PILLAR 4 · 0 PAPERS · NO SEARCH RUN YET
Edge inference & real-time constraints
Running learned models on edge silicon under hard latency budgets, and the effect of wireless tail latency on time-critical decisions.
Search string (see Methods for the per-database form)
("edge inference" OR "edge deployment" OR "Jetson" OR "TensorRT" OR "on-device" OR "embedded GPU") AND ("latency" OR "real-time" OR "deadline" OR "tail latency" OR "p99" OR "jitter" OR "quantiz*" OR "INT8") AND ("safety" OR "graph neural" OR "GNN" OR "robot*" OR "wireless" OR "Wi-Fi" OR "5G")Included papers
| Paper | Year | Venue | Contribution | Methods | Relevance | Tags |
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GAPS THIS PILLAR LEAVES OPEN
- No included paper in this pillar addresses multi-agent state
- No included paper in this pillar addresses non-generative inference
- No included paper in this pillar addresses latency / jitter aware
- No included paper in this pillar addresses time-to-irreversibility
- No included paper in this pillar addresses edge deployment
- No included paper in this pillar addresses human handoff
- No included paper in this pillar addresses cross-domain evaluation