Papers
1–3 of 3Research Paper·Feb 26, 2026
Rudder: Steering Prefetching in Distributed GNN Training using LLM Agents
Large-scale Graph Neural Networks (GNNs) are typically trained by sampling a vertex's neighbors to a fixed distance. Because large input graphs are distributed, training requires frequent irregular co...
6.0 viability
Research Paper·Feb 27, 2026
SLA-Aware Distributed LLM Inference Across Device-RAN-Cloud
Embodied AI requires sub-second inference near the Radio Access Network (RAN), but deployments span heterogeneous tiers (on-device, RAN-edge, cloud) and must not disrupt real-time baseband processing....
3.0 viability
Research Paper·Jan 29, 2026
Learning Provably Correct Distributed Protocols Without Human Knowledge
Provably correct distributed protocols, which are a critical component of modern distributed systems, are highly challenging to design and have often required decades of human effort. These protocols ...
2.0 viability