The paper introduces Relay On-Policy Distillation (Relay-OPD), a method for on-policy distillation that constructs relay trajectories to address prefix failure and improve performance.

This paper investigates how network perturbations can alter the asymptotic agreement trajectory in distributed coordination systems, proving fragility in standard cooperative output regulation schemes…

This paper introduces a new variant of the Traveling Salesman Problem where the goal is to find two paths connecting a set of sites while minimizing the Fréchet distance between the two paths.

Proposed an asynchronous block coordinate descent algorithm for distributed trajectory estimation in robotics, reducing communications by up to 96.9% and achieving exponential convergence.

This paper introduces Path Consistency Scoring (PCS), a framework that evaluates router geolocation as a path-level consistency problem and produces a path consistency score based on a Hidden Markov M…

This paper proposes a UAV trajectory optimization framework with continual transfer learning within the O-RAN architecture for 6G cellular systems.

This paper proposes a hierarchical analytical framework to characterize region-level latency differences in Low-Earth orbit satellite Internet using Starlink RTT measurements.

Stochastic Lifting is a novel technique that enhances the modeling of stochastic physical systems by introducing independent random labels to state transitions, allowing a single network to generate d…

This paper presents a randomized algorithm that runs in $ ilde{O}(n^2)$ time and, with high probability, guarantees a 2-approximation for all pairs at distance at least $c$ in an undirected, unweighte…

The paper introduces CAN-QA, a novel question-answering benchmark that reformulates CAN traffic analysis from a classification task to a reasoning task, demonstrating that current LLMs struggle with c…

This paper analyzes darknet traffic to characterize advanced, AI-assisted bot reconnaissance, finding that modern evasion techniques allow most bot traffic to bypass standard IDS thresholds.

The paper introduces SafetyDrift, a predictive model that forecasts when AI agents will violate safety protocols by analyzing the cumulative risk across sequences of individually safe actions.

The paper introduces a higher-order network framework to compare observed and simulated human mobility data, demonstrating that while synthetic data is promising, current simulation models have specif…

The paper introduces EvoXXLTraffic, an ultra-large, sensor-evolving dataset that simulates real-world road network growth, demonstrating that existing state-of-the-art traffic forecasting models fail…

This paper introduces Stigmergic Graph Memory (SGM), a method to improve warehouse throughput in many-to-many Multi-Agent Pickup and Delivery (MAPD) by using a bounded, decaying memory layer to record…

The paper proposes HTP, a novel framework that leverages Large Language Models (LLMs) to first generate abstract travel patterns and then synthesize realistic GPS points, significantly improving traje…

The paper proves XNLP-hardness of Directed Edge Geography and Undirected Edge Geography when parameterized by pathwidth, and shows their fixed-parameter tractability when parameterized by treewidth an…