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README.md
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@@ -66,40 +66,45 @@ This openvla-oft model is trained on ``Haozhan72/Openvla-oft-SFT-libero10-trajal
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## Full OOD Evaluation and Results
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### Overall OOD Eval Results
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Note: rl4vla refers to the paper VLA-RL-Study: What Can RL Bring to VLA Generalization? An Empirical Study.
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### OOD Eval on Vision
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| Description
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| vision avg
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| unseen table
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| dynamic texture (weak) |
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| dynamic texture (strong)
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| dynamic noise (weak)
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| dynamic noise (strong)
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### OOD Eval on Semantic
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| unseen
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| unseen
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| multi-object (both
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### OOD Eval on Position
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## How to Use
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Please integrate the provided model with the [RLinf](https://github.com/RLinf/RLinf) codebase. To do so, modify the following parameters in the configuration file ``examples/embodiment/config/maniskill_grpo_openvlaoft.yaml``:
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## Full OOD Evaluation and Results
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### Overall OOD Eval Results
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Note: rl4vla refers to the paper [VLA-RL-Study: What Can RL Bring to VLA Generalization? An Empirical Study](https://arxiv.org/abs/2505.19789).
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| Description | rl4vla | __GRPO-openvlaoft__ | PPO-openvlaoft | PPO-openvla | GRPO-openvla |
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|-------------|--------|---------------------|----------------|-------------|--------------|
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| Avg results | 76.08 | 61.48 | 64.53 | **82.21** | 75.47 |
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### OOD Eval on Vision
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| Description | rl4vla | __GRPO-openvlaoft__ | PPO-openvlaoft | PPO-openvla | GRPO-openvla |
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|-------------|--------|---------------------|----------------|-------------|--------------|
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| vision avg | 76.56 | 84.69 | 80.55 | **82.03** | 74.69 |
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| unseen table | 84.40 | 91.41 | 94.53 | **95.70** | 89.84 |
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| dynamic texture (weak) | 83.30 | **91.02** | 82.42 | 85.55 | 78.91 |
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| dynamic texture (strong) | 63.00 | **77.34** | 62.50 | 72.27 | 65.62 |
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| dynamic noise (weak) | 85.40 | 89.45 | **89.84** | 87.11 | 79.69 |
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| dynamic noise (strong) | 66.70 | **74.22** | 73.44 | 69.53 | 59.38 |
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### OOD Eval on Semantic
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| Description | rl4vla | __GRPO-openvlaoft__ | PPO-openvlaoft | PPO-openvla | GRPO-openvla |
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|-------------|--------|---------------------|----------------|-------------|--------------|
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| object avg | 75.40 | 51.61 | 56.64 | **80.57** | 74.41 |
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| train setting | 93.80 | 94.14 | 91.80 | **96.09** | 84.38 |
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| unseen objects | 71.40 | 80.47 | 77.73 | **81.64** | 76.56 |
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| unseen receptacles | 75.00 | 74.22 | 78.12 | **81.25** | 73.44 |
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| unseen instructions | 89.10 | 67.97 | 68.36 | **94.53** | 89.06 |
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| multi-object (both seen) | 75.00 | 35.16 | 42.97 | **84.38** | 75.78 |
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| multi-object (both unseen) | 57.80 | 30.47 | 38.67 | **62.89** | 57.81 |
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| distractive receptacle | 81.20 | 18.75 | 31.64 | **82.81** | 78.12 |
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| multi-receptacle (both unseen) | 59.90 | 11.72 | 23.83 | **60.94** | 60.16 |
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### OOD Eval on Position
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| Description | rl4vla | __GRPO-openvlaoft__ | PPO-openvlaoft | PPO-openvla | GRPO-openvla |
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|-------------|--------|---------------------|----------------|-------------|--------------|
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| position avg | 77.60 | 42.97 | 56.05 | **89.26** | 81.64 |
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| unseen position (object & receptacle) | 80.70 | 40.23 | 50.39 | **86.33** | 75.00 |
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| mid-episode object reposition | 74.50 | 45.70 | 61.72 | **92.19** | 88.28 |
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## How to Use
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Please integrate the provided model with the [RLinf](https://github.com/RLinf/RLinf) codebase. To do so, modify the following parameters in the configuration file ``examples/embodiment/config/maniskill_grpo_openvlaoft.yaml``:
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