thinkjepa-dual-temporal-world-model

Replace single-pathway JEPA with a dual-temporal architecture combining dense frame sampling (fine-grained dynamics) and uniformly-sampled VLM guidance (semantic coherence) to improve egocentric trajectory prediction by 14-27% on ADE/accuracy metrics. Effective when predicting hand-object interactions where both low-level dynamics and high-level semantic co…

Independent GitHub snapshot · Automated classification · Original documentation governs