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continual learning 26 reinforcement learning 9 language models 5 large language models 4 robotics 4 agents 3 generative models 3 multi-agent systems 3 recursive self-improvement 3 vision-language models 3

14 SEP 2026 · Paper

Dream-RSI: Recursive Self-Improvement through Evolving Worlds

This paper introduces Dream-RSI, a framework for recursive self-improvement in exploration, which helps autonomous AI agents discover high-value solutions more efficiently by using a replay simulator to provide low-cost feedback. Practitioners might care because effective exploration is crucial for AI progress, and Dream-RSI can improve discovery quality and reduce costs.

recursive self-improvement exploration reinforcement learning meta-search spaces off-policy learning low-cost feedback

14 SEP 2026 · Paper

Not All Prompts Are Equal: Exploration-Guided Prompt Scaffolding for Multimodal Reinforcement Post-Training

This paper proposes a way to improve online reinforcement learning by adapting the training prompts used with large language models to make them more informative, and shows that this approach can lead to better performance on a variety of tasks. Practitioners might care because it could help them get better results from their language models.

reinforcement learning multimodal models prompt engineering exploration large language models