ADOPT: Optimizing LLM Pipelines with Adaptive Dependency Awareness
Published:Dec 31, 2025 15:46
•1 min read
•ArXiv
Analysis
This paper addresses the challenge of optimizing prompts in multi-step LLM pipelines, a crucial area for complex task solving. The key contribution is ADOPT, a framework that tackles the difficulties of joint prompt optimization by explicitly modeling inter-step dependencies and using a Shapley-based resource allocation mechanism. This approach aims to improve performance and stability compared to existing methods, which is significant for practical applications of LLMs.
Key Takeaways
Reference
“ADOPT explicitly models the dependency between each LLM step and the final task outcome, enabling precise text-gradient estimation analogous to computing analytical derivatives.”