Update README with verification status of EasyCom components and add results from recent experiments comparing open-stream replay and causal-prefix methods. Introduce new metrics CSV and detailed README for the EasyCom results, including current performance metrics and required follow-up actions before publication.
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# EasyCom: open-stream replay versus causal-prefix
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Recorded on **2026-08-19**. These are the current single-run results reported
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from the remote EasyCom experiments. They are an experiment snapshot, not yet
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the final multi-seed paper numbers.
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## Experiment contract
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- Dataset: EasyCom using EgoSpeak's official split.
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- Train sessions: 7, 11, 10, 6, 9, 4, 8, 5, and 12.
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- Test sessions: 3, 2, and 1.
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- Model: frozen Qwen2.5-Omni-3B Thinker plus the trainable `10 x 3` head.
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- Prediction rate: 5 Hz, one state every 0.2 seconds.
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- Video sampling: 2 FPS.
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- Causal context budget: 20 seconds.
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- Targets: ten future horizons from 0.2 through 2.0 seconds.
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- Metric: frame AP for all three classes, followed by per-horizon mAP and the
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mean over all ten horizons.
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The two representations are trained and evaluated separately. A head trained
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on one representation must not be reused on the other.
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## Summary
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All values below are percentages.
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| Representation | EgoSpeak full-timeline mean mAP | Strict causal mean mAP | Difference from open stream |
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|---|---:|---:|---:|
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| Open-stream replay | 58.316 | 58.326 | — |
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| Causal-prefix | 58.830 | 58.841 | +0.514 / +0.515 |
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For context, the EgoSpeak Table 2 EasyCom reference values currently recorded
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in the project README are 58.7 for Transformer A+V and 60.6 for GRU A+V.
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Accordingly, causal-prefix is 0.130 points above the Transformer reference,
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whereas open-stream replay is 0.384 points below it. Neither reaches the GRU
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A+V result.
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## Full-timeline result by horizon
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| Horizon | Time | Open-stream mAP | Causal-prefix mAP | Causal minus open |
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|---:|---:|---:|---:|---:|
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| 1 | 0.2 s | 69.756 | 72.149 | +2.393 |
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| 2 | 0.4 s | 65.163 | 66.904 | +1.741 |
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| 3 | 0.6 s | 61.578 | 62.468 | +0.890 |
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| 4 | 0.8 s | 58.783 | 59.214 | +0.431 |
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| 5 | 1.0 s | 56.913 | 57.037 | +0.124 |
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| 6 | 1.2 s | 55.727 | 55.789 | +0.062 |
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| 7 | 1.4 s | 54.819 | 54.845 | +0.026 |
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| 8 | 1.6 s | 53.957 | 53.905 | -0.052 |
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| 9 | 1.8 s | 53.459 | 53.265 | -0.194 |
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| 10 | 2.0 s | 53.002 | 52.723 | -0.279 |
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The complete per-class AP values for both evaluation protocols are stored in
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[`metrics.csv`](metrics.csv). [`summary.json`](summary.json) contains the
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machine-readable aggregate comparison.
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## Current interpretation
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1. Causal-prefix is 0.514 mAP points better overall in the exact EgoSpeak
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full-timeline protocol.
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2. Almost all of that advantage occurs at 0.2--0.6 seconds. At 1.2--1.4
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seconds the difference is negligible, and open-stream is slightly better
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at 1.6--2.0 seconds.
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3. The full-timeline and strict-causal means differ by only 0.010--0.011
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points, so unavailable pre-session rows are not driving the comparison.
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4. The short-horizon pattern is consistent with block-local audio processing,
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partial-block AV/TMRoPE organization, or other 2-second boundary effects
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weakening precise speech-onset/offset cues. It does not look like a general
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loss of longer-horizon conversational information.
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5. Previous smoke tests showed exact open-stream cache replay but a lower
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cosine against the continuous-window representation. This supports a real
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representation-semantics difference rather than a cache-copy error.
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## Required follow-up before publication
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- Repeat head training with at least three identical seeds for both modes and
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report mean and standard deviation.
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- Group feature cosine and AP/mAP by the ten 0.2-second phases inside each
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2-second block to test for a block-boundary effect.
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- Compare samples before and after the 20-second memory budget fills to isolate
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input segmentation from rolling-memory behavior.
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- Archive the original remote `metrics.json`, checkpoint configuration, git
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commit, Transformers version, and Qwen model revision alongside the final
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paper results. The numbers in this snapshot were transcribed from the
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reported console tables.
