Not All Prefills Are Equal: PPD Disaggregation for Multi-turn LLM Serving
2026-03-17T07:23:53Z•aa30deefa15cc6331ad897b24ea74c26c08953054b199e72a48a205f3aab1887
CATSadversarial-mlai-assisted-macas-classificationatlasranavailabilityganiot-mackv-cache-reuseleollm-safetyllm-servingnon-rt-rico-ranprefill-disaggregationprivacyrf-map-synthesissatellite-commstcp-bbrtestbed-fidelitytransport-prioritizationweather-impact
What happened
Collection of recent arXiv papers (networking, wireless, and ML-for-telecom) covering: PPD (Prefill-capable Decode) — a dynamic routing scheme to reduce multi-turn LLM serving latency by routing append-prefills to decode nodes and reusing KV caches; EEI-BMA — an AI-assisted, probability-aware MAC for energy-efficient IoT scheduling; SAIL — an unsupervised GAN for controllable RF-map synthesis; Linnaeus — hierarchical AS classification combining network features and LLMs; an LLM-based Net Analyzer rApp for the O-RAN Non-RT RIC emphasizing separation of reasoning and actuation; CATS — a Conducor
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_ni
- Record identifier
- aa30deefa15cc6331ad897b24ea74c26c08953054b199e72a48a205f3aab1887
- Enrichment time
- 2026-03-17T07:23:53Z
- 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.