Across four domain-model settings on tau-Bench, geometry-conditioned adaptive reasoning triggers raise average task reward from 0.241 (24.1%) under Never-thinking to 0.396 (39.6%) while reducing mean token cost from 104.8k to 93.0k, an 11.2% reduction.

Across four domain-model settings on tau-Bench, geometry-conditioned adaptive reasoning triggers raise average task reward from 0.241 (24.1%) under Never-thinking to 0.396 (39.6%) while reducing mean token cost from 104.8k to 93.0k, an 11.2% reduction. · CiteArk

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指标与条件	论文报告	最近可用实测	证据判断
policy: never-think · benchmark: tau-bench	0.241 fraction	—	尚未评估
policy: geometry-conditioned · benchmark: tau-bench	0.396 fraction	—	尚未评估
policy: never-think · benchmark: tau-bench	104.8 thousands_tokens	—	尚未评估
policy: geometry-conditioned · benchmark: tau-bench	93 thousands_tokens	—	尚未评估
benchmark: tau-bench	11.2 percentage_points	—	尚未评估

Across four domain-model settings on tau-Bench, geometry-conditioned adaptive reasoning triggers raise average task reward from 0.241 (24.1%) under Never-thinking to 0.396 (39.6%) while reducing mean token cost from 104.8k to 93.0k, an 11.2% reduction.

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