Retroformer: Large Language Agents With Policy Gradient Optimization
Large language models becoming autonomous agents capable of performing multi-step tasks. New approach uses retrospective model & policy gradient optimization to refine prompts & improve performance over time.
This is a Plain English Papers summary of a research paper called Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization. If you like these kinds of analysis, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter. Overview Emerging trend of large language models (LLMs) becoming autonomous language agents capable of performing multi-step tasks Existing agents not optimized using environment-specific rewards Iterative refinement through verbal feedback, but no gradient-based learning from rewards Introduces a framework for reinforcing l...