jmonas commited on
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1 Parent(s): 7a19191

Update app.py

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  1. app.py +2 -2
app.py CHANGED
@@ -137,7 +137,7 @@ def main():
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  "Welcome to the 1X World Model Challenge. This platform hosts two challenges—Compression and Sampling—focused on advancing research in world models for robotics."
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  )
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  st.write(
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- "In partnership with OpenDriveLab, we are launching this challenge as part of the [Autonomous Grand Challenge 2025](https://opendrivelab.com/challenge2025/), held in conjunction with the CVPR 2025 (confirmed) and ICCV 2025 (tentative) workshops."
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  )
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  st.markdown("---")
@@ -255,7 +255,7 @@ def main():
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  st.markdown("## Already Started Working on These Challenges?")
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  st.write(
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  """
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- Before partnering with OpenDriveLab to launch the World Model Challenge at CVPR 2025 and (tentatively) ICCV 2025, we had already released the Compression and Sampling challenges publicly, offering $10K for each. However, due to the rapid progress in the field, we are updating the challenge setups.
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  For the Compression Challenge, we initially used the MAGVIT spatial tokenizer to compare participant losses. We are now switching to the highly performant Cosmos spatial-temporal tokenizer as our new standard.
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  "Welcome to the 1X World Model Challenge. This platform hosts two challenges—Compression and Sampling—focused on advancing research in world models for robotics."
138
  )
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  st.write(
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+ "In partnership with OpenDriveLab, we are launching this challenge as part of the [Autonomous Grand Challenge 2025](https://opendrivelab.com/challenge2025/), held in conjunction with the [CVPR 2025](https://opendrivelab.com/cvpr2025/workshop/) and [ICCV 2025](https://opendrivelab.com/iccv2025/workshop/) workshops."
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  )
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  st.markdown("---")
 
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  st.markdown("## Already Started Working on These Challenges?")
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  st.write(
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  """
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+ Before partnering with OpenDriveLab to launch the World Model Challenge at CVPR 2025 and ICCV 2025, we had already released the Compression and Sampling challenges publicly, offering $10K for each. However, due to the rapid progress in the field, we are updating the challenge setups.
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  For the Compression Challenge, we initially used the MAGVIT spatial tokenizer to compare participant losses. We are now switching to the highly performant Cosmos spatial-temporal tokenizer as our new standard.
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