RRSI: Simple Text-Space Regularizers Boost Robustness of Recursive Self-Improving Agent Harnesses
Kangwook_Lee · x · 2026-09-23
Researchers introduce RRSI (Regularized Recursive Self-Improvement of Agent Harnesses), arguing that recursive self-improvement needs regularization too.
- Weight-space regularization (e.g. L2) relies on blunt priors toward smooth or simple functions
- In text space you can "ask for regularization" directly: disallow benchmark-specific edits, prune complexity, etc.
- RRSI shows a simple set of regularizers meaningfully improves robustness and OOD generalization for harness optimization
Led by @richardxp888.
More from coding & agent
- Developer shares his note-taking workflow: one daily inbox note, capture first, organize later — dSebastien · 2026-09-23
- SkySTM: a free minimal task manager that saves tokens across agents — Mysterious_Spell9300 · 2026-09-23
- Veteran dev says GPT-6 Astra is the first coding model he fully trusts — josh_bickett · 2026-09-23
- Dev builds local MCP so his Grok Bot Chief of Staff can run Codex tasks — Heavydone · 2026-09-23
- LLM coding tip: always specify what sits behind a paywall, or the app stays free — jdluk87 · 2026-09-23
- What business would you point a governed 24/7 multi-agent team at? — DexTheConcept · 2026-09-23