Add 50K persistent-channel scan for LiquidAI/LFM2.5-2.6B
Browse files- .gitattributes +1 -0
- analysis/cross_model_persistent_scan_50k_qwen35_2b_data/LiquidAI__LFM2.5-2.6B/COMPLETE.json +461 -0
- analysis/cross_model_persistent_scan_50k_qwen35_2b_data/LiquidAI__LFM2.5-2.6B/TOP.txt +107 -0
- analysis/cross_model_persistent_scan_50k_qwen35_2b_data/LiquidAI__LFM2.5-2.6B/layer_features.csv +3 -0
- analysis/cross_model_persistent_scan_50k_qwen35_2b_data/LiquidAI__LFM2.5-2.6B/persistent_channels.csv +0 -0
- analysis/cross_model_persistent_scan_50k_qwen35_2b_data/LiquidAI__LFM2.5-2.6B/runtime.json +45 -0
.gitattributes
CHANGED
|
@@ -60,3 +60,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 60 |
*.webm filter=lfs diff=lfs merge=lfs -text
|
| 61 |
analysis/cross_model_persistent_scan_50k_qwen35_2b_data/Qwen__Qwen3.5-4B/layer_features.csv filter=lfs diff=lfs merge=lfs -text
|
| 62 |
analysis/cross_model_persistent_scan_50k_qwen35_2b_data/Qwen__Qwen3.5-9B/layer_features.csv filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 60 |
*.webm filter=lfs diff=lfs merge=lfs -text
|
| 61 |
analysis/cross_model_persistent_scan_50k_qwen35_2b_data/Qwen__Qwen3.5-4B/layer_features.csv filter=lfs diff=lfs merge=lfs -text
|
| 62 |
analysis/cross_model_persistent_scan_50k_qwen35_2b_data/Qwen__Qwen3.5-9B/layer_features.csv filter=lfs diff=lfs merge=lfs -text
|
| 63 |
+
analysis/cross_model_persistent_scan_50k_qwen35_2b_data/LiquidAI__LFM2.5-2.6B/layer_features.csv filter=lfs diff=lfs merge=lfs -text
|
analysis/cross_model_persistent_scan_50k_qwen35_2b_data/LiquidAI__LFM2.5-2.6B/COMPLETE.json
ADDED
|
@@ -0,0 +1,461 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 3 |
+
"complete": true,
|
| 4 |
+
"prompt_pipeline": "original_qwen35_2b_v1",
|
| 5 |
+
"sequences": 50000,
|
| 6 |
+
"n_layers": 30,
|
| 7 |
+
"hidden_size": 2048,
|
| 8 |
+
"top_channels": [
|
| 9 |
+
{
|
| 10 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 11 |
+
"feature_index": 472,
|
| 12 |
+
"persistent_channel_score": 0.957948093710141,
|
| 13 |
+
"layer_count": 30,
|
| 14 |
+
"layer_coverage": 1.0,
|
| 15 |
+
"near_universal_layer_fraction": 1.0,
|
| 16 |
+
"mean_universal_score": 0.962552484388261,
|
| 17 |
+
"min_universal_score": 0.9467349727346357,
|
| 18 |
+
"min_worst_group_sign_consistency": 0.9985486211901307,
|
| 19 |
+
"min_worst_group_strong_coverage": 0.9985486211901307,
|
| 20 |
+
"mean_topk_coverage": 0.999996,
|
| 21 |
+
"median_relative_strength": 159.14144180255914,
|
| 22 |
+
"median_magnitude_cv": 0.23360832535227566,
|
| 23 |
+
"cross_layer_sign_stability": 1.0,
|
| 24 |
+
"mean_activation_across_layers": 0.5011469936125942,
|
| 25 |
+
"max_abs_mean_activation": 1.648145157648325
|
| 26 |
+
},
|
| 27 |
+
{
|
| 28 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 29 |
+
"feature_index": 870,
|
| 30 |
+
"persistent_channel_score": 0.8389420901995455,
|
| 31 |
+
"layer_count": 30,
|
| 32 |
+
"layer_coverage": 1.0,
|
| 33 |
+
"near_universal_layer_fraction": 0.9666666666666667,
|
| 34 |
+
"mean_universal_score": 0.9491006091178861,
|
| 35 |
+
"min_universal_score": 0.6673562323396536,
|
| 36 |
+
"min_worst_group_sign_consistency": 0.5145228215767634,
|
| 37 |
+
"min_worst_group_strong_coverage": 0.6647727272727273,
|
| 38 |
+
"mean_topk_coverage": 0.9905486666666666,
|
| 39 |
+
"median_relative_strength": 103.22831618164304,
|
| 40 |
+
"median_magnitude_cv": 0.29588758721709885,
|
| 41 |
+
"cross_layer_sign_stability": 1.0,
|
| 42 |
+
"mean_activation_across_layers": 0.4344357726622234,
|
| 43 |
+
"max_abs_mean_activation": 1.6387907219779492
|
| 44 |
+
},
|
| 45 |
+
{
|
| 46 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 47 |
+
"feature_index": 550,
|
| 48 |
+
"persistent_channel_score": 0.8220368224763399,
|
| 49 |
+
"layer_count": 30,
|
| 50 |
+
"layer_coverage": 1.0,
|
| 51 |
+
"near_universal_layer_fraction": 0.9333333333333333,
|
| 52 |
+
"mean_universal_score": 0.9414343443538169,
|
| 53 |
+
"min_universal_score": 0.6636159021687957,
|
| 54 |
+
"min_worst_group_sign_consistency": 0.9901129943502824,
|
| 55 |
+
"min_worst_group_strong_coverage": 0.12929848693259974,
|
| 56 |
+
"mean_topk_coverage": 0.958728,
|
| 57 |
+
"median_relative_strength": 59.97476990657656,
|
| 58 |
+
"median_magnitude_cv": 0.29860113945595035,
|
| 59 |
+
"cross_layer_sign_stability": 1.0,
|
| 60 |
+
"mean_activation_across_layers": 0.11735861682389619,
|
| 61 |
+
"max_abs_mean_activation": 0.23627018360726534
|
| 62 |
+
},
|
| 63 |
+
{
|
| 64 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 65 |
+
"feature_index": 2,
|
| 66 |
+
"persistent_channel_score": 0.7455635304566353,
|
| 67 |
+
"layer_count": 30,
|
| 68 |
+
"layer_coverage": 1.0,
|
| 69 |
+
"near_universal_layer_fraction": 0.9,
|
| 70 |
+
"mean_universal_score": 0.9201695540552003,
|
| 71 |
+
"min_universal_score": 0.21864701996537292,
|
| 72 |
+
"min_worst_group_sign_consistency": 0.5151515151515151,
|
| 73 |
+
"min_worst_group_strong_coverage": 0.0,
|
| 74 |
+
"mean_topk_coverage": 0.9062766666666666,
|
| 75 |
+
"median_relative_strength": 51.209585089967845,
|
| 76 |
+
"median_magnitude_cv": 0.10256228383986929,
|
| 77 |
+
"cross_layer_sign_stability": 0.9333333333333333,
|
| 78 |
+
