Counterfactual debugging scales sim2real failure diagnosis to 1M steps in world models
sarahcat21 · x · 2026-09-03
Researchers propose Counterfactual Debugging to diagnose why world-model-trained agents fail in deployment, using causal attribution over simulated counterfactuals to pinpoint safety failures. The key advance: a divide-and-conquer approach scales counterfactual debugging to 1M steps, making it practical to locate the true sim2real gap.
Related event: Counterfactual Debugging Pins Down Sim2Real Failures at Million-Step Scale(4 posts)→
More from Embodied
- MIT's SANDO Drone Planner Avoids Every Moving Obstacle Across 12 Real Flights — Olivier__OG · 2026-10-18
- SimInfinity: open-source robotic simulation benchmark with 10K real-world tasks — joemeno · 2026-10-18
- Robi: a German/English voice companion demo built on Gemma, Tyger and Humaneness Voice TTS — realmrfakename · 2026-10-18
- Munich's Plim unveils wheeled home-care humanoid controllable from 9,000 km away — CyberRobooo · 2026-10-18
- Musk says Optimus and Cybercab will make up the vast majority of Tesla's value — XFreeze · 2026-10-18
- SAE weight editing steers robot behavior at inference time, IIIT Hyderabad paper lands IJCAI Safe Physical AI workshop — ponguru · 2026-10-18