docs(README): Motif K400 = 87.4 (eval complete)

Fill Motif K400 attentive-probe top-1 (87.4); only KITTI remains in progress.

README.md

@@ -105,7 +105,7 @@ single-resolution (S) figure is available.
 
 | Model | Training<br>data | DAVIS S<br>J&F ↑ | DAVIS M<br>J&F ↑ | DAVIS L<br>J&F ↑ | ImageNet-1K<br>lin. probe ↑ | ADE20K<br>mIoU ↑ | K400 ↑ | KITTI<br>depth MSE ↓ |
 |---|---|---|---|---|---|---|---|---|
-| **Motif Vision Encoder** | 0.5B | **74.0** | **80.5** | **83.5** | 87.2 | 52.0 | *in progress* | *in progress* |
+| **Motif Vision Encoder** | 0.5B | **74.0** | **80.5** | **83.5** | 87.2 | 52.0 | 87.4 | *in progress* |
 | DINOv3 | 1.7B | 71.1 | 79.7 | 83.3 | 88.4 | **55.9** | 87.8 | **2.3** |
 | PEcore | 5.4B | 48.2 | 53.1 | 49.8 | **89.3** | 38.9 | **87.9** | 4.1 |
 | SigLIP2 | 10B | 56.1 | 62.3 | 62.9 | 89.1 | 45.4 | 86.9 | – |
@@ -127,8 +127,8 @@ single-resolution (S) figure is available.
   18.5M video clips), roughly **3.6× less data than DINOv3**, which is trained on LVD-1689M
   (1,689M images). Despite the smaller corpus — and with only ~4% of samples being video — the
   encoder stays competitive across both image and video benchmarks, and leads on DAVIS.
-- K400 action recognition and KITTI depth estimation are still being evaluated and will be added
-  as the runs complete. Numbers in this table will be updated as evaluations finish.
+- KITTI depth estimation is still being evaluated and will be added as the run completes.
+  Numbers in this table will be updated as evaluations finish.
 
 Protocol: DINOv3-style linear/attentive probes for image tasks; V-JEPA 2-style protocol for
 video. Baseline DAVIS / ADE20K / K400 / KITTI figures are taken from the DINOv3 technical