"mean_activation_across_layers": 0.1282008465030627,
|
| 79 |
+
"max_abs_mean_activation": 0.38787150651603935
|
| 80 |
+
},
|
| 81 |
+
{
|
| 82 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 83 |
+
"feature_index": 1536,
|
| 84 |
+
"persistent_channel_score": 0.6929697356180959,
|
| 85 |
+
"layer_count": 30,
|
| 86 |
+
"layer_coverage": 1.0,
|
| 87 |
+
"near_universal_layer_fraction": 0.8,
|
| 88 |
+
"mean_universal_score": 0.8492595729038218,
|
| 89 |
+
"min_universal_score": 0.25919717977569623,
|
| 90 |
+
"min_worst_group_sign_consistency": 0.502086230876217,
|
| 91 |
+
"min_worst_group_strong_coverage": 0.0,
|
| 92 |
+
"mean_topk_coverage": 0.8262006666666666,
|
| 93 |
+
"median_relative_strength": 27.85810036620381,
|
| 94 |
+
"median_magnitude_cv": 0.26426221749584067,
|
| 95 |
+
"cross_layer_sign_stability": 0.9333333333333333,
|
| 96 |
+
"mean_activation_across_layers": -0.057470548183999694,
|
| 97 |
+
"max_abs_mean_activation": 0.14369701060033171
|
| 98 |
+
},
|
| 99 |
+
{
|
| 100 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 101 |
+
"feature_index": 229,
|
| 102 |
+
"persistent_channel_score": 0.6693110728158953,
|
| 103 |
+
"layer_count": 30,
|
| 104 |
+
"layer_coverage": 1.0,
|
| 105 |
+
"near_universal_layer_fraction": 0.6666666666666666,
|
| 106 |
+
"mean_universal_score": 0.8284433718830767,
|
| 107 |
+
"min_universal_score": 0.3868379511213528,
|
| 108 |
+
"min_worst_group_sign_consistency": 0.5697841726618704,
|
| 109 |
+
"min_worst_group_strong_coverage": 0.016129032258064516,
|
| 110 |
+
"mean_topk_coverage": 0.7442779999999999,
|
| 111 |
+
"median_relative_strength": 20.775409784229467,
|
| 112 |
+
"median_magnitude_cv": 0.3294126718220717,
|
| 113 |
+
"cross_layer_sign_stability": 0.9333333333333333,
|
| 114 |
+
"mean_activation_across_layers": -0.05530296689207797,
|
| 115 |
+
"max_abs_mean_activation": 0.1807509315473214
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 119 |
+
"feature_index": 1867,
|
| 120 |
+
"persistent_channel_score": 0.595245359553392,
|
| 121 |
+
"layer_count": 30,
|
| 122 |
+
"layer_coverage": 1.0,
|
| 123 |
+
"near_universal_layer_fraction": 0.36666666666666664,
|
| 124 |
+
"mean_universal_score": 0.7440420920320002,
|
| 125 |
+
"min_universal_score": 0.25637014579185124,
|
| 126 |
+
"min_worst_group_sign_consistency": 0.5016611295681064,
|
| 127 |
+
"min_worst_group_strong_coverage": 0.02824858757062147,
|
| 128 |
+
"mean_topk_coverage": 0.6382093333333334,
|
| 129 |
+
"median_relative_strength": 19.064491583078023,
|
| 130 |
+
"median_magnitude_cv": 0.3691714347728641,
|
| 131 |
+
"cross_layer_sign_stability": 0.9333333333333333,
|
| 132 |
+
"mean_activation_across_layers": 0.06999153299137247,
|
| 133 |
+
"max_abs_mean_activation": 0.21658486943774402
|
| 134 |
+
},
|
| 135 |
+
{
|
| 136 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 137 |
+
"feature_index": 34,
|
| 138 |
+
"persistent_channel_score": 0.5648606146181676,
|
| 139 |
+
"layer_count": 30,
|
| 140 |
+
"layer_coverage": 1.0,
|
| 141 |
+
"near_universal_layer_fraction": 0.5,
|
| 142 |
+
"mean_universal_score": 0.7038127742404588,
|
| 143 |
+
"min_universal_score": 0.2546390279722649,
|
| 144 |
+
"min_worst_group_sign_consistency": 0.5,
|
| 145 |
+
"min_worst_group_strong_coverage": 0.002070393374741201,
|
| 146 |
+
"mean_topk_coverage": 0.6097793333333336,
|
| 147 |
+
"median_relative_strength": 18.050883848605473,
|
| 148 |
+
"median_magnitude_cv": 0.3190401874204889,
|
| 149 |
+
"cross_layer_sign_stability": 0.5333333333333333,
|
| 150 |
+
"mean_activation_across_layers": 0.05221798357165668,
|
| 151 |
+
"max_abs_mean_activation": 0.14889890330638808
|
| 152 |
+
},
|
| 153 |
+
{
|
| 154 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 155 |
+
"feature_index": 757,
|
| 156 |
+
"persistent_channel_score": 0.5532856143003289,
|
| 157 |
+
"layer_count": 30,
|
| 158 |
+
"layer_coverage": 1.0,
|
| 159 |
+
"near_universal_layer_fraction": 0.26666666666666666,
|
| 160 |
+
"mean_universal_score": 0.6703169027710926,
|
| 161 |
+
"min_universal_score": 0.2689775185428889,
|
| 162 |
+
"min_worst_group_sign_consistency": 0.5006954102920723,
|
| 163 |
+
"min_worst_group_strong_coverage": 0.01440329218106996,
|
| 164 |
+
"mean_topk_coverage": 0.6274153333333332,
|
| 165 |
+
"median_relative_strength": 12.79151964481638,
|
| 166 |
+
"median_magnitude_cv": 0.4756381129955801,
|
| 167 |
+
"cross_layer_sign_stability": 0.8666666666666667,
|
| 168 |
+
"mean_activation_across_layers": 0.017863152024382756,
|
| 169 |
+
"max_abs_mean_activation": 0.045089512485006006
|
| 170 |
+
},
|
| 171 |
+
{
|
| 172 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 173 |
+
"feature_index": 553,
|
| 174 |
+
"persistent_channel_score": 0.551000873345633,
|
| 175 |
+
"layer_count": 30,
|
| 176 |
+
"layer_coverage": 1.0,
|
| 177 |
+
"near_universal_layer_fraction": 0.16666666666666666,
|
| 178 |
+
"mean_universal_score": 0.6979132535770329,
|
| 179 |
+
"min_universal_score": 0.3901903391618597,
|
| 180 |
+
"min_worst_group_sign_consistency": 0.5020746887966805,
|
| 181 |
+
"min_worst_group_strong_coverage": 0.025196850393700787,
|
| 182 |
+
"mean_topk_coverage": 0.6290526666666666,
|
| 183 |
+
"median_relative_strength": 12.292737884223683,
