Featured

Evaluating a Frozen Frontier VLM Directly as a Robot Policy on the RoboMME Memory-Dependent Manipulation Benchmark

The study uses a frozen frontier vision-language model, GPT-6-Astra, directly as the robot policy and tests it on RoboMME, a benchmark of 16 memory-dependent manipulation tasks. The model keeps the entire episode context throughout and directly outputs each end-effector waypoint and gripper command, with no training specific to this benchmark.

Part of the event: Frozen frontier VLM used directly as robot policy achieves 92.1% success rate on RoboMME

This page provides a summary and source link only.