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representation,protocol,horizon,seconds,background_ap_percent,camera_wearer_ap_percent,other_people_ap_percent,map_percent
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open_stream_replay,egospeak_full_timeline,1,0.2,53.605,74.331,81.331,69.756
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open_stream_replay,egospeak_full_timeline,2,0.4,47.066,69.402,79.020,65.163
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open_stream_replay,egospeak_full_timeline,3,0.6,42.615,64.600,77.520,61.578
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open_stream_replay,egospeak_full_timeline,4,0.8,39.463,60.641,76.244,58.783
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open_stream_replay,egospeak_full_timeline,5,1.0,38.002,57.371,75.367,56.913
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open_stream_replay,egospeak_full_timeline,6,1.2,37.398,55.258,74.523,55.727
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open_stream_replay,egospeak_full_timeline,7,1.4,36.933,53.400,74.126,54.819
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open_stream_replay,egospeak_full_timeline,8,1.6,36.653,51.502,73.716,53.957
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open_stream_replay,egospeak_full_timeline,9,1.8,36.527,50.346,73.504,53.459
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open_stream_replay,egospeak_full_timeline,10,2.0,36.673,49.089,73.246,53.002
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open_stream_replay,causal_valid_only,1,0.2,53.605,74.331,81.336,69.757
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open_stream_replay,causal_valid_only,2,0.4,47.066,69.402,79.029,65.166
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open_stream_replay,causal_valid_only,3,0.6,42.615,64.607,77.532,61.585
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open_stream_replay,causal_valid_only,4,0.8,39.463,60.652,76.259,58.792
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open_stream_replay,causal_valid_only,5,1.0,38.002,57.386,75.385,56.924
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open_stream_replay,causal_valid_only,6,1.2,37.398,55.277,74.543,55.739
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open_stream_replay,causal_valid_only,7,1.4,36.933,53.421,74.148,54.834
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open_stream_replay,causal_valid_only,8,1.6,36.656,51.522,73.740,53.973
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open_stream_replay,causal_valid_only,9,1.8,36.529,50.365,73.530,53.475
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open_stream_replay,causal_valid_only,10,2.0,36.676,49.107,73.275,53.019
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causal_prefix,egospeak_full_timeline,1,0.2,56.402,75.843,84.203,72.149
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causal_prefix,egospeak_full_timeline,2,0.4,48.713,70.695,81.305,66.904
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causal_prefix,egospeak_full_timeline,3,0.6,43.007,65.451,78.946,62.468
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causal_prefix,egospeak_full_timeline,4,0.8,39.482,61.051,77.107,59.214
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causal_prefix,egospeak_full_timeline,5,1.0,37.773,57.423,75.915,57.037
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causal_prefix,egospeak_full_timeline,6,1.2,37.197,54.929,75.241,55.789
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causal_prefix,egospeak_full_timeline,7,1.4,36.884,53.060,74.590,54.845
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causal_prefix,egospeak_full_timeline,8,1.6,36.514,50.916,74.283,53.905
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causal_prefix,egospeak_full_timeline,9,1.8,36.424,49.471,73.901,53.265
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causal_prefix,egospeak_full_timeline,10,2.0,36.095,48.407,73.667,52.723
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causal_prefix,causal_valid_only,1,0.2,56.402,75.843,84.209,72.151
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causal_prefix,causal_valid_only,2,0.4,48.713,70.695,81.315,66.908
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causal_prefix,causal_valid_only,3,0.6,43.007,65.458,78.960,62.475
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causal_prefix,causal_valid_only,4,0.8,39.482,61.062,77.123,59.223
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causal_prefix,causal_valid_only,5,1.0,37.773,57.438,75.934,57.048
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causal_prefix,causal_valid_only,6,1.2,37.197,54.947,75.262,55.802
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causal_prefix,causal_valid_only,7,1.4,36.884,53.081,74.612,54.859
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causal_prefix,causal_valid_only,8,1.6,36.517,50.936,74.308,53.920
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causal_prefix,causal_valid_only,9,1.8,36.426,49.489,73.928,53.281
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causal_prefix,causal_valid_only,10,2.0,36.098,48.425,73.697,52.740
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{
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"schema_version": 1,
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"recorded_date": "2026-08-19",
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"status": "single_run_snapshot",
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"dataset": "EasyCom",
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"split": {
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"train_sessions": [7, 11, 10, 6, 9, 4, 8, 5, 12],
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"test_sessions": [3, 2, 1]
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},
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"model": "Qwen2.5-Omni-3B Thinker",
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"head": "MLP 2048 -> 1024 -> 30, reshaped to 10 x 3",
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"prediction_step_seconds": 0.2,
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"video_fps": 2,
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"memory_seconds": 20,
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"metrics_percent": {
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"open_stream_replay": {
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"egospeak_full_timeline_mean_map": 58.316,
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"causal_valid_only_mean_map": 58.326,
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"egospeak_full_timeline_horizon_map": [
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69.756,
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65.163,
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61.578,
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58.783,
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56.913,
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55.727,
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54.819,
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53.957,
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53.459,
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53.002
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]
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},
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"causal_prefix": {
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"egospeak_full_timeline_mean_map": 58.830,
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"causal_valid_only_mean_map": 58.841,
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"egospeak_full_timeline_horizon_map": [
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72.149,
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66.904,
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62.468,
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59.214,
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57.037,
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55.789,
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54.845,
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53.905,
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53.265,
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52.723
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]
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},
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"causal_prefix_minus_open_stream": {
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"egospeak_full_timeline_mean_map": 0.514,
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"causal_valid_only_mean_map": 0.515,
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"egospeak_full_timeline_horizon_map": [
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2.393,
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1.741,
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0.890,
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0.431,
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0.124,
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0.062,
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0.026,
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-0.052,
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-0.194,
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-0.279
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]
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}
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},
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"egospeak_table2_reference_percent": {
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"easycom_transformer_audio_video_mean_map": 58.7,
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"easycom_gru_audio_video_mean_map": 60.6
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},
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"provenance": {
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"source": "User-reported remote infer_turn_head.py console tables",
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"raw_metrics_json_archived_here": false,
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"multi_seed": false
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}
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}
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