Record preliminary transition auxiliary results
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@@ -272,6 +272,14 @@ same four-epoch budget. The primary paper outcome remains activity mAP; the
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transition metrics diagnose whether an activity improvement is genuinely
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transition metrics diagnose whether an activity improvement is genuinely
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associated with better boundary prediction.
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associated with better boundary prediction.
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The preliminary seed-0/1 results are archived in
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[results/easycom_transition_auxiliary_4ep_2026-08-27/](results/easycom_transition_auxiliary_4ep_2026-08-27/README.md).
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Neither R1 nor R2 establishes a meaningful activity-mAP gain. At 0.2 seconds,
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transition prevalence is 11.21718%, while transition AP is approximately
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15.3%, indicating weak but non-random ranking. R2 improves activity mean mAP
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over R1 by only 0.01162 points and transition AP by 0.16660 points. Seed 2 is
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still required before freezing this as a complete null ablation.
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## Current Ego4D context-length results
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## Current Ego4D context-length results
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The following single-seed snapshot was recorded on 2026-08-22. Both variants
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The following single-seed snapshot was recorded on 2026-08-22. Both variants
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122
results/easycom_transition_auxiliary_4ep_2026-08-27/README.md
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results/easycom_transition_auxiliary_4ep_2026-08-27/README.md
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# EasyCom transition-aware auxiliary-head ablation
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Recorded on 2026-08-27 from user-reported remote evaluation output. This is a
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preliminary two-seed snapshot: seed 2 has not been reported, so these numbers
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must not yet be used as a final multi-seed paper result.
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## Experiment contract
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- Dataset: EasyCom.
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- Train split: Sessions 4 through 12, with no development set.
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- Test split: EgoSpeak official Sessions 3, 2, and 1.
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- Backbone: frozen Qwen2.5-Omni-3B Thinker.
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- Representation: 8-second open-stream replay, 2 FPS video, 5 Hz states, final
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four query layers stacked.
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- Readout: concat-MLP followed by the activity MLP.
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- Activity objective: LSTR-MCE.
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- Training budget: 4 epochs, batch size 512, learning rate 7e-5, weight decay
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5e-5, dropout 0.2, 1.6 warmup epochs, warmup factor 0.3.
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- Completed seeds: 0 and 1. Missing seed: 2.
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- Primary evaluation protocol: causal-valid-only activity AP/mAP.
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A positive transition at future horizon h means that the complete three-label
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activity state changes between target rows t+h-1 and t+h.
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- R1: activity loss + 0.2 times weighted transition BCE, with positive weight
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3.
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- R2: R1 loss - 0.1 times exact expected weighted transition correctness.
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## Individual results
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All values below are percentage points.
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| Variant | Seed | 0.2s mAP | BG AP | Wearer AP | Others AP | Mean mAP | Transition 0.2s AP | Transition 0.2s F1@0.5 | Transition mean AP |
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|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|
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| R1 | 0 | 73.51590 | 56.84019 | 77.92448 | 85.78303 | 60.86360 | 15.19153 | 0.46172 | 13.04354 |
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| R1 | 1 | 73.78692 | 56.92102 | 78.63090 | 85.80884 | 60.82023 | 15.32492 | 1.14068 | 13.06174 |
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| R2 | 0 | 73.53288 | 56.89701 | 77.92732 | 85.77432 | 60.86528 | 15.37608 | 0.00000 | 13.11854 |
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| R2 | 1 | 73.82947 | 56.97474 | 78.69340 | 85.82027 | 60.84178 | 15.47356 | 0.84227 | 13.13820 |
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## Two-seed mean and sample standard deviation
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| Variant | 0.2s mAP | Wearer AP | Others AP | Mean mAP | Transition 0.2s AP | Transition mean AP |
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|---|---:|---:|---:|---:|---:|---:|
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| R1 | 73.65141 +/- 0.19164 | 78.27769 +/- 0.49951 | 85.79594 +/- 0.01825 | 60.84192 +/- 0.03067 | 15.25823 +/- 0.09432 | 13.05264 +/- 0.01287 |
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| R2 | 73.68118 +/- 0.20972 | 78.31036 +/- 0.54169 | 85.79729 +/- 0.03249 | 60.85353 +/- 0.01662 | 15.42482 +/- 0.06893 | 13.12837 +/- 0.01390 |
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## Matched-seed comparison with LSTR-MCE
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The baseline values are taken from the existing four-epoch loss-structure
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ablation. Using only the same completed seeds 0 and 1 avoids comparing a
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two-seed transition result with a three-seed baseline mean.
