---
title: LIBERO-Pro
description: "Plug-and-play LIBERO overlay that probes memorization: object, pose, instruction, task, and environment shifts. WorldFoundry imports official rollouts."
---

LIBERO-PRO (Huazhong University of Science and Technology, with Harvard, MIT, WUT, and Lehigh) is **not** a new lifelong suite and **not** [LIBERO-Plus](/docs/evaluation/benchmark-hub/libero-plus)'s 10,030-instance factor grid. It is a **plug-and-play** overlay on the original LIBERO tasks. The claim is that stock LIBERO train/eval are almost the same scene, so 90%+ scores can be rote replay. PRO applies **reasonable** perturbations and asks whether the policy still grounds the instruction.

Five official types (Figure 6 in the paper):

- **Object attributes** — color, texture, scale; same semantic target.
- **Initial configuration** — placements that stay physically valid. Small position shifts are where many VLAs go to zero.
- **Instruction** — paraphrases of the same goal.
- **Task redesign** — new object sets or composed goals. These do **not** mix with the other four.
- **Environment** — background, lighting, texture; feasibility unchanged.

The other four types can be combined. Official eval matches stock LIBERO: **50 episodes per task**. The paper reports models above **90%** on clean LIBERO collapsing to **0%** under generalized PRO settings — an upstream finding, not a hub row.

Paper: [LIBERO-PRO](https://arxiv.org/abs/2510.03827). Project: [LIBERO-PRO webpage](https://zxy-mllab.github.io/LIBERO-PRO-Webpage/). Code: [Zxy-MLlab/LIBERO-PRO](https://github.com/Zxy-MLlab/LIBERO-PRO) (MIT). Dataset: `zhouxueyang/LIBERO-Pro`.

WorldFoundry is **official-results only**. You run the upstream overlay, then `official-validation` normalizes the export. No in-tree robosuite. [Base LIBERO](/docs/evaluation/benchmark-hub/libero) can wire closed-loop execution; this card cannot.

<BenchmarkPageSections id="libero-pro" locale="en" />

## How to run

```bash
worldfoundry-eval zoo benchmark-run \
  --benchmark-id libero-pro \
  --mode official-validation \
  --official-results-path <official_results.json> \
  --output-dir tmp/libero-pro/official-validation \
  --json
```

Optional `WORLDFOUNDRY_LIBERO_PRO_ROOT` points at the `Zxy-MLlab/LIBERO-PRO` checkout. Default import path: `WORLDFOUNDRY_LIBERO_PRO_RESULTS_PATH`. Manifest: `worldfoundry/data/benchmarks/tasks/external/libero-pro.yaml`. Outputs: `scorecard.json` (primary `success_rate`), `raw_results.jsonl`, and `evaluation/summary.json`.

[← Benchmark Hub](/docs/evaluation/benchmark-hub)