HIPIF trains LLM agents end-to-end using subgoal-based hierarchical planning and information folding of completed histories, plus hierarchical reflection and process rewards, to handle long-horizon tasks without auxiliary models or expert trajectories.
Gradient coupling: The hidden barrier to generalization in agentic reinforcement learning
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HIPIF: Hierarchical Planning and Information Folding for Long-Horizon LLM Agent Learning
HIPIF trains LLM agents end-to-end using subgoal-based hierarchical planning and information folding of completed histories, plus hierarchical reflection and process rewards, to handle long-horizon tasks without auxiliary models or expert trajectories.