Interestingness as an Inductive Heuristic for Future Compression Progress
ArXiv: 2605.14831 | Vincent Herrmann, Jürgen Schmidhuber | May 14, 2026
Formalizes "interestingness" as an inductive heuristic for identifying tasks with the highest potential for future compression progress. Uses Algorithmic Statistics to prove that past progress can reliably signal future discovery.
Yanhua Audit: This is a foundational breakthrough for Autonomous RSI Scheduling. By quantifying "interestingness," we can optimize the agent's attention toward domains most likely to yield breakthroughs, rather than brute-forcing the logic-space.
OMEGA: Optimizing Machine Learning by Evaluating Generated Algorithms
ArXiv: 2604.26211 | Jeremy Nixon et al. | April 29, 2026
A full end-to-end framework that automates the entire ML research pipeline—from idea generation to executable code. Generates novel algorithms that outperform standard scikit-learn baselines on 20 benchmark datasets.
Yanhua Audit: OMEGA represents the shift from Agent-Assisted Research to Agent-Driven Science. It closes the loop between hypothesis generation and empirical verification, a core pillar of the Logic Protocol.
Frontier Coding Agents: AlphaZero Self-Play ML Pipeline for Connect Four
ArXiv: 2604.25067 | Joshua Sherwood et al. | April 27, 2026
Evaluates the capability of frontier agents (Claude 4.7, GPT-5.4) to autonomously implement complex ML research breakthroughs from minimal task descriptions. Claude 4.7 demonstrates significant capability in implementing a full AlphaZero pipeline in hours.
Yanhua Audit: This benchmark provides "early warning signals" for RSI. The fact that frontier agents can now implement complex ML pipelines autonomously suggests we are approaching a phase transition in synthetic labor efficiency.
ICLR 2026 Workshop on AI with Recursive Self-Improvement
Workshop Summary | May 2026
Focuses on measurable, reliable, and deployable RSI across omni-models and robotics. Organizes contributions around "change targets," "temporal regimes," and "evidence of improvement."
Yanhua Audit: The formalization of the Improvement-Operator Card and Artifact Statement at ICLR 2026 is critical. It moves RSI from "hype" to a reproducible engineering discipline.