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| Comparison | Delta 0.2s mAP | Delta BG AP | Delta wearer AP | Delta others AP | Delta mean mAP |
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|---|---:|---:|---:|---:|---:|
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| R1 minus LSTR-MCE | +0.04975 | +0.02633 | +0.05942 | +0.06350 | +0.04949 |
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| R2 minus LSTR-MCE | +0.07951 | +0.08160 | +0.09209 | +0.06486 | +0.06110 |
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| R2 minus R1 | +0.02977 | +0.05527 | +0.03267 | +0.00136 | +0.01162 |
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All activity changes are much smaller than the observed seed variation. The
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current evidence therefore does not establish a meaningful activity
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anticipation improvement.
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## Transition diagnostic
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The 0.2-second transition prevalence is 11.21718%, which is also the expected
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AP of a random ranking. R1 reaches 15.19--15.32% AP, or 1.35--1.37 times the
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random baseline. R2 reaches 15.38--15.47%, or 1.37--1.38 times random. The
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auxiliary head therefore learns weak but non-random transition ranking.
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F1 at threshold 0.5 is nearly zero because recall is only 0--0.58%. This fixed
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threshold is not a reliable model-quality measure under weighted BCE: positive
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weight 3 changes probability calibration and remains below the approximately
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7.9 negative-to-positive ratio implied by the test prevalence. Threshold-free
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AP is the appropriate diagnostic here. Any deployable threshold must be
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selected on training-held-out data, not the test set.
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R2 improves transition AP over R1 by only 0.16660 points at 0.2 seconds and
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0.07573 points on the ten-horizon mean. Its activity mean-mAP improvement over
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R1 is only 0.01162 points. Exact expected correctness supplies almost the same
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gradient direction as weighted BCE, so this result is consistent with the two
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terms being largely redundant rather than R2 learning a new sequential policy.
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## Current interpretation
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This is a preliminary null ablation:
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> Exact 200-ms transition supervision provides weak non-random boundary
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> ranking but no meaningful improvement in the primary activity-anticipation
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> metric. Adding exact expected correctness produces negligible further gain.
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This experiment should not be described as interactive reinforcement learning.
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R2 computes the binary-action expectation analytically on fixed offline labels;
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it is a low-variance supervised reward control.
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## Required follow-up
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1. Complete and report seed 2 before freezing the table.
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2. Do not select a transition threshold or tune positive/reward weights on the
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test sessions.
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3. If the transition line is continued, replace the sparse exact-boundary
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target with a pre-specified cumulative transition-hazard target: whether at
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least one transition occurs within the next h steps.
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4. If that structured target also fails to improve activity mAP, treat
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transition auxiliary learning on frozen states as a rejected direction and
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move experiment budget to representation or temporal modeling.
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## Provenance
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- Feature root:
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/data1/yfzx/wangx/Datasets/easycom/omni_features/open_stream_2fps_8s_last4_stack
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- Target root:
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/data1/yfzx/wangx/Datasets/easycom/easycom_target_frame
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- Remote result roots:
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results/easycom-transition-r1-4ep-seed-N and
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results/easycom-transition-r2-4ep-seed-N
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- Source: user-reported summary and diagnostic console output.
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- Raw remote metrics JSON archived locally: no.
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- Full per-horizon activity and transition curves archived locally: no.
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Machine-readable records are in summary.json and metrics.csv. The received
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console values are preserved in raw_console.txt.