|
| 184 |
+
"median_magnitude_cv": 0.46913092357869335,
|
| 185 |
+
"cross_layer_sign_stability": 0.9333333333333333,
|
| 186 |
+
"mean_activation_across_layers": 0.04176563688618901,
|
| 187 |
+
"max_abs_mean_activation": 0.16970406812452057
|
| 188 |
+
},
|
| 189 |
+
{
|
| 190 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 191 |
+
"feature_index": 1134,
|
| 192 |
+
"persistent_channel_score": 0.5362216907464692,
|
| 193 |
+
"layer_count": 30,
|
| 194 |
+
"layer_coverage": 1.0,
|
| 195 |
+
"near_universal_layer_fraction": 0.26666666666666666,
|
| 196 |
+
"mean_universal_score": 0.6238917149661649,
|
| 197 |
+
"min_universal_score": 0.2137728007755957,
|
| 198 |
+
"min_worst_group_sign_consistency": 0.5007215007215007,
|
| 199 |
+
"min_worst_group_strong_coverage": 0.0,
|
| 200 |
+
"mean_topk_coverage": 0.4760353333333333,
|
| 201 |
+
"median_relative_strength": 8.154004571389002,
|
| 202 |
+
"median_magnitude_cv": 0.4257050280968049,
|
| 203 |
+
"cross_layer_sign_stability": 1.0,
|
| 204 |
+
"mean_activation_across_layers": -0.022181685682188788,
|
| 205 |
+
"max_abs_mean_activation": 0.2372124403475225
|
| 206 |
+
},
|
| 207 |
+
{
|
| 208 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 209 |
+
"feature_index": 2000,
|
| 210 |
+
"persistent_channel_score": 0.5355327129313976,
|
| 211 |
+
"layer_count": 30,
|
| 212 |
+
"layer_coverage": 1.0,
|
| 213 |
+
"near_universal_layer_fraction": 0.3333333333333333,
|
| 214 |
+
"mean_universal_score": 0.6881931444146175,
|
| 215 |
+
"min_universal_score": 0.20600027701949292,
|
| 216 |
+
"min_worst_group_sign_consistency": 0.5020661157024794,
|
| 217 |
+
"min_worst_group_strong_coverage": 0.0,
|
| 218 |
+
"mean_topk_coverage": 0.5639426666666665,
|
| 219 |
+
"median_relative_strength": 18.29211240804653,
|
| 220 |
+
"median_magnitude_cv": 0.4274033360062088,
|
| 221 |
+
"cross_layer_sign_stability": 0.6,
|
| 222 |
+
"mean_activation_across_layers": -0.027046705579168006,
|
| 223 |
+
"max_abs_mean_activation": 0.0811354188382905
|
| 224 |
+
},
|
| 225 |
+
{
|
| 226 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 227 |
+
"feature_index": 1363,
|
| 228 |
+
"persistent_channel_score": 0.5267673512078089,
|
| 229 |
+
"layer_count": 30,
|
| 230 |
+
"layer_coverage": 1.0,
|
| 231 |
+
"near_universal_layer_fraction": 0.3,
|
| 232 |
+
"mean_universal_score": 0.6711602167925068,
|
| 233 |
+
"min_universal_score": 0.3457159547491374,
|
| 234 |
+
"min_worst_group_sign_consistency": 0.5,
|
| 235 |
+
"min_worst_group_strong_coverage": 0.0014124293785310734,
|
| 236 |
+
"mean_topk_coverage": 0.5393526666666667,
|
| 237 |
+
"median_relative_strength": 5.938149660248597,
|
| 238 |
+
"median_magnitude_cv": 0.45381399166293246,
|
| 239 |
+
"cross_layer_sign_stability": 0.8,
|
| 240 |
+
"mean_activation_across_layers": -0.018118700955831284,
|
| 241 |
+
"max_abs_mean_activation": 0.12983077154167608
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 245 |
+
"feature_index": 1299,
|
| 246 |
+
"persistent_channel_score": 0.5197244483804294,
|
| 247 |
+
"layer_count": 30,
|
| 248 |
+
"layer_coverage": 1.0,
|
| 249 |
+
"near_universal_layer_fraction": 0.23333333333333334,
|
| 250 |
+
"mean_universal_score": 0.651385946008561,
|
| 251 |
+
"min_universal_score": 0.2629052324437925,
|
| 252 |
+
"min_worst_group_sign_consistency": 0.5010351966873706,
|
| 253 |
+
"min_worst_group_strong_coverage": 0.053613053613053616,
|
| 254 |
+
"mean_topk_coverage": 0.3536213333333333,
|
| 255 |
+
"median_relative_strength": 7.986079949688154,
|
| 256 |
+
"median_magnitude_cv": 0.36000645866866365,
|
| 257 |
+
"cross_layer_sign_stability": 0.8666666666666667,
|
| 258 |
+
"mean_activation_across_layers": 0.022573747516157285,
|
| 259 |
+
"max_abs_mean_activation": 0.07354524175294361
|
| 260 |
+
},
|
| 261 |
+
{
|
| 262 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 263 |
+
"feature_index": 883,
|
| 264 |
+
"persistent_channel_score": 0.4993675154058116,
|
| 265 |
+
"layer_count": 30,
|
| 266 |
+
"layer_coverage": 1.0,
|
| 267 |
+
"near_universal_layer_fraction": 0.2,
|
| 268 |
+
"mean_universal_score": 0.5798257280416617,
|
| 269 |
+
"min_universal_score": 0.22746117092682946,
|
| 270 |
+
"min_worst_group_sign_consistency": 0.5,
|
| 271 |
+
"min_worst_group_strong_coverage": 0.02177068214804064,
|
| 272 |
+
"mean_topk_coverage": 0.37439466666666665,
|
| 273 |
+
"median_relative_strength": 7.129320108331576,
|
| 274 |
+
"median_magnitude_cv": 0.3841132633451606,
|
| 275 |
+
"cross_layer_sign_stability": 0.8666666666666667,
|
| 276 |
+
"mean_activation_across_layers": 0.027175514883015513,
|
| 277 |
+
"max_abs_mean_activation": 0.22188478653478436
|
| 278 |
+
},
|
| 279 |
+
{
|
| 280 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 281 |
+
"feature_index": 1492,
|
| 282 |
+
"persistent_channel_score": 0.4948619854050106,
|
| 283 |
+
"layer_count": 30,
|
| 284 |
+
"layer_coverage": 1.0,
|
| 285 |
+
"near_universal_layer_fraction": 0.16666666666666666,
|
| 286 |
+
"mean_universal_score": 0.6787363038049938,
|
| 287 |
+
"min_universal_score": 0.3252619887323199,
|
| 288 |
+
"min_worst_group_sign_consistency": 0.500763358778626,
|
| 289 |
+
"min_worst_group_strong_coverage": 0.0,
