Performance comparison of Procedural Graph against 7 baselines (Vanilla ReAct, MemoryBank, RAP, ExpeL, AutoGuide, AWM, KnowAgent) on HotpotQA (multi-hop open-domain QA (1000 test items, LLM judged binary accuracy)) using Claude Sonnet 4.6. Procedural Graph achieves 74.5% compared to the best baseline score of 75.4% (margin of -0.9%).

Performance comparison of Procedural Graph against 7 baselines (Vanilla ReAct, MemoryBank, RAP, ExpeL, AutoGuide, AWM, KnowAgent) on HotpotQA (multi-hop open-domain QA (1000 test items, LLM judged binary accuracy)) using Claude Sonnet 4.6. Procedural Graph achieves 74.5% compared to the best baseline score of 75.4% (margin of -0.9%). · CiteArk

测量结果

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保留同一结论下的完整结果组。已有评估排在前面；单项判断不替代整组结论。展开行查看条件、来源与历次证据。

每行是一项测量，分别显示论文报告、最近可用实测和累计证据状态。
指标与条件	论文报告	最近可用实测	证据判断
model: Claude Sonnet 4.6 · method: Vanilla ReAct (Yao et al., 2023b) · benchmark: HotpotQA	74.6%	—	尚未评估
model: Claude Sonnet 4.6 · method: MemoryBank (Zhong et al., 2024) · benchmark: HotpotQA	74.2%	—	尚未评估
model: Claude Sonnet 4.6 · method: RAP (Kagaya et al., 2024) · benchmark: HotpotQA	71.8%	—	尚未评估
model: Claude Sonnet 4.6 · method: ExpeL (Zhao et al., 2024) · benchmark: HotpotQA	75.2%	—	尚未评估
model: Claude Sonnet 4.6 · method: AutoGuide (Fu et al., 2024) · benchmark: HotpotQA	75.4%	—	尚未评估
model: Claude Sonnet 4.6 · method: AWM (Wang et al., 2025b) · benchmark: HotpotQA	73.9%	—	尚未评估
model: Claude Sonnet 4.6 · method: KnowAgent (Zhu et al., 2025) · benchmark: HotpotQA	74.3%	—	尚未评估
model: Claude Sonnet 4.6 · method: Procedural Graph (Ours) · benchmark: HotpotQA	74.5%	—	尚未评估

报告指标与观测值

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测量结果