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Benchmark

LIBERO-Long

Reported in 3 papers on Zotpaper. The latest, each as the paper states it:

Scoring imagined futures and actions before execution triples robot success rates70.8% success rate
Autoregressive video pretraining unlocks the value of long context for real-time robot control99.5% success rate
Structured intermediate rewards improve robots on long, dependent tasks96.6% success rate

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2 results for “LIBERO-Long”

Research · Robotics & embodied AI
Autoregressive video pretraining unlocks the value of long context for real-time robot control
Long-WAM: Scaling the Context of World-Action Models
Long-WAM scales visual history up to 19.2 seconds for action prediction, achieving high success on dynamic tasks.
LIBERO-Long: 99.5% success rate (as reported)
9 Oct 2026NVIDIA, MIT, HKU
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-Long: 96.6% success rate (as reported)
30 Sept 2026The Pennsylvania State University, Amazon AWS AICode