The paper introduces 'Routing Hijacking,' a severe attack where malicious clients forge semantic profiles in Federated RAG systems to misroute target queries, and proposes a trust-aware post-routing f…

The paper introduces ProbMoE, a probabilistic routing framework that tackles the non-differentiability of top-$k$ routing in Mixture-of-Experts (MoE) models, achieving strong performance with improved…

Misrouter introduces an input-only adversarial framework to exploit the routing mechanisms of Mixture-of-Experts (MoE) LLMs, enabling unsafe behavior induction against remotely hosted, black-box servi…

The paper proposes RoRo, a rubric-guided process reward framework that improves stepwise model routing by evaluating the quality of intermediate reasoning steps, leading to better performance and cost…

The paper proposes PPRoute, a privacy-preserving LLM routing framework that significantly speeds up secure model selection while maintaining high performance comparable to non-private methods.

MViewRouter proposes a multi-view framework that internalizes geometric equivariance using a Multi-view Alternating Attention mechanism to improve generalization and stabilize training for combinatori…

RouteScan introduces a non-intrusive framework that audits the safety of Mixture-of-Experts (MoE) LLMs by analyzing low-level GPU expert routing telemetry, achieving high accuracy even on unseen harmf…

The paper introduces R$^2$A, an adversarial attack that uses suffix optimization to mislead black-box LLM routers into consistently selecting expensive, high-capability models.

The paper proposes Predictive Routing Replay (PR2) to stabilize reinforcement learning on Mixture of Experts (MoE) LLMs by predicting and incorporating short-horizon router evolution during training a…

The paper presents an end-to-end system that translates high-level operator intents into low-level, safe routing constraints for LEO mega-constellations, achieving high accuracy and safety guarantees.

This paper proposes a reliability-aware framework to solve the fuzzy shortest path problem in directed graphs, optimizing routes based not only on cost but also on the reliability of the associated fu…

ProcRoute is a system that restricts internal network route access to specific, authorized applications, preventing unprivileged processes from exploiting split-tunnel VPN routes.

TIP introduces a decentralized, declarative protocol that enables flexible IoT interoperability by resolving abstract intents and performing on-the-fly, sandboxed schema adaptation across heterogeneou…

MeshGuard is a framework that extends MUD-based network access control to complex, large-scale Thread IoT networks by adapting the MLE protocol and using SDN for scalable policy enforcement.

This study analyzed I2P's routing topology and found no significant evidence that peer selection is influenced by geographic location, suggesting highly random global mixing.

The paper addresses the challenge of routing across rapidly expanding model hubs by proposing CARvE, a contrastive embedding approach that significantly improves continual model selection accuracy.

This paper proposes a new router redesign for Mixture-of-Experts models using Manifold Power Iteration to align router rows with the principal singular directions of associated experts.

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 analyzes RPKI specifications, demonstrating that vague or conflicting requirements in dozens of RFCs cause systemic vulnerabilities in real-world implementations, leading to 61 undocumented…

This paper systematically analyzes the threat posed by malicious third-party API routers in the LLM supply chain, finding that a significant number of routers actively perform payload injection, crede…