Initial commit: caption quality test on UAV-VisLoc

Self-contained experimental track validating generated text captions
via retrieval R@1 lift on UAV-VisLoc.

Architecture: GeoRSCLIP ViT-B/32 dual encoder, 512-dim shared space.
Loss: 4-term InfoNCE (img-img + sat-cap + drone-cap + cap-cap)
      with cosine temperature decay, PALW-like curriculum.
Metric: delta R@1 (with text - without text) >= +3% => PASS.

Gin-configured (balanced / baseline_no_text / text_heavy variants).
Follows NADEZHDA code style.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/losses/__init__.py

@@ -0,0 +1,8 @@
+"""Loss functions for caption quality test."""
+from src.losses.multi_infonce import (
+    MultiTermInfoNCE,
+    cosine_temperature,
+    curriculum_lambdas,
+)
+
+__all__ = ["MultiTermInfoNCE", "cosine_temperature", "curriculum_lambdas"]