Add overlap-aware turn prediction objectives

README.md

@@ -954,6 +954,21 @@ without normalizing the target. The previous L2-normalized objective belongs
 to MiniROAD and is available only as the explicit
 `--loss miniroad-normalized` ablation.
 
+Two label-structure ablations are also available without changing the saved
+three-column target files:
+
+- `--loss independent-bce` keeps a `10 x 3` head, trains the three labels with
+  independent sigmoid/BCE, and evaluates the sigmoid marginals directly;
+- `--loss four-state-ce` changes the head to `10 x 4` and maps each target to
+  `silence`, `wearer_only`, `others_only`, or `overlap`. At evaluation time it
+  returns the original three marginal scores as `P(silence)`,
+  `P(wearer_only)+P(overlap)`, and `P(others_only)+P(overlap)`.
+
+The four-state marginals are intentionally not renormalized. Keep features,
+split, fusion, optimizer, schedule, and seeds fixed when comparing these losses.
+For checkpoint selection, reserve one official training session such as
+Session 12 with `--dev-sessions 12`; Sessions 1--3 remain test-only.
+
 Recommended experimental procedure:
 
 1. Freeze Qwen and extract all training-session states offline.