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README.md

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-title: Weak Supervision Reasoning
-emoji: 🔥
-colorFrom: red
-colorTo: yellow
+title: Weak Supervision Reasoning Explorer
+emoji: 🔬
+colorFrom: purple
+colorTo: pink
 sdk: gradio
-sdk_version: 6.13.0
+sdk_version: 4.36.0
 app_file: app.py
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Weak Supervision Reasoning Explorer
+
+Interactive demo exploring when LLMs can learn to reason with weak supervision, based on paper 2604.18574.
+
+**Hypothesis:** Models that generalize under weak supervision exhibit a prolonged pre-saturation phase during which training reward and downstream performance climb together, while rapid saturation indicates memorization.
+
+## Key Findings from Paper
+
+- **Reward Saturation Dynamics:** Models that generalize show prolonged pre-saturation
+- **Reasoning Faithfulness:** Intermediate steps logically supporting final answers predict generalization
+- **SFT is Critical:** Supervised fine-tuning on explicit reasoning traces enables weak supervision generalization
+
+## Features
+
+- Visualize reward saturation curves
+- Compare reasoning faithfulness across models
+- Interactive weak supervision scenarios