Structured memory improves precision on deterministic financial calculations while retrieval-augmented generation outperforms in conversational settings, supporting a hybrid deployment framework for resource-constrained SMEs.
Large language model is semi-parametric reinforcement learning agent
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
representative citing papers
A survey that provides a taxonomy of methods for improving planning in LLM-based agents across task decomposition, plan selection, external modules, reflection, and memory.
citing papers explorer
-
Architecture Matters More Than Scale: A Comparative Study of Retrieval and Memory Augmentation for Financial QA Under SME Compute Constraints
Structured memory improves precision on deterministic financial calculations while retrieval-augmented generation outperforms in conversational settings, supporting a hybrid deployment framework for resource-constrained SMEs.
-
Understanding the planning of LLM agents: A survey
A survey that provides a taxonomy of methods for improving planning in LLM-based agents across task decomposition, plan selection, external modules, reflection, and memory.