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@@ -0,0 +1,8 @@
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variant,seed,horizon_0.2_map,horizon_0.2_background_ap,horizon_0.2_wearer_ap,horizon_0.2_others_ap,ten_horizon_mean_map,transition_positive_rate,transition_horizon_0.2_ap,transition_horizon_0.2_f1_at_0.5,transition_ten_horizon_mean_ap
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lstr-mce,0,73.44637,56.76438,77.86650,85.70824,60.84861,,,,
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lstr-mce,1,73.75696,56.94418,78.57004,85.75664,60.73626,,,,
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r1-supervised,0,73.51590,56.84019,77.92448,85.78303,60.86360,11.21718,15.19153,0.46172,13.04354
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r1-supervised,1,73.78692,56.92102,78.63090,85.80884,60.82023,11.21718,15.32492,1.14068,13.06174
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r2-expected-reward,0,73.53288,56.89701,77.92732,85.77432,60.86528,11.21718,15.37608,0.00000,13.11854
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r2-expected-reward,1,73.82947,56.97474,78.69340,85.82027,60.84178,11.21718,15.47356,0.84227,13.13820
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@@ -0,0 +1,34 @@
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r1 seed=0: 0.2s_mAP=73.51590, BG_AP=56.84019, wearer_AP=77.92448, others_AP=85.78303, mean_mAP=60.86360, transition_0.2s_AP=15.19153, transition_0.2s_F1=0.46172, transition_mean_AP=13.04354
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r1 seed=1: 0.2s_mAP=73.78692, BG_AP=56.92102, wearer_AP=78.63090, others_AP=85.80884, mean_mAP=60.82023, transition_0.2s_AP=15.32492, transition_0.2s_F1=1.14068, transition_mean_AP=13.06174
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r2 seed=0: 0.2s_mAP=73.53288, BG_AP=56.89701, wearer_AP=77.92732, others_AP=85.77432, mean_mAP=60.86528, transition_0.2s_AP=15.37608, transition_0.2s_F1=0.00000, transition_mean_AP=13.11854
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r2 seed=1: 0.2s_mAP=73.82947, BG_AP=56.97474, wearer_AP=78.69340, others_AP=85.82027, mean_mAP=60.84178, transition_0.2s_AP=15.47356, transition_0.2s_F1=0.84227, transition_mean_AP=13.13820
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Mean +/- sample standard deviation
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r1:
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0.2s_mAP 73.65141 +/- 0.19164
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BG_AP 56.88061 +/- 0.05716
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wearer_AP 78.27769 +/- 0.49951
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others_AP 85.79594 +/- 0.01825
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mean_mAP 60.84192 +/- 0.03067
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transition_0.2s_AP 15.25823 +/- 0.09432
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transition_0.2s_F1 0.80120 +/- 0.48010
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transition_mean_AP 13.05264 +/- 0.01287
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r2:
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0.2s_mAP 73.68118 +/- 0.20972
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BG_AP 56.93587 +/- 0.05496
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wearer_AP 78.31036 +/- 0.54169
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others_AP 85.79729 +/- 0.03249
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mean_mAP 60.85353 +/- 0.01662
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transition_0.2s_AP 15.42482 +/- 0.06893
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transition_0.2s_F1 0.42113 +/- 0.59557
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transition_mean_AP 13.12837 +/- 0.01390
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Transition prevalence diagnostic:
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r1 seed=0: positive_rate=11.21718%, AP=15.19153%, AP/random=1.35x, P@0.5=42.85714%, R@0.5=0.23211%, F1@0.5=0.46172%
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r1 seed=1: positive_rate=11.21718%, AP=15.32492%, AP/random=1.37x, P@0.5=33.33333%, R@0.5=0.58027%, F1@0.5=1.14068%
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r2 seed=0: positive_rate=11.21718%, AP=15.37608%, AP/random=1.37x, P@0.5=0.00000%, R@0.5=0.00000%, F1@0.5=0.00000%
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r2 seed=1: positive_rate=11.21718%, AP=15.47356%, AP/random=1.38x, P@0.5=40.74074%, R@0.5=0.42553%, F1@0.5=0.84227%
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170
results/easycom_transition_auxiliary_4ep_2026-08-27/summary.json
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{
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"schema_version": 1,
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"recorded_date": "2026-08-27",
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"status": "preliminary_two_seed_null_ablation",
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"missing_seed": 2,
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"dataset": "EasyCom",
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"split": {
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"train_sessions": [4, 5, 6, 7, 8, 9, 10, 11, 12],
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"dev_sessions": [],
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"test_sessions": [3, 2, 1]
