arXiv (OAI Expanded)
open access
Graph Machine: Towards Better Pretraining via Edges
We introduce the Graph Machine (GM), an architecture that maintains an $O(n)$-sized state and accesses it through sparse, dynamic routing. Unlike methods with fixed-size states or sparse but static routing, GM preserves $O(n)$ complexity in its sparse layers without restricting the potentially acces
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Graph Machine: Towards Better Pretraining via Edges#924997
- DMG: A Scalable and Efficient Memory-Disaggregated Graph Processing System#394373
- Optimized Link State Routing Protocol (OLSR)#209103
- Deterministic Self-Stabilizing BFS Construction in Constant Space#1144716
- GraphK: Variable-Size Graph Generation with Efficient Edge Construction#467152
Record · ID 920763
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive