Stanford postdoc brings MessyMem and MessyNav to CoRL 2026, plus Learn@Deploy workshop
leto__jean · x · 2026-11-10
A Stanford IPRL postdoc presents first postdoc papers at CoRL 2026:
- MessyMem: learning-from-doing memory for mobile manipulation, in the SISREN spotlight session
- MessyNav: zero-shot navigation via manipulation in messy environments
- Co-organizing the Learn@Deploy half-day workshop on robot learning at deployment time: test-time optimization, self-critique, and safe online adaptation under real compute, memory and safety constraints
Workshop themes include agentic code generation in the loop, deployment-time evaluation, and streaming sample-efficiency vs catastrophic forgetting.
More from Embodied
- New-gen UMI gripper passes real-world bar test, lifting a full glass of water — YuXiang_IRVL · 2026-11-10
- Unitree G1 humanoid learns to walk from scratch in under an hour on an old GPU — MarcJSchmidt · 2026-11-10
- Steve Waslander appointed Director of U of T Robotics Institute — VectorInst · 2026-11-10
- Boston Dynamics' Atlas robot learns to roller skate and pull off a 360 aerial spin — adariostrange · 2026-11-10
- Embodied Turing Machines: coding agents write reusable robot routines, 70.24% on 42 bimanual tasks — jiqizhixin · 2026-11-10
- CoRL 2026: EgoScale lands oral session, latest GR00T2 results at H2R workshop — chris_j_paxton · 2026-11-10