overfeed.news

Agent Evaluation Metric for multi-turn conversations

29d

Age

Published
Collected
Image: AWS Machine Learning Blog

Multi-turn agents fail in ways single-turn evaluation misses: one early mistake corrupts every later turn. This post introduces the Agent Evaluation Metric (AEM), a decomposable, turn-level way to measure agent quality, applied to its first dimension, correctness, to pinpoint the turn that caused a failure and separate it from the turns that inherited it.

Excerpt from the source

Multi-turn agents fail in ways that single-turn evaluation misses: one early mistake quietly corrupts every later turn. This post introduces the Agent Evaluation Metric (AEM), a decomposable, turn-level way to measure agent quality. We apply it to its first dimension, correctness. We show how AEM pinpoints the one turn that caused a failure and separates it from the turns that merely inherited the problem. The correctness challenge in multi-turn agentic conversations Evaluating agent…

Read the full article at aws.amazon.com

overfeed.news indexes and links. We publish a short excerpt — the full article stays at AWS Machine Learning Blog.

Log in to follow this source
Agent Evaluation Metric for multi-turn conversations —…