Reinforcement-Learning

LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels

LeWorldModel introduces a stable end-to-end method for learning latent world models from raw pixels using only two loss terms, achieving competitive planning performance while being 48× faster than foundation-model-based …

AI · Development Editorial Team

Mar 15 arxiv.org 4 min read

AutoResearch-RL: Autonomous Neural Architecture Discovery Through Reinforcement Learning

AutoResearch-RL presents a framework where reinforcement learning agents autonomously conduct neural architecture and hyperparameter research without human supervision, using PPO to optimize code modifications based on …

AI · Development Editorial Team

Feb 27 arxiv.org 4 min read

Ferret-UI Lite: Building Efficient 3B On-Device GUI Agents with Reinforcement Learning

Apple researchers present Ferret-UI Lite, a compact 3B multimodal language model designed for on-device GUI automation across mobile, web, and desktop platforms. The model achieves competitive performance through curated …

AI · Development Editorial Team

Feb 2 arxiv.org 3 min read

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

GEPA introduces a novel prompt optimization approach that uses natural language reflection and Pareto-based evolutionary search to optimize compound AI systems, achieving superior performance compared to reinforcement …

AI · Development Editorial Team