Meta-reasoning in autonomous agents: performance gains across benchmarks and models
Year: 2026
Type: article
Abstract: Introduction: Meta-reasoning, the ability of an autonomous agent to monitor and regulate its own reasoning processes, has emerged as a critical component for achieving adaptive and trustworthy artificial intelligence. However, limited empirical evidence quantifies how meta-reasoning impacts agent performance across diverse contexts and model architectures. This study presents a comprehensive empirical analysis of meta-reasoning capabilities in large language model (LLM)-based autonomous agents using two established benchmarks: GAIA (General AI Assistants) and AgentBench.
Source: Academia AI and Applications
DOI: 10.20935/acadai8229
Institutions: Amazon (United States), ServiceNow (United States)
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7147435254