|
| 290 |
+
"mean_topk_coverage": 0.52123,
|
| 291 |
+
"median_relative_strength": 12.113077914208471,
|
| 292 |
+
"median_magnitude_cv": 0.441620834776408,
|
| 293 |
+
"cross_layer_sign_stability": 0.5333333333333333,
|
| 294 |
+
"mean_activation_across_layers": -0.03605583601432731,
|
| 295 |
+
"max_abs_mean_activation": 0.11534043567877451
|
| 296 |
+
},
|
| 297 |
+
{
|
| 298 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 299 |
+
"feature_index": 575,
|
| 300 |
+
"persistent_channel_score": 0.49393444171193807,
|
| 301 |
+
"layer_count": 30,
|
| 302 |
+
"layer_coverage": 1.0,
|
| 303 |
+
"near_universal_layer_fraction": 0.16666666666666666,
|
| 304 |
+
"mean_universal_score": 0.6975649632343706,
|
| 305 |
+
"min_universal_score": 0.34113643924193743,
|
| 306 |
+
"min_worst_group_sign_consistency": 0.5008695652173913,
|
| 307 |
+
"min_worst_group_strong_coverage": 0.0,
|
| 308 |
+
"mean_topk_coverage": 0.6400560000000001,
|
| 309 |
+
"median_relative_strength": 16.473679844679314,
|
| 310 |
+
"median_magnitude_cv": 0.43597965997410404,
|
| 311 |
+
"cross_layer_sign_stability": 0.3333333333333333,
|
| 312 |
+
"mean_activation_across_layers": 0.05078768931961289,
|
| 313 |
+
"max_abs_mean_activation": 0.23466487461518204
|
| 314 |
+
},
|
| 315 |
+
{
|
| 316 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 317 |
+
"feature_index": 2029,
|
| 318 |
+
"persistent_channel_score": 0.4871297704013662,
|
| 319 |
+
"layer_count": 30,
|
| 320 |
+
"layer_coverage": 1.0,
|
| 321 |
+
"near_universal_layer_fraction": 0.0,
|
| 322 |
+
"mean_universal_score": 0.5985669510659835,
|
| 323 |
+
"min_universal_score": 0.40013937135011496,
|
| 324 |
+
"min_worst_group_sign_consistency": 0.5,
|
| 325 |
+
"min_worst_group_strong_coverage": 0.22434017595307917,
|
| 326 |
+
"mean_topk_coverage": 0.5098299999999999,
|
| 327 |
+
"median_relative_strength": 10.979833941578327,
|
| 328 |
+
"median_magnitude_cv": 0.6506336200190584,
|
| 329 |
+
"cross_layer_sign_stability": 0.6,
|
| 330 |
+
"mean_activation_across_layers": -0.022721483626995772,
|
| 331 |
+
"max_abs_mean_activation": 0.11758708076673965
|
| 332 |
+
},
|
| 333 |
+
{
|
| 334 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 335 |
+
"feature_index": 1893,
|
| 336 |
+
"persistent_channel_score": 0.48047599109464106,
|
| 337 |
+
"layer_count": 30,
|
| 338 |
+
"layer_coverage": 1.0,
|
| 339 |
+
"near_universal_layer_fraction": 0.0,
|
| 340 |
+
"mean_universal_score": 0.6256761734010432,
|
| 341 |
+
"min_universal_score": 0.2149669119158996,
|
| 342 |
+
"min_worst_group_sign_consistency": 0.5,
|
| 343 |
+
"min_worst_group_strong_coverage": 0.0,
|
| 344 |
+
"mean_topk_coverage": 0.332254,
|
| 345 |
+
"median_relative_strength": 9.341558977075813,
|
| 346 |
+
"median_magnitude_cv": 0.4294677589842927,
|
| 347 |
+
"cross_layer_sign_stability": 0.9333333333333333,
|
| 348 |
+
"mean_activation_across_layers": 0.029276729971457065,
|
| 349 |
+
"max_abs_mean_activation": 0.09126209545559226
|
| 350 |
+
},
|
| 351 |
+
{
|
| 352 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 353 |
+
"feature_index": 104,
|
| 354 |
+
"persistent_channel_score": 0.4770195078256478,
|
| 355 |
+
"layer_count": 30,
|
| 356 |
+
"layer_coverage": 1.0,
|
| 357 |
+
"near_universal_layer_fraction": 0.06666666666666667,
|
| 358 |
+
"mean_universal_score": 0.6153137530624521,
|
| 359 |
+
"min_universal_score": 0.35958087348887835,
|
| 360 |
+
"min_worst_group_sign_consistency": 0.5605381165919282,
|
| 361 |
+
"min_worst_group_strong_coverage": 0.004155124653739612,
|
| 362 |
+
"mean_topk_coverage": 0.110608,
|
| 363 |
+
"median_relative_strength": 5.723553501933067,
|
| 364 |
+
"median_magnitude_cv": 0.33306253949587883,
|
| 365 |
+
"cross_layer_sign_stability": 1.0,
|
| 366 |
+
"mean_activation_across_layers": 0.018294366314614695,
|
| 367 |
+
"max_abs_mean_activation": 0.05512318082857917
|
| 368 |
+
},
|
| 369 |
+
{
|
| 370 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 371 |
+
"feature_index": 279,
|
| 372 |
+
"persistent_channel_score": 0.47642325299322763,
|
| 373 |
+
"layer_count": 30,
|
| 374 |
+
"layer_coverage": 1.0,
|
| 375 |
+
"near_universal_layer_fraction": 0.03333333333333333,
|
| 376 |
+
"mean_universal_score": 0.5660022605573071,
|
| 377 |
+
"min_universal_score": 0.22286766329038354,
|
| 378 |
+
"min_worst_group_sign_consistency": 0.5,
|
| 379 |
+
"min_worst_group_strong_coverage": 0.028901734104046242,
|
| 380 |
+
"mean_topk_coverage": 0.4673360000000001,
|
| 381 |
+
"median_relative_strength": 7.196144035997688,
|
| 382 |
+
"median_magnitude_cv": 0.6296366617311197,
|
| 383 |
+
"cross_layer_sign_stability": 0.8666666666666667,
|
| 384 |
+
"mean_activation_across_layers": -0.015216723608125418,
|
| 385 |
+
"max_abs_mean_activation": 0.03437756172806346
|
| 386 |
+
},
|
| 387 |
+
{
|
| 388 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 389 |
+
"feature_index": 1885,
|
| 390 |
+
"persistent_channel_score": 0.4746833803074868,
|
| 391 |
+
"layer_count": 30,
|
| 392 |
+
"layer_coverage": 1.0,
|
| 393 |
+
"near_universal_layer_fraction": 0.0,
|
| 394 |
+
"mean_universal_score": 0.6200028152716234,
|
| 395 |
+
"min_universal_score": 0.29595739277623434,
|
| 396 |
+
