Reproducible Research in Network Modeling
2026-07-21T07:23:55Z•6b171cdfa87ee07c4f3e2464e8c4d6f5d76642b8314da174d460887dea625fbe
6GCAD-TDMAKV cacheLLM servingMAC protocolsMixture-of-Experts (MoE)NPU schedulingUAV/air mobilityWasserstein DROadversarial MLavailabilitydeterministic schedulingdistributed inferenceedge computingprivacyreinforcement learning (Q-learning)resource exhaustionspectrum allocationsupply-chain/implementation risk
What happened
This document bundle contains recent research on networked AI and wireless systems (6G/LWAM), LLM serving and caching, distributed MoE inference at the edge, NPU scheduling, UAV formation MAC control, and learning-based spectrum allocation. Collectively these works enable higher performance and autonomy but introduce new security and safety attack surfaces: KV-cache reservation uncertainty (preemption/recomputation) and memory-exhaustion/availability attacks against LLM serving; model-serving and distributed-MoE substitution strategies that can enable model-quality attacks, evasion or data-exfi
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_ni
- Record identifier
- 6b171cdfa87ee07c4f3e2464e8c4d6f5d76642b8314da174d460887dea625fbe
- Enrichment time
- 2026-07-21T07:23:55Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.