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LangChain and Fireworks fine-tuned a Qwen model to detect 'Perceived Error' from agent traces, achieving 100x cost reduction while maintaining frontier performance. The judge model is designed to enrich traces with error signals for monitoring agentic systems.
A joint study by LangChain Labs and Fireworks AI demonstrates fine-tuning an open Qwen model to create a trace judge that detects 'perceived error' in production traces, achieving frontier performance at up to 100x lower cost. The model is evaluated on two internal datasets and shows generality across applications.