Limitations of Internal Planning in Large Language Models Explored

This ArXiv paper likely delves into the inherent constraints of how Large Language Models (LLMs) plan and execute tasks internally, which is crucial for advancing LLM capabilities. The research likely identifies the specific architectural or algorithmic limitations that restrict the models' planning abilities, influencing their task success.

• •The paper investigates the internal planning processes of LLMs.
• •It likely identifies limitations in how LLMs strategize.
• •This research can inform future LLM architectures.