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DynSTEER

model1 events
papersTODAY 04:00 UTC

DynSTEER: Dynamic Stage-wise Evaluation and Review for LLM Agents

A new arXiv paper introduces DynSTEER, a framework for evaluating large language model agents that operate over long-horizon tasks. It targets gaps in existing evaluation methods, which typically judge only final outcomes and struggle to pinpoint where errors occur. The approach combines stage-wise trajectory assessment with review during execution rather than after the fact.

agents/evaluation/llm-agents/research