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Notes on recursive self-improvement
3 notes
AI4AI-Bench: Benchmarking LLM Agents in Algorithmic Design for Recursive Self-Improvement
The paper presents AI4AI-Bench, a benchmark for evaluating Large Language Model (LLM) agents in recursive self-improvement. The goal is to determine if an AI system can improve the process that produces future AI…
AI4AI-Bench: Benchmarking LLM Agents in Algorithmic Design for Recursive Self-Improvement
AI4AI-Bench is a new benchmark for assessing the ability of AI agents to design their own training algorithms. The benchmark consists of 10 frozen research repositories covering 10 different algorithm families. In each…
MetaSkill-Evolve: Recursive Self-Improvement of LLM Agents via Two-Timescale Meta-Skill Evolution
MetaSkill-Evolve is a framework that allows for recursive self-improvement of Large Language Model (LLM) agents. This is achieved by introducing a two-timescale system where each agent has both a task skill and a…
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