Why The Guardrail?
AI safety research moves fast. With hundreds of new papers published daily across arXiv categories like cs.AI, cs.LG, cs.CL, and stat.ML, staying current is a challenge. The Guardrail solves this with a fully automated pipeline that finds and summarizes the papers that matter.
How it works
- Daily paper ingestion from arXiv AI and ML categories at 6:00 AM UTC.
- Gemini Flash 3 analyzes titles and abstracts for AI safety relevance.
- Relevant papers are categorized into a 10-category AI safety taxonomy.
- Each paper receives a concise 1 to 2 sentence summary.
- Results are committed and deployed via GitHub Actions to GitHub Pages.
Update schedule
The pipeline runs automatically every day at 6:00 AM UTC. New papers typically appear within 24 to 48 hours of arXiv submission, depending on arXiv processing times.
Category taxonomy
- AI Control: Maintaining human oversight and control over AI systems.
- RLHF: Reinforcement Learning from Human Feedback and preference learning.
- I/O Classifiers: Input and output monitoring, filtering, and safety classifiers.
- Mechanistic Interpretability: Understanding internal model representations and circuits.
- Position Paper: Opinion pieces, policy proposals, and theoretical frameworks.
- Alignment Theory: Foundational alignment research, goal specification, value learning.
- Robustness and Security: Adversarial robustness, jailbreaking, prompt injection defenses.
- Evaluations and Benchmarks: Safety evaluations, capability assessments, red-teaming.
- Governance and Policy: Regulation and responsible deployment practices.
- Agent Safety: Safety considerations for autonomous agents and tool use.
Limitations
- LLM-based filtering is imperfect, so some relevant papers may be missed.
- Summaries are AI-generated and may not capture all nuances.
- Category assignments and relevance scores rely on titles and abstracts only.
- Processing delays mean papers appear 24 to 48 hours after submission.