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Benchmark

LIBERO

Reported in 31 papers on Zotpaper. The latest, each as the paper states it:

AI robot controllers raise average task success from 33% to 95%85% success rate
Simple prompt trick stops AI agents from faking progress in robot tasks51.4% Success@25
Scoring imagined futures and actions before execution triples robot success rates78.3% mean success

LIBERO-Plus (16)LIBERO-PRO (6)LIBERO-Long (3)All benchmarks →

3 results for “LIBERO”

Research · Robotics & embodied AI
Robots learn tasks better with demonstrations generated by a video model
RynnWorld-Latent: A Cross-Embodiment World Model Conditioned on Universal Latent Actions
Zhao and colleagues report that a model trained across human, robot and simulation videos generates additional demonstrations that improve robot policy success in the evaluated settings.
LIBERO: 96.1% success rate (as reported)
30 Oct 2026Hong Kong Embodied AI Lab, CUHK, DAMO Academy, Alibaba Group
Research · Robotics & embodied AI
Synthetic demonstrations let robot policies escape sparse-reward failures
SynthDemo-RL: Breaking the Zero-Reward Barrier in VLA Adaptation with LLM-Guided Synthetic Demonstrations
An automated teacher supplied successful manipulation trajectories that enabled subsequent reinforcement learning on tasks where direct PPO received no reward.
LIBERO: 96% success rate (as reported)
21 Sept 2026Fujitsu Limited, The Institute of Statistical Mathematics
Research · Robotics & embodied AI
Structured intermediate rewards improve robots on long, dependent tasks
StructRL: Online Structured Reinforcement Learning for Long-Horizon Vision-Language-Action Tasks
StructRL rewards verified subtasks in prerequisite order, giving robot policies useful feedback before an entire manipulation sequence succeeds.
LIBERO Goal: 95.6% success rate (as reported)
30 Sept 2026The Pennsylvania State University, Amazon AWS AICode