RAC is a log-based recovery paradigm implemented as an architectural extension to agent frameworks, achieving 1.5-8X better latency and token economy than LLM-based recovery on τ-bench and REALM-Bench.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Robust Agent Compensation (RAC): Teaching AI Agents to Compensate
RAC is a log-based recovery paradigm implemented as an architectural extension to agent frameworks, achieving 1.5-8X better latency and token economy than LLM-based recovery on τ-bench and REALM-Bench.