Now
What I’m doing now
Currently reading
- How Seer and SimVLA expose model inputs, state, and action outputs differently.
- Ways to reuse model state while keeping approximation and evaluation boundaries clear.
Currently building
View projects- A shared experiment layout for running VLA models with separate model, method, environment, and result settings.
- Run manifests and environment snapshots that make experiment context easier to revisit.
Questions on my mind
View research questions- Which parts of a VLA experiment can be shared across models?
- Which representations can be reused without changing behavior in ways I cannot see?
- How much context is enough to understand an old experiment later?