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This paper introduces AISE-Bench, a curated benchmark with 1,133 QA pairs for evaluating LLM agents on multi-step API planning and grounded summarization for academic knowledge graphs. The benchmark reveals that even the strongest model achieves only moderate performance, highlighting challenges in stepwise correctness and traceable reasoning.