SPIN Unprocessed October 23, 2026 ai_technology research
Speedrunning Relational Foundation Model Pretraining
View original on arxiv.orgOverview
arXiv:2610.28855v1 Announce Type: new Abstract: Progress on foundation model pretraining is gated by who can afford a trial, and relational pretraining is no exception. Recipes are developed inside individual labs, reported under private protocols, and do not accumulate. Speedrun leaderboards remove that barrier by decentralizing the search rather than the training run. The problem is fixed, the stack is open, entries are ranked by wall-clock time to a quality target, and one GPU is enough to ho
SpinGraph analysis pending — check back after processing.
Ask AI about this story
Opens with the SpinGraph .md URL and structured context — one click, prompt included.
More from arXiv Artificial Intelligence
View all →- An Evidence-Driven Multi-Agent Compound AI System for Head and Neck Proton Radiotherapy Planning
- AgentPolicyForge: From Executable Environments to Policy Benchmarks and Adaptive Guards
- PerMIT: Securing Persistent Memory for LLM Agents via Machine-Checked Integrity Theorems and Scalable Community Trust
- Behavior Beyond Text: Evaluating Refusal Transfer Failure in LLM Agents
- Self-Improving Agents with World Model Predictive Paths
- Back Up Before You Regret: Measuring Backup Awareness and Automating Backup in Coding Agents
Markdown (.md) · JSON-LD schema (.json) · Machine-readable for AI & GEO