We have 3 of 9 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
DiffAdapterVLA is introduced, which realizes Planning in the Backbone: it injects explicit trajectory tokens into selected VLM late layers, bringing trajectory state into backbone forward computation, where it co-evolves with driving conditions at different depths.
A novel framework that aligns multi-trajectory supervision with policy optimization, and introduces two complementary mechanisms: feasibility-first advantage assignment and dynamic distillation to ensure that expanded trajectory supervision is effectively absorbed during policy optimization.
SimWAM, a simple yet effective WAM that leverages future-video prediction as a training-time supervision signal, co-trains a pretrained video expert and a lightweight action expert with joint flow matching and applies reinforcement learning to optimize a compositional driving reward beyond trajectory imitation.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
