A survey that defines Compound AI Systems, proposes a multi-dimensional taxonomy based on component roles and orchestration strategies, reviews four foundational paradigms, and identifies key challenges for future research.
arXiv preprint arXiv:2403.15452 , year=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
roles
background 1polarities
background 1representative citing papers
CAHL jointly optimizes hierarchical policies for tool-augmented LLMs via RLVR and reports improved results on API-Bank, BFCL, and Bamboogle.
citing papers explorer
-
From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems
A survey that defines Compound AI Systems, proposes a multi-dimensional taxonomy based on component roles and orchestration strategies, reviews four foundational paradigms, and identifies key challenges for future research.
-
Capability-Aligned Hierarchical Learning for Tool-Augmented LLMs
CAHL jointly optimizes hierarchical policies for tool-augmented LLMs via RLVR and reports improved results on API-Bank, BFCL, and Bamboogle.