The Guardrail

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

1. Daily paper ingestion from arXiv AI and ML categories at 6:00 AM UTC.
2. An LLM analyzes titles and abstracts for AI safety relevance.
3. Relevant papers are assigned to one or more of six broad categories, plus fine-grained topic tags.
4. Each paper receives a concise 1 to 2 sentence summary.
5. 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

• Interpretability: Understanding how models work internally, including circuits, features, representations, and mechanistic analysis.
• Alignment & Learning: Training AI to do what we want, including RLHF, preference learning, value alignment, reward modeling, and goal specification.
• Robustness & Security: Adversarial attacks, jailbreaking, prompt injection, defenses, content filtering, and guardrails.
• Evaluations: Measuring AI capabilities or safety, including benchmarks, red-teaming, safety evals, and capability assessments.
• Agents & Control: Autonomous AI systems, tool use, human oversight, controllability, corrigibility, and multi-agent safety.
• Policy & Governance: AI regulation, deployment practices, societal impact, risk assessment, position papers, and policy proposals.

Each paper also gets fine-grained tags from a taxonomy of 51 topics. The model can propose new tags, which are added after human approval.