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app.py

@@ -347,51 +347,51 @@ def main():
 
     st.markdown("## FAQs")
 
-    st.markdown("**How should I preprocess the dataset?**")
-    st.write(
-        "The raw data in the `world_model_raw_data` dataset is provided as-is, with no additional preprocessing. "
-        "You are free to apply your own steps—such as resizing, normalization, or augmentation—but please document all preprocessing methods in your technical report."
-    )
+    with st.expander("How should I preprocess the dataset?"):
+        st.write(
+            "The raw data in the `world_model_raw_data` dataset is provided as-is, with no additional preprocessing. "
+            "You are free to apply your own steps—such as resizing, normalization, or augmentation—but please document all preprocessing methods in your technical report."
+        )
 
-    st.markdown("**What output format is expected for predictions?**")
-    st.write(
-        "For the Sampling Challenge, your model should output a predicted video frame in RGB format at a resolution of 512×512 pixels. "
-        "For the Evaluation Challenge, you should submit a ranked list of the provided policies based on their expected real-world performance."
-    )
+    with st.expander("What output format is expected for predictions?"):
+        st.write(
+            "For the Sampling Challenge, your model should output a predicted video frame in RGB format at a resolution of 512×512 pixels. "
+            "For the Evaluation Challenge, you should submit a ranked list of the provided policies based on their expected real-world performance."
+        )
 
-    st.markdown("**What evaluation metrics will be used?**")
-    st.write(
-        "The Compression Challenge is evaluated by the model's loss (e.g., cross-entropy or mean squared error). "
-        "The Sampling Challenge will use image quality metrics like PSNR and SSIM, while the Evaluation Challenge is assessed by comparing your ranking "
-        "against the ground-truth ranking using correlation metrics such as Spearman's rho."
-    )
+    with st.expander("What evaluation metrics will be used?"):
+        st.write(
+            "The Compression Challenge is evaluated by the model's loss (e.g., cross-entropy or mean squared error). "
+            "The Sampling Challenge will use image quality metrics like PSNR and SSIM, while the Evaluation Challenge is assessed by comparing your ranking "
+            "against the ground-truth ranking using correlation metrics such as Spearman's rho."
+        )
 
-    st.markdown("**Are there restrictions on using future frames or actions?**")
-    st.write(
-        "You are allowed to use future actions to condition your frame predictions, but you must not use any actual future frames during inference."
-    )
+    with st.expander("Are there restrictions on using future frames or actions?"):
+        st.write(
+            "You are allowed to use future actions to condition your frame predictions, but you must not use any actual future frames during inference."
+        )
 
-    st.markdown("**Can I modify the baseline models?**")
-    st.write(
-        "Yes, you are encouraged to enhance the provided baseline models. However, any modifications must be thoroughly documented in your technical report, "
-        "and your final submission must be fully reproducible."
-    )
+    with st.expander("Can I modify the baseline models?"):
+        st.write(
+            "Yes, you are encouraged to enhance the provided baseline models. However, any modifications must be thoroughly documented in your technical report, "
+            "and your final submission must be fully reproducible."
+        )
 
-    st.markdown("**How do I ensure my submission is reproducible?**")
-    st.write(
-        "Include complete code, configuration files, and clear instructions for running your model. Non-reproducible submissions may be disqualified."
-    )
+    with st.expander("How do I ensure my submission is reproducible?"):
+        st.write(
+            "Include complete code, configuration files, and clear instructions for running your model. Non-reproducible submissions may be disqualified."
+        )
 
-    st.markdown("**Is there a limit on model size or inference time?**")
-    st.write(
-        "There are no strict limits on model size or inference time, but solutions will be evaluated on both performance and efficiency."
-    )
+    with st.expander("Is there a limit on model size or inference time?"):
+        st.write(
+            "There are no strict limits on model size or inference time, but solutions will be evaluated on both performance and efficiency."
+        )
 
-    st.markdown("**What if I submit a Compression Challenge solution using the old tokenizer?**")
-    st.write(
-        "Solutions using the MAGVIT tokenizer that achieve a loss below 8.0 on our held-out test set will continue to be honored for the $10K award "
-        "for six months from March 1, 2025. However, these submissions will not be eligible for the CVPR/ICCV competitions, which will use the Cosmos tokenizer as the standard."
-    )
+    with st.expander("What if I submit a Compression Challenge solution using the old tokenizer?"):
+        st.write(
+            "Solutions using the MAGVIT tokenizer that achieve a loss below 8.0 on our held-out test set will continue to be honored for the $10K award "
+            "for six months from March 1, 2025. However, these submissions will not be eligible for the CVPR/ICCV competitions, which will use the Cosmos tokenizer as the standard."
+        )
 
     
     st.markdown("---")