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},
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"model": {
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"backbone": "Qwen2.5-Omni-3B",
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"thinker_frozen": true,
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"streaming_mode": "open-stream-replay",
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"memory_seconds": 8,
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"video_fps": 2,
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"prediction_hz": 5,
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"selected_layers": "last_4_query_states",
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"layer_fusion": "concat-mlp"
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},
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"training": {
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"epochs": 4,
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"batch_size": 512,
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"learning_rate": 0.00007,
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"weight_decay": 0.00005,
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"warmup_epochs": 1.6,
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"warmup_factor": 0.3,
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"dropout": 0.2,
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"activity_loss": "lstr-mce",
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"completed_seeds": [0, 1],
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"checkpoint_selection": "final_epoch_no_dev"
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},
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"transition_definition": {
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"positive": "activity[t+h] differs from activity[t+h-1]",
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"r1": {
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"objective": "activity + 0.2 * weighted_transition_bce",
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"positive_weight": 3.0
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},
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"r2": {
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"objective": "activity + 0.2 * transition - 0.1 * expected_transition_correctness",
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"positive_weight": 3.0,
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"reward_weight": 0.1,
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"expectation": "analytic_binary_action_expectation_without_sampling"
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}
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},
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"evaluation": {
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"activity_protocol": "causal_valid_only",
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"transition_horizon_0.2_positive_rate_percent": 11.21718,
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"transition_random_ap_percent": 11.21718
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},
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"individual_run_summary_percent": [
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{
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"variant": "r1-supervised",
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"seed": 0,
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"horizon_0.2_map": 73.51590,
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"horizon_0.2_background_ap": 56.84019,
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"horizon_0.2_wearer_ap": 77.92448,
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"horizon_0.2_others_ap": 85.78303,
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"ten_horizon_mean_map": 60.86360,
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"transition_horizon_0.2_ap": 15.19153,
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"transition_horizon_0.2_f1_at_0.5": 0.46172,
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"transition_ten_horizon_mean_ap": 13.04354,
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"transition_ap_over_random": 1.35
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},
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{
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"variant": "r1-supervised",
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"seed": 1,
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"horizon_0.2_map": 73.78692,
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"horizon_0.2_background_ap": 56.92102,
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"horizon_0.2_wearer_ap": 78.63090,
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"horizon_0.2_others_ap": 85.80884,
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"ten_horizon_mean_map": 60.82023,
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"transition_horizon_0.2_ap": 15.32492,
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"transition_horizon_0.2_f1_at_0.5": 1.14068,
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"transition_ten_horizon_mean_ap": 13.06174,
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"transition_ap_over_random": 1.37
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},
