WORLD-MODELS / Adaptation draft v2; action-mechanism gate failed; unsubmitted

KineJing: resource-efficient adaptation and evaluation of tri-view robot predictors

A separate 11,285-parameter prototype improves reused-set pixel error, while EEF removal gives similar performance; action contribution, unseen-task validity and artifact binding remain unresolved.

The scored historical system, local adapter and small prototype are different evidence objects; scores cannot be transferred between them.

Why we tried it

Adapt a released tri-view predictor on constrained hardware and test whether gains depend on actions.

What the evidence shows

A 71.06% matched local error reduction still trailed persistence; a separate small prototype improved about 6.54%, while EEF removal performed similarly.

Where the work stands

The historical scored system, adapter and prototype are distinct; ten reused trajectories do not establish causal action contribution or unseen-task validity.

Possible next steps

Use untouched task groups and paired action-divergent branches, vary adapter seeds, and bind exact model and evaluation artifacts.

Suggested next steps are untested research questions, not new experimental results. The archive records manuscript provenance, licensing and status.