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@@ -9,4 +9,6 @@ The model is trained on samples collected from the training splits of [VLN-CE](h
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| VLN-CE R2R Val. | 10.7 | 5.65 | 49.2 | 41.9 | 36.5 |
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| [VLN-CE R2R Test](https://eval.ai/web/challenges/challenge-page/719/leaderboard/1966) | 11.3 | 5.39 | 52 | 45 | 39 |
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| VLN-CE RxR Val. | 15.4 | 5.72 | 55.6 | 45.7 | 38.2 |
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| VLN-CE R2R Val. | 10.7 | 5.65 | 49.2 | 41.9 | 36.5 |
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| [VLN-CE R2R Test](https://eval.ai/web/challenges/challenge-page/719/leaderboard/1966) | 11.3 | 5.39 | 52 | 45 | 39 |
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| VLN-CE RxR Val. | 15.4 | 5.72 | 55.6 | 45.7 | 38.2 |
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The related inference code can be found in [here](https://github.com/jzhzhang/NaVid-VLN-CE)
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