates mechanism discovery from phenomenal-law recovery and reveals a substantial generalization gap in mechanistic reasoning, establishing mechanism discovery as a distinct challenge beyond recovering observable scientific laws.
SRHarness is introduced, a domain-specific harness for agentic symbolic regression built around three mechanisms: composable scientific actions that provide a common interface over raw, transformed, and candidate-derived quantities; persistent scientific state that retains evaluated hypotheses and exposes compact model...
This work proposes a funderline-based item-based item tokenizer (Tlow) to transform raw semantic embeddings into a latent space where embeddings conform to a unified standard normal distribution, achieving dual advantages of dimensional independence and distributional simplicity.
Human mobility predictability concerns the best prediction performance attainable from a given target and input information, but its ground truth is not directly observable on real mobility data. We present BER-PEF, a Bayes-error-rate-based framework that converts BER estimation into mobility predictability estimation...
This work proposes Real-time Adaptive Physics-Informed Diffusion (RAPID), a unified framework explicitly designed to balance high-fidelity generation with strict real-time constraints, and establishes a new state-of-the-art balance between fidelity and safety.
The Act2Intention framework is proposed, which builds an active mobile agent by integrating understanding, predicting user intentions, and executing decisions, and establishes a standardized platform for developing and evaluating proactive agents and consequently paves the way for research on intention-driven human-com...
Generating realistic and diverse pedestrian background flows is critical for numerous downstream applications, ranging from the training and validation of autonomous driving systems to the simulation of mobile communication networks. While recent diffusion-based models achieve state-of-the-art accuracy, they suffer fro...
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