"min_worst_group_sign_consistency": 0.5013477088948788,
|
| 397 |
+
"min_worst_group_strong_coverage": 0.0013477088948787063,
|
| 398 |
+
"mean_topk_coverage": 0.3755146666666667,
|
| 399 |
+
"median_relative_strength": 6.858417755516772,
|
| 400 |
+
"median_magnitude_cv": 0.3692213878584144,
|
| 401 |
+
"cross_layer_sign_stability": 0.8666666666666667,
|
| 402 |
+
"mean_activation_across_layers": 0.03248058242455461,
|
| 403 |
+
"max_abs_mean_activation": 0.11847037018441695
|
| 404 |
+
},
|
| 405 |
+
{
|
| 406 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 407 |
+
"feature_index": 1676,
|
| 408 |
+
"persistent_channel_score": 0.4702794152382654,
|
| 409 |
+
"layer_count": 30,
|
| 410 |
+
"layer_coverage": 1.0,
|
| 411 |
+
"near_universal_layer_fraction": 0.0,
|
| 412 |
+
"mean_universal_score": 0.5923863684066036,
|
| 413 |
+
"min_universal_score": 0.2415780766316867,
|
| 414 |
+
"min_worst_group_sign_consistency": 0.5034387895460798,
|
| 415 |
+
"min_worst_group_strong_coverage": 0.005865102639296188,
|
| 416 |
+
"mean_topk_coverage": 0.32256199999999996,
|
| 417 |
+
"median_relative_strength": 7.442045012625273,
|
| 418 |
+
"median_magnitude_cv": 0.4638773348691331,
|
| 419 |
+
"cross_layer_sign_stability": 0.9333333333333333,
|
| 420 |
+
"mean_activation_across_layers": -0.016979013225465737,
|
| 421 |
+
"max_abs_mean_activation": 0.061995339494608406
|
| 422 |
+
},
|
| 423 |
+
{
|
| 424 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 425 |
+
"feature_index": 45,
|
| 426 |
+
"persistent_channel_score": 0.4679948271546285,
|
| 427 |
+
"layer_count": 30,
|
| 428 |
+
"layer_coverage": 1.0,
|
| 429 |
+
"near_universal_layer_fraction": 0.2,
|
| 430 |
+
"mean_universal_score": 0.5438906747878061,
|
| 431 |
+
"min_universal_score": 0.21137274678957907,
|
| 432 |
+
"min_worst_group_sign_consistency": 0.5,
|
| 433 |
+
"min_worst_group_strong_coverage": 0.0,
|
| 434 |
+
"mean_topk_coverage": 0.34053666666666665,
|
| 435 |
+
"median_relative_strength": 4.392493344169434,
|
| 436 |
+
"median_magnitude_cv": 0.4935548991912325,
|
| 437 |
+
"cross_layer_sign_stability": 0.8,
|
| 438 |
+
"mean_activation_across_layers": -0.010004084160006857,
|
| 439 |
+
"max_abs_mean_activation": 0.029948766747364883
|
| 440 |
+
},
|
| 441 |
+
{
|
| 442 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 443 |
+
"feature_index": 1832,
|
| 444 |
+
"persistent_channel_score": 0.4648256241359502,
|
| 445 |
+
"layer_count": 30,
|
| 446 |
+
"layer_coverage": 1.0,
|
| 447 |
+
"near_universal_layer_fraction": 0.0,
|
| 448 |
+
"mean_universal_score": 0.5509931342703392,
|
| 449 |
+
"min_universal_score": 0.20232078109434276,
|
| 450 |
+
"min_worst_group_sign_consistency": 0.5,
|
| 451 |
+
"min_worst_group_strong_coverage": 0.0,
|
| 452 |
+
"mean_topk_coverage": 0.2749253333333333,
|
| 453 |
+
"median_relative_strength": 7.469881166148392,
|
| 454 |
+
"median_magnitude_cv": 0.4754235499441395,
|
| 455 |
+
"cross_layer_sign_stability": 1.0,
|
| 456 |
+
"mean_activation_across_layers": -0.019526935915422188,
|
| 457 |
+
"max_abs_mean_activation": 0.06038556009741487
|
| 458 |
+
}
|
| 459 |
+
],
|
| 460 |
+
"finished_at": "2026-10-20T11:58:40"
|
| 461 |
+
}
|
analysis/cross_model_persistent_scan_50k_qwen35_2b_data/LiquidAI__LFM2.5-2.6B/TOP.txt
ADDED
|
@@ -0,0 +1,107 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
MODEL: LiquidAI/LFM2.5-2.6B
|
| 2 |
+
SEQUENCES: 50,000
|
| 3 |
+
LAYERS: 30
|
| 4 |
+
HIDDEN SIZE: 2048
|
| 5 |
+
|
| 6 |
+
TOP PERSISTENT CHANNELS
|
| 7 |
+
========================================================================================================================
|
| 8 |
+
feature= 472 score=0.957948 nearLayers=1.000 meanU=0.9626 minWGsign=0.9985 minWGstrong=0.9985 topK=1.0000 rel=159.14x CV=0.2336 signStable=1.000
|
| 9 |
+
feature= 870 score=0.838942 nearLayers=0.967 meanU=0.9491 minWGsign=0.5145 minWGstrong=0.6648 topK=0.9905 rel=103.23x CV=0.2959 signStable=1.000
|
| 10 |
+
feature= 550 score=0.822037 nearLayers=0.933 meanU=0.9414 minWGsign=0.9901 minWGstrong=0.1293 topK=0.9587 rel=59.97x CV=0.2986 signStable=1.000
|
| 11 |
+
feature= 2 score=0.745564 nearLayers=0.900 meanU=0.9202 minWGsign=0.5152 minWGstrong=0.0000 topK=0.9063 rel=51.21x CV=0.1026 signStable=0.933
|
| 12 |
+
feature= 1536 score=0.692970 nearLayers=0.800 meanU=0.8493 minWGsign=0.5021 minWGstrong=0.0000 topK=0.8262 rel=27.86x CV=0.2643 signStable=0.933
|
| 13 |
+
feature= 229 score=0.669311 nearLayers=0.667 meanU=0.8284 minWGsign=0.5698 minWGstrong=0.0161 topK=0.7443 rel=20.78x CV=0.3294 signStable=0.933
|
| 14 |
+
feature= 1867 score=0.595245 nearLayers=0.367 meanU=0.7440 minWGsign=0.5017 minWGstrong=0.0282 topK=0.6382 rel=19.06x CV=0.3692 signStable=0.933
|
| 15 |
+
feature= 34 score=0.564861 nearLayers=0.500 meanU=0.7038 minWGsign=0.5000 minWGstrong=0.0021 topK=0.6098 rel=18.05x CV=0.3190 signStable=0.533
|
| 16 |
+
feature= 757 score=0.553286 nearLayers=0.267 meanU=0.6703 minWGsign=0.5007 minWGstrong=0.0144 topK=0.6274 rel=12.79x CV=0.4756 signStable=0.867
|
| 17 |
+
feature= 553 score=0.551001 nearLayers=0.167 meanU=0.6979 minWGsign=0.5021 minWGstrong=0.0252 topK=0.6291 rel=12.29x CV=0.4691 signStable=0.933
|
| 18 |
+
