ivanov-tech/roadmap23-leader-corrective-plus300

Roadmap23 corrective +300

Research checkpoint: 300 additional supervised updates from parent revision e7d65c5babf0212f8a2c95eec585868e4c4f0059, not training from scratch. Architecture: LingBot-VLA v2. Vision encoder frozen; language/action components trained. The mixture combines standard LIBERO replay, prior swap examples, and corrective demonstrations for bowl, milk, and salad-dressing tasks. Original 600-update schedule was paused at 300. No reinforcement learning was used.

Evidence and limits (2026-09-06)

Targeted matched bowl/milk tests: parent18/48 versus this checkpoint37/48; new-layout subset11/30 versus22/30. This was an interrupted larger test, with unresolved exact camera-equivalence/numerical-noise caveats, not proof of broad benefit. Separate 112-attempt LIBERO-PRO panel: this checkpoint73/112, folded six-component estimate0.601190; Apex comparator84/112,0.714286. Fresh actual-parent112 control is pending at publication. One initial-state trial per selected task/variant; not an official subnet result or a full benchmark. No championship claim.

Inference weights and configs only. Dataset, private scene banks, optimizer, and distributed training state are NOT included. See MODELMANIFEST.json for source hashes and parent provenance. Uses upstream LingBot-VLA v2 inference with official LIBERO normalization (training/normstats.json); our evaluation predicted50 actions and executed5 before replanning, with10 denoising steps. Tokenizer/processor assets come unchanged from the public parent. Parent did not publish a license/model card at the pinned revision; this card does not grant additional rights over upstream components. Check upstream terms.