QoSFlow: Ensuring Service Quality of Distributed Workflows Using Interpretable Sensitivity Models
2026-03-04T19:48:01Z•358fe38b2f2861015709482fceaa85c595f4f79d7f5123db1ee13eb1a41d804e
D-BusGNNGPULLM-agentsLLM-unlearningMSMOpenBMCRistretto255SMTcarbon-efficiencycryptographyfirmwarehyperthreadingmachine-unlearningnvidia-pcmoutsourcingplatform-identityprefetchingprivacy-preservingschedulingserverlessstatistical-soundness
What happened
This feed collects recent arXiv submissions (Mar 2, 2026) across distributed systems, cloud/cloud-native scheduling, GPU/firmware tooling, cryptography, and ML/LLM infrastructure. Security-relevant items include: nvidia-pcm — a D-Bus-driven platform configuration manager for OpenBMC that enables a single firmware image for multiple hardware variants (potentially increasing attack-surface and emphasizing secure handling of platform identity); 2G2T — a constant-size, statistically sound protocol for outsourcing multi-scalar multiplication (implemented on Ristretto255) with formal soundness; MPU—
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_dc
- Record identifier
- 358fe38b2f2861015709482fceaa85c595f4f79d7f5123db1ee13eb1a41d804e
- Enrichment time
- 2026-03-04T19:48:01Z
- 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.