feature= 1134 score=0.536222 nearLayers=0.267 meanU=0.6239 minWGsign=0.5007 minWGstrong=0.0000 topK=0.4760 rel=8.15x CV=0.4257 signStable=1.000
|
| 19 |
+
feature= 2000 score=0.535533 nearLayers=0.333 meanU=0.6882 minWGsign=0.5021 minWGstrong=0.0000 topK=0.5639 rel=18.29x CV=0.4274 signStable=0.600
|
| 20 |
+
feature= 1363 score=0.526767 nearLayers=0.300 meanU=0.6712 minWGsign=0.5000 minWGstrong=0.0014 topK=0.5394 rel=5.94x CV=0.4538 signStable=0.800
|
| 21 |
+
feature= 1299 score=0.519724 nearLayers=0.233 meanU=0.6514 minWGsign=0.5010 minWGstrong=0.0536 topK=0.3536 rel=7.99x CV=0.3600 signStable=0.867
|
| 22 |
+
feature= 883 score=0.499368 nearLayers=0.200 meanU=0.5798 minWGsign=0.5000 minWGstrong=0.0218 topK=0.3744 rel=7.13x CV=0.3841 signStable=0.867
|
| 23 |
+
feature= 1492 score=0.494862 nearLayers=0.167 meanU=0.6787 minWGsign=0.5008 minWGstrong=0.0000 topK=0.5212 rel=12.11x CV=0.4416 signStable=0.533
|
| 24 |
+
feature= 575 score=0.493934 nearLayers=0.167 meanU=0.6976 minWGsign=0.5009 minWGstrong=0.0000 topK=0.6401 rel=16.47x CV=0.4360 signStable=0.333
|
| 25 |
+
feature= 2029 score=0.487130 nearLayers=0.000 meanU=0.5986 minWGsign=0.5000 minWGstrong=0.2243 topK=0.5098 rel=10.98x CV=0.6506 signStable=0.600
|
| 26 |
+
feature= 1893 score=0.480476 nearLayers=0.000 meanU=0.6257 minWGsign=0.5000 minWGstrong=0.0000 topK=0.3323 rel=9.34x CV=0.4295 signStable=0.933
|
| 27 |
+
feature= 104 score=0.477020 nearLayers=0.067 meanU=0.6153 minWGsign=0.5605 minWGstrong=0.0042 topK=0.1106 rel=5.72x CV=0.3331 signStable=1.000
|
| 28 |
+
feature= 279 score=0.476423 nearLayers=0.033 meanU=0.5660 minWGsign=0.5000 minWGstrong=0.0289 topK=0.4673 rel=7.20x CV=0.6296 signStable=0.867
|
| 29 |
+
feature= 1885 score=0.474683 nearLayers=0.000 meanU=0.6200 minWGsign=0.5013 minWGstrong=0.0013 topK=0.3755 rel=6.86x CV=0.3692 signStable=0.867
|
| 30 |
+
feature= 1676 score=0.470279 nearLayers=0.000 meanU=0.5924 minWGsign=0.5034 minWGstrong=0.0059 topK=0.3226 rel=7.44x CV=0.4639 signStable=0.933
|
| 31 |
+
feature= 45 score=0.467995 nearLayers=0.200 meanU=0.5439 minWGsign=0.5000 minWGstrong=0.0000 topK=0.3405 rel=4.39x CV=0.4936 signStable=0.800
|
| 32 |
+
feature= 1832 score=0.464826 nearLayers=0.000 meanU=0.5510 minWGsign=0.5000 minWGstrong=0.0000 topK=0.2749 rel=7.47x CV=0.4754 signStable=1.000
|
| 33 |
+
feature= 1513 score=0.464341 nearLayers=0.000 meanU=0.5972 minWGsign=0.5022 minWGstrong=0.0014 topK=0.2601 rel=8.28x CV=0.3574 signStable=0.867
|
| 34 |
+
feature= 1766 score=0.459903 nearLayers=0.100 meanU=0.5587 minWGsign=0.5000 minWGstrong=0.0043 topK=0.1477 rel=5.51x CV=0.3730 signStable=0.933
|
| 35 |
+
feature= 989 score=0.458457 nearLayers=0.000 meanU=0.5032 minWGsign=0.5000 minWGstrong=0.0494 topK=0.3060 rel=4.91x CV=0.3602 signStable=0.933
|
| 36 |
+
feature= 591 score=0.454049 nearLayers=0.000 meanU=0.5570 minWGsign=0.5007 minWGstrong=0.0488 topK=0.5709 rel=5.01x CV=0.8461 signStable=0.667
|
| 37 |
+
feature= 213 score=0.452010 nearLayers=0.133 meanU=0.5385 minWGsign=0.5000 minWGstrong=0.0000 topK=0.2345 rel=4.90x CV=0.4219 signStable=0.800
|
| 38 |
+
feature= 1163 score=0.451741 nearLayers=0.100 meanU=0.5258 minWGsign=0.5000 minWGstrong=0.0000 topK=0.1615 rel=5.07x CV=0.3112 signStable=0.867
|
| 39 |
+
feature= 262 score=0.450846 nearLayers=0.000 meanU=0.5335 minWGsign=0.5007 minWGstrong=0.0450 topK=0.2281 rel=5.41x CV=0.4777 signStable=0.933
|
| 40 |
+
feature= 285 score=0.448060 nearLayers=0.033 meanU=0.6031 minWGsign=0.5000 minWGstrong=0.0000 topK=0.5033 rel=10.04x CV=0.4093 signStable=0.400
|
| 41 |
+
feature= 224 score=0.447155 nearLayers=0.000 meanU=0.5571 minWGsign=0.5022 minWGstrong=0.0186 topK=0.1490 rel=6.36x CV=0.4474 signStable=0.933
|
| 42 |
+
feature= 1595 score=0.446329 nearLayers=0.000 meanU=0.5397 minWGsign=0.5083 minWGstrong=0.0102 topK=0.1152 rel=4.65x CV=0.3571 signStable=1.000
|
| 43 |
+
feature= 1343 score=0.446033 nearLayers=0.000 meanU=0.5305 minWGsign=0.5008 minWGstrong=0.0723 topK=0.1303 rel=5.40x CV=0.4301 signStable=0.933
|
| 44 |
+
feature= 703 score=0.444028 nearLayers=0.000 meanU=0.5388 minWGsign=0.5028 minWGstrong=0.0135 topK=0.1969 rel=5.65x CV=0.5209 signStable=0.933
|
| 45 |
+
feature= 1696 score=0.442754 nearLayers=0.000 meanU=0.5349 minWGsign=0.5000 minWGstrong=0.0000 topK=0.2082 rel=5.45x CV=0.4924 signStable=0.933
|
| 46 |
+
feature= 809 score=0.437346 nearLayers=0.167 meanU=0.6490 minWGsign=0.5021 minWGstrong=0.0000 topK=0.4819 rel=8.26x CV=0.4979 signStable=0.133
|
| 47 |
+
feature= 1723 score=0.435835 nearLayers=0.000 meanU=0.4933 minWGsign=0.5000 minWGstrong=0.0216 topK=0.1060 rel=4.65x CV=0.4262 signStable=1.000
|
| 48 |
+
feature= 1755 score=0.434535 nearLayers=0.000 meanU=0.5237 minWGsign=0.5000 minWGstrong=0.0014 topK=0.0371 rel=4.81x CV=0.3596 signStable=1.000
|
| 49 |
+
feature= 635 score=0.434168 nearLayers=0.033 meanU=0.4747 minWGsign=0.5008 minWGstrong=0.0870 topK=0.1402 rel=3.03x CV=0.2459 signStable=0.800
|
| 50 |
+
feature= 205 score=0.433673 nearLayers=0.000 meanU=0.5434 minWGsign=0.5014 minWGstrong=0.0000 topK=0.0407 rel=5.05x CV=0.3294 signStable=0.933
|
| 51 |
+
feature= 21 score=0.433539 nearLayers=0.000 meanU=0.4844 minWGsign=0.5000 minWGstrong=0.0457 topK=0.2472 rel=5.00x CV=0.6404 signStable=0.867
|
| 52 |
