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AgentHPOBench: A Benchmark For Evaluating LLM Agents as Sequential Hyperparameter Optimizers
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- AgentHPOBench is a benchmark with 30 machine learning tasks for evaluating whether LLM agents can iteratively optimize hyperparameters based on experimental results.
- 为何重要
- ML engineers and researchers building autonomous agents should care when assessing whether agents can learn from experimental evidence and refine configurations.
- 注意
- Current agents show optimization ability but struggle with sustained iteration, complex log interpretation, and consistently reaching reference performance levels.
收听本摘要
- agent
- llm
- eval
- benchmark
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