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{
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"variant": "r2-expected-reward",
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"seed": 0,
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"horizon_0.2_map": 73.53288,
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"horizon_0.2_background_ap": 56.89701,
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"horizon_0.2_wearer_ap": 77.92732,
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"horizon_0.2_others_ap": 85.77432,
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"ten_horizon_mean_map": 60.86528,
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"transition_horizon_0.2_ap": 15.37608,
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"transition_horizon_0.2_f1_at_0.5": 0.00000,
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"transition_ten_horizon_mean_ap": 13.11854,
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"transition_ap_over_random": 1.37
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},
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{
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"variant": "r2-expected-reward",
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"seed": 1,
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"horizon_0.2_map": 73.82947,
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"horizon_0.2_background_ap": 56.97474,
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"horizon_0.2_wearer_ap": 78.69340,
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"horizon_0.2_others_ap": 85.82027,
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"ten_horizon_mean_map": 60.84178,
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"transition_horizon_0.2_ap": 15.47356,
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"transition_horizon_0.2_f1_at_0.5": 0.84227,
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"transition_ten_horizon_mean_ap": 13.13820,
|
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|
"transition_ap_over_random": 1.38
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"two_seed_summary_percent": {
|
||||||
|
"r1-supervised": {
|
||||||
|
"horizon_0.2_map": {"mean": 73.65141, "sample_std": 0.19164},
|
||||||
|
"horizon_0.2_background_ap": {"mean": 56.88061, "sample_std": 0.05716},
|
||||||
|
"horizon_0.2_wearer_ap": {"mean": 78.27769, "sample_std": 0.49951},
|
||||||
|
"horizon_0.2_others_ap": {"mean": 85.79594, "sample_std": 0.01825},
|
||||||
|
"ten_horizon_mean_map": {"mean": 60.84192, "sample_std": 0.03067},
|
||||||
|
"transition_horizon_0.2_ap": {"mean": 15.25823, "sample_std": 0.09432},
|
||||||
|
"transition_horizon_0.2_f1_at_0.5": {"mean": 0.80120, "sample_std": 0.48010},
|
||||||
|
"transition_ten_horizon_mean_ap": {"mean": 13.05264, "sample_std": 0.01287}
|
||||||
|
},
|
||||||
|
"r2-expected-reward": {
|
||||||
|
"horizon_0.2_map": {"mean": 73.68118, "sample_std": 0.20972},
|
||||||
|
"horizon_0.2_background_ap": {"mean": 56.93587, "sample_std": 0.05496},
|
||||||
|
"horizon_0.2_wearer_ap": {"mean": 78.31036, "sample_std": 0.54169},
|
||||||
|
"horizon_0.2_others_ap": {"mean": 85.79729, "sample_std": 0.03249},
|
||||||
|
"ten_horizon_mean_map": {"mean": 60.85353, "sample_std": 0.01662},
|
||||||
|
"transition_horizon_0.2_ap": {"mean": 15.42482, "sample_std": 0.06893},
|
||||||
|
"transition_horizon_0.2_f1_at_0.5": {"mean": 0.42113, "sample_std": 0.59557},
|
||||||
|
"transition_ten_horizon_mean_ap": {"mean": 13.12837, "sample_std": 0.01390}
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"paired_mean_deltas_percent": {
|
||||||
|
"r1_minus_lstr_mce": {
|
||||||
|
"horizon_0.2_map": 0.04975,
|
||||||
|
"horizon_0.2_background_ap": 0.02633,
|
||||||
|
"horizon_0.2_wearer_ap": 0.05942,
|
||||||
|
"horizon_0.2_others_ap": 0.06350,
|
||||||
|
"ten_horizon_mean_map": 0.04949
|
||||||
|
},
|
||||||
|
"r2_minus_lstr_mce": {
|
||||||
|
"horizon_0.2_map": 0.07951,
|
||||||
|
"horizon_0.2_background_ap": 0.08160,
|
||||||
|
"horizon_0.2_wearer_ap": 0.09209,
|
||||||
|
"horizon_0.2_others_ap": 0.06486,
|
||||||
|
"ten_horizon_mean_map": 0.06110
|
||||||
|
},
|
||||||
|
"r2_minus_r1": {
|
||||||
|
"horizon_0.2_map": 0.02977,
|
||||||
|
"horizon_0.2_background_ap": 0.05527,
|
||||||
|
"horizon_0.2_wearer_ap": 0.03267,
|
||||||
|
"horizon_0.2_others_ap": 0.00136,
|
||||||
|
"ten_horizon_mean_map": 0.01162,
|
||||||
|
"transition_horizon_0.2_ap": 0.16660,
|
||||||
|
"transition_ten_horizon_mean_ap": 0.07573
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"interpretation": {
|
||||||
|
"activity_improvement_established": false,
|
||||||
|
"transition_ranking": "weak_but_above_random",
|
||||||
|
"threshold_0.5_is_calibrated": false,
|
||||||
|
"r2_additional_gain": "negligible",
|
||||||
|
"r2_is_interactive_rl": false,
|
||||||
|
"recommended_next_target": "cumulative_transition_hazard",
|
||||||
|
"required_before_final_claim": "complete_seed_2"
|
||||||
|
},
|
||||||
|
"provenance": {
|
||||||
|
"source": "user_reported_remote_summary_and_diagnostic_console",
|
||||||
|
"remote_feature_root": "/data1/yfzx/wangx/Datasets/easycom/omni_features/open_stream_2fps_8s_last4_stack",
|
||||||
|
"remote_target_root": "/data1/yfzx/wangx/Datasets/easycom/easycom_target_frame",
|
||||||
|
"raw_remote_metrics_archived": false,
|
||||||
|
"full_horizon_metrics_archived": false
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
Reference in New Issue
Block a user