GPG: Generalized Policy Gradient Theorem for Transformer-based Policies

This article introduces a new theoretical framework, the Generalized Policy Gradient (GPG) theorem, specifically designed for Transformer-based policies. The focus is on providing a more robust and general approach to policy gradient methods within the context of large language models (LLMs) and other transformer applications. The paper likely explores the mathematical underpinnings of GPG, its advantages over existing methods, and potentially provides empirical results demonstrating its effectiveness. The use of 'Generalized' suggests an attempt to broaden the applicability of policy gradient techniques.