Record EgoSpeak three-level evaluation
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@@ -57,3 +57,13 @@ disjoint Sessions 4--12 calibration reviews and out-of-fold predictions.
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Before manuscript reporting, freeze the 2.0-second ENTRY cap, 0.6-second YIELD
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cap, positive anchor-selection policy, and multiple-competitor handling using
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training-side data only.
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## Recorded Sessions 1--3 baseline
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The first threshold-free run gives ENTRY AP 52.487% (163 positive, 335 hard
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negative; 32.731% prevalence) and INT/YIELD AP 20.135% (28 positive, 109 hard
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negative; 20.438% prevalence). It excludes 81 ENTRY and 5 INT cases as invalid
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or post-outcome. These are provisional LLM-assisted labels, not human-reviewed
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confirmatory results. Dense, raw-boundary, and opportunity metrics and their
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Figure 7 interpretation are frozen together in the
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[`2026-09-16 result record`](../results/easycom_egospeak_three_level_eval_2026-09-16/README.md).
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@@ -159,6 +159,15 @@ adapter 实验。
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- addressed-to-wearer response recall 和 latency;
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- wearer 已经讲话时的 yield recall 和 latency。
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首个 Sessions 1--3 EgoSpeak MiniROADA A+V 基线已把三层指标分开:dense 0.2 秒
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mAP/十-horizon mean mAP 为 `74.124/61.155`,raw wearer onset/offset mean AP 为
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`24.491/38.024`;在尚未人工复核的 LLM-assisted matched opportunities 上,ENTRY
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AP 为 `52.487`(prevalence `32.731%`),INT/YIELD AP 为 `20.135`
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(prevalence `20.438%`)。因此 EgoSpeak Figure 7 式连续 wearer score 只能作为 dense
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forecasting 的定性解释,不能代替 boundary 或 semantic opportunity 评估。完整 horizon
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曲线和限制见
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[`three-level baseline record`](../results/easycom_egospeak_three_level_eval_2026-09-16/README.md)。
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### P3:第一优先方法——匿名逐人时序旁路
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先做易解释、能在 8×L20 上完成的旁路,而不是直接修改整个 Thinker。
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