+
feature= 947 score=0.431613 nearLayers=0.000 meanU=0.5398 minWGsign=0.5021 minWGstrong=0.0014 topK=0.1294 rel=6.40x CV=0.3582 signStable=0.800
|
| 53 |
+
feature= 479 score=0.431182 nearLayers=0.000 meanU=0.5114 minWGsign=0.5000 minWGstrong=0.0000 topK=0.1276 rel=4.65x CV=0.4238 signStable=0.933
|
| 54 |
+
feature= 526 score=0.430086 nearLayers=0.000 meanU=0.4901 minWGsign=0.5010 minWGstrong=0.0000 topK=0.0885 rel=3.80x CV=0.3720 signStable=1.000
|
| 55 |
+
feature= 354 score=0.429611 nearLayers=0.000 meanU=0.5213 minWGsign=0.5007 minWGstrong=0.0055 topK=0.1708 rel=4.29x CV=0.4238 signStable=0.867
|
| 56 |
+
feature= 1745 score=0.428216 nearLayers=0.133 meanU=0.5970 minWGsign=0.5000 minWGstrong=0.0000 topK=0.4107 rel=7.03x CV=0.4992 signStable=0.267
|
| 57 |
+
feature= 75 score=0.427347 nearLayers=0.000 meanU=0.4915 minWGsign=0.5000 minWGstrong=0.0000 topK=0.2930 rel=5.06x CV=0.4040 signStable=0.733
|
| 58 |
+
feature= 1328 score=0.426266 nearLayers=0.000 meanU=0.5074 minWGsign=0.5007 minWGstrong=0.0000 topK=0.0057 rel=3.80x CV=0.3365 signStable=1.000
|
| 59 |
+
feature= 689 score=0.426094 nearLayers=0.000 meanU=0.5045 minWGsign=0.5007 minWGstrong=0.0041 topK=0.1542 rel=4.02x CV=0.3856 signStable=0.867
|
| 60 |
+
feature= 298 score=0.425403 nearLayers=0.000 meanU=0.5524 minWGsign=0.5011 minWGstrong=0.0086 topK=0.3058 rel=4.46x CV=0.3554 signStable=0.600
|
| 61 |
+
feature= 581 score=0.424770 nearLayers=0.000 meanU=0.4647 minWGsign=0.5000 minWGstrong=0.0028 topK=0.0815 rel=4.15x CV=0.4298 signStable=1.000
|
| 62 |
+
feature= 644 score=0.422761 nearLayers=0.233 meanU=0.5767 minWGsign=0.5014 minWGstrong=0.0000 topK=0.3005 rel=6.72x CV=0.2374 signStable=0.067
|
| 63 |
+
feature= 1618 score=0.422331 nearLayers=0.000 meanU=0.4666 minWGsign=0.5007 minWGstrong=0.0273 topK=0.1057 rel=3.92x CV=0.4486 signStable=0.933
|
| 64 |
+
feature= 1459 score=0.419004 nearLayers=0.000 meanU=0.4522 minWGsign=0.5000 minWGstrong=0.0611 topK=0.0833 rel=4.08x CV=0.3904 signStable=0.867
|
| 65 |
+
feature= 232 score=0.417217 nearLayers=0.000 meanU=0.4490 minWGsign=0.5022 minWGstrong=0.0028 topK=0.0140 rel=3.48x CV=0.3489 signStable=1.000
|
| 66 |
+
feature= 79 score=0.416960 nearLayers=0.000 meanU=0.4600 minWGsign=0.5000 minWGstrong=0.0029 topK=0.0331 rel=3.30x CV=0.3963 signStable=1.000
|
| 67 |
+
feature= 907 score=0.415175 nearLayers=0.000 meanU=0.4537 minWGsign=0.5000 minWGstrong=0.0491 topK=0.1782 rel=3.76x CV=0.4826 signStable=0.800
|
| 68 |
+
feature= 294 score=0.414802 nearLayers=0.000 meanU=0.4514 minWGsign=0.5000 minWGstrong=0.0034 topK=0.0901 rel=3.22x CV=0.3892 signStable=0.933
|
| 69 |
+
feature= 966 score=0.414462 nearLayers=0.000 meanU=0.4463 minWGsign=0.5000 minWGstrong=0.0332 topK=0.1428 rel=4.03x CV=0.5464 signStable=0.867
|
| 70 |
+
feature= 339 score=0.414030 nearLayers=0.000 meanU=0.4846 minWGsign=0.5007 minWGstrong=0.0000 topK=0.0332 rel=4.84x CV=0.3840 signStable=0.867
|
| 71 |
+
feature= 1139 score=0.413612 nearLayers=0.033 meanU=0.5054 minWGsign=0.5000 minWGstrong=0.0589 topK=0.3586 rel=4.53x CV=0.5766 signStable=0.467
|
| 72 |
+
feature= 1654 score=0.413367 nearLayers=0.000 meanU=0.4745 minWGsign=0.5007 minWGstrong=0.0000 topK=0.0200 rel=4.53x CV=0.3280 signStable=0.867
|
| 73 |
+
feature= 1119 score=0.412082 nearLayers=0.000 meanU=0.4811 minWGsign=0.5000 minWGstrong=0.0863 topK=0.3098 rel=3.81x CV=0.7070 signStable=0.600
|
| 74 |
+
feature= 1545 score=0.411313 nearLayers=0.000 meanU=0.4103 minWGsign=0.5000 minWGstrong=0.0234 topK=0.0745 rel=3.20x CV=0.5263 signStable=1.000
|
| 75 |
+
feature= 1395 score=0.410910 nearLayers=0.000 meanU=0.3905 minWGsign=0.5000 minWGstrong=0.0000 topK=0.0160 rel=2.35x CV=0.2348 signStable=1.000
|
| 76 |
+
feature= 1991 score=0.410802 nearLayers=0.000 meanU=0.4435 minWGsign=0.5000 minWGstrong=0.0083 topK=0.0673 rel=2.95x CV=0.2808 signStable=0.867
|
| 77 |
+
feature= 314 score=0.409121 nearLayers=0.200 meanU=0.5395 minWGsign=0.5000 minWGstrong=0.0016 topK=0.3125 rel=2.83x CV=0.2738 signStable=0.200
|
| 78 |
+
feature= 482 score=0.409020 nearLayers=0.000 meanU=0.4364 minWGsign=0.5000 minWGstrong=0.0000 topK=0.0231 rel=3.80x CV=0.3757 signStable=0.933
|
| 79 |
+
feature= 828 score=0.408808 nearLayers=0.000 meanU=0.5325 minWGsign=0.5008 minWGstrong=0.0043 topK=0.2199 rel=6.07x CV=0.4249 signStable=0.533
|
| 80 |
+
feature= 855 score=0.408559 nearLayers=0.300 meanU=0.5690 minWGsign=0.5010 minWGstrong=0.0000 topK=0.3089 rel=3.61x CV=0.3038 signStable=0.000
|
| 81 |
+
feature= 887 score=0.408372 nearLayers=0.000 meanU=0.4725 minWGsign=0.5023 minWGstrong=0.0000 topK=0.0355 rel=3.81x CV=0.3880 signStable=0.867
|
| 82 |
+
feature= 494 score=0.408226 nearLayers=0.000 meanU=0.4860 minWGsign=0.5000 minWGstrong=0.0000 topK=0.0926 rel=5.33x CV=0.3893 signStable=0.733
|
| 83 |
+
feature= 178 score=0.407778 nearLayers=0.000 meanU=0.4666 minWGsign=0.5007 minWGstrong=0.0000 topK=0.0621 rel=3.00x CV=0.3556 signStable=0.867
|
| 84 |
+
feature= 721 score=0.407162 nearLayers=0.000 meanU=0.4759 minWGsign=0.5021 minWGstrong=0.0000 topK=0.0071 rel=3.33x CV=0.3280 signStable=0.867
|
| 85 |
+
feature= 188 score=0.407011 nearLayers=0.100 meanU=0.4188 minWGsign=0.5000 minWGstrong=0.0000 topK=0.1008 rel=2.07x CV=0.3459 signStable=0.800
