July research dual-track: Photoroom PRX's data captioner + SUNTA's surprise-driven video prediction to 250 timesteps

Two method-level research notes this week — neither ships a new model. Photoroom's 7/6 PRX Part 4 documents a data pipeline that re-captions every PRX training image with Qwen3-VL-8B, validates long captions > short, JPEG q92 ≈ PNG, and lowers FID/CMMD/DINO-MMD on PRX pre-training; data lives in Lance and is rewritten into Mosaic Data Shards with resolution + aspect-ratio bucketing. arXiv 7/2 paper SUNTA drives hierarchical-SSM chunk boundaries by prediction errors ('surprise'), keeping 2D and 3D video predictions accurate over 250 timesteps while every baseline degrades within 10. Both are 'do data / do structure right on top of existing models,' not 'stack bigger parameters.'