LeCuration: A Tiny World Model as a Data Curation Multi-Tool

LeCuration is a tiny world model used to curate data for another, larger downstream model. It uses LeWorldModel (LeWM) as a latent encoder and predictor, and adds a DiT decoder to supply visuals for autoregressive gameplay rollouts; its embeddings can serve as an anomaly detection signal and a content-based clustering heuristic, while autoregressive prediction of game state can be used to qualitatively check whether actions and states are consistent. The team ran a qualitative proof of concept on CS:GO gameplay data and has not yet reported quantitative curation metrics or downstream training results.