|
| 86 |
+
feature= 1575 score=0.406656 nearLayers=0.000 meanU=0.4647 minWGsign=0.5014 minWGstrong=0.0000 topK=0.0560 rel=4.35x CV=0.3549 signStable=0.800
|
| 87 |
+
feature= 91 score=0.405929 nearLayers=0.000 meanU=0.4205 minWGsign=0.5000 minWGstrong=0.0249 topK=0.0538 rel=1.85x CV=0.2280 signStable=0.867
|
| 88 |
+
feature= 1398 score=0.405826 nearLayers=0.000 meanU=0.4040 minWGsign=0.5007 minWGstrong=0.0082 topK=0.0560 rel=2.39x CV=0.4216 signStable=1.000
|
| 89 |
+
feature= 1142 score=0.405188 nearLayers=0.000 meanU=0.4166 minWGsign=0.5000 minWGstrong=0.0015 topK=0.0205 rel=2.94x CV=0.4497 signStable=1.000
|
| 90 |
+
feature= 1489 score=0.404807 nearLayers=0.000 meanU=0.6002 minWGsign=0.5000 minWGstrong=0.0103 topK=0.4019 rel=8.14x CV=0.3815 signStable=0.133
|
| 91 |
+
feature= 1796 score=0.403770 nearLayers=0.000 meanU=0.4389 minWGsign=0.5000 minWGstrong=0.0072 topK=0.1068 rel=3.39x CV=0.5363 signStable=0.867
|
| 92 |
+
feature= 586 score=0.402546 nearLayers=0.000 meanU=0.4394 minWGsign=0.5000 minWGstrong=0.0028 topK=0.0221 rel=3.82x CV=0.3869 signStable=0.867
|
| 93 |
+
feature= 331 score=0.402278 nearLayers=0.000 meanU=0.4398 minWGsign=0.5007 minWGstrong=0.0000 topK=0.0138 rel=3.69x CV=0.3616 signStable=0.867
|
| 94 |
+
feature= 677 score=0.401736 nearLayers=0.000 meanU=0.4257 minWGsign=0.5007 minWGstrong=0.0000 topK=0.0166 rel=2.82x CV=0.3816 signStable=0.933
|
| 95 |
+
feature= 1295 score=0.401701 nearLayers=0.000 meanU=0.4185 minWGsign=0.5000 minWGstrong=0.0000 topK=0.0102 rel=2.82x CV=0.3510 signStable=0.933
|
| 96 |
+
feature= 2006 score=0.401432 nearLayers=0.000 meanU=0.4430 minWGsign=0.5022 minWGstrong=0.0000 topK=0.0455 rel=2.92x CV=0.3754 signStable=0.867
|
| 97 |
+
feature= 1483 score=0.400817 nearLayers=0.000 meanU=0.3620 minWGsign=0.5017 minWGstrong=0.0000 topK=0.0066 rel=2.17x CV=0.2094 signStable=0.933
|
| 98 |
+
feature= 1399 score=0.400738 nearLayers=0.000 meanU=0.3928 minWGsign=0.5009 minWGstrong=0.0000 topK=0.0064 rel=2.49x CV=0.3835 signStable=1.000
|
| 99 |
+
feature= 1453 score=0.400262 nearLayers=0.000 meanU=0.4479 minWGsign=0.5000 minWGstrong=0.0021 topK=0.0230 rel=3.05x CV=0.3813 signStable=0.867
|
| 100 |
+
feature= 142 score=0.398078 nearLayers=0.000 meanU=0.4020 minWGsign=0.5000 minWGstrong=0.0022 topK=0.0295 rel=3.09x CV=0.4539 signStable=0.933
|
| 101 |
+
feature= 1922 score=0.396739 nearLayers=0.000 meanU=0.3660 minWGsign=0.5007 minWGstrong=0.0000 topK=0.0010 rel=2.44x CV=0.3716 signStable=1.000
|
| 102 |
+
feature= 134 score=0.395787 nearLayers=0.000 meanU=0.3970 minWGsign=0.5007 minWGstrong=0.0000 topK=0.0011 rel=2.68x CV=0.3729 signStable=0.933
|
| 103 |
+
feature= 1525 score=0.394236 nearLayers=0.000 meanU=0.3877 minWGsign=0.5000 minWGstrong=0.0128 topK=0.0303 rel=2.38x CV=0.4347 signStable=0.933
|
| 104 |
+
feature= 165 score=0.394224 nearLayers=0.000 meanU=0.3472 minWGsign=0.5008 minWGstrong=0.0000 topK=0.0065 rel=1.64x CV=0.2139 signStable=0.933
|
| 105 |
+
feature= 1899 score=0.394071 nearLayers=0.000 meanU=0.4119 minWGsign=0.5022 minWGstrong=0.0000 topK=0.0074 rel=2.13x CV=0.3955 signStable=0.933
|
| 106 |
+
feature= 286 score=0.393006 nearLayers=0.000 meanU=0.3880 minWGsign=0.5000 minWGstrong=0.0000 topK=0.0061 rel=2.70x CV=0.4148 signStable=0.933
|
| 107 |
+
feature= 776 score=0.392953 nearLayers=0.000 meanU=0.4345 minWGsign=0.5000 minWGstrong=0.0000 topK=0.0335 rel=2.64x CV=0.3335 signStable=0.800
|
analysis/cross_model_persistent_scan_50k_qwen35_2b_data/LiquidAI__LFM2.5-2.6B/layer_features.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:42f55fa922bf2be5ccf4dd32aef5b7b40c8f97f8ff56370bdaf4e72b04c3f5a2
|
| 3 |
+
size 15574025
|
analysis/cross_model_persistent_scan_50k_qwen35_2b_data/LiquidAI__LFM2.5-2.6B/persistent_channels.csv
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
analysis/cross_model_persistent_scan_50k_qwen35_2b_data/LiquidAI__LFM2.5-2.6B/runtime.json
ADDED
|
@@ -0,0 +1,45 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"model": "LiquidAI/LFM2.5-2.6B",
|
| 3 |
+
"loader": "AutoModelForCausalLM",
|
| 4 |
+
"stack": "model.layers",
|
| 5 |
+
"n_layers": 30,
|
| 6 |
+
"hidden_size": 2048,
|
| 7 |
+
"target_sequences": 50000,
|
| 8 |
+
"batch_size": 16,
|
| 9 |
+
"max_input_tokens": 128,
|
| 10 |
+
"prompt_pipeline": "original_qwen35_2b_v1",
|
| 11 |
+
"sources": [
|
| 12 |
+
"ultrachat",
|
| 13 |
+
"fineweb_edu",
|
| 14 |
+
"openwebmath",
|
| 15 |
+
"cosmopedia_v2"
|
| 16 |
+
],
|
| 17 |
+
"formats": [
|
| 18 |
+
"raw",
|
| 19 |
+
"qa_short",
|
| 20 |
+
"user_assistant",
|
| 21 |
+
"hash_sections",
|
| 22 |
+
"xml_document",
|
| 23 |
+
"key_point",
|
| 24 |
+
"continue",
|
| 25 |
+
"next_sentence",
|
| 26 |
+
"context_answer",
|
| 27 |
+
"brackets",
|
| 28 |
+
"reader_reply",
|
| 29 |
+
"plain_instruction",
|
| 30 |
+
"title",
|
| 31 |
+
"summary",
|
| 32 |
+
"minimal",
|
| 33 |
+
"note",
|
| 34 |
+
"completion",
|
| 35 |
+
"quoted",
|
| 36 |
+
"dash",
|
| 37 |
+
"task_block"
|
| 38 |
+
],
|
| 39 |
+
"grouping": "source::format",
|
| 40 |
+
"reference_prompt_tokenizer": "Qwen/Qwen3.5-2B",
|
| 41 |
+
"seed": 3407,
|
| 42 |
+
"min_input_tokens": 48,
|
| 43 |
+
"top_fraction": 0.015625,
|
| 44 |
+
"strong_multiplier": 3.0
|
| 45 |
+
}
|