Official codebase for Margin-aware Preference Optimization for Aligning Diffusion Models without Reference (MaPO).
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Updated
Jun 11, 2024 - Python
Official codebase for Margin-aware Preference Optimization for Aligning Diffusion Models without Reference (MaPO).
Video Generation Benchmark
[ACM MM 2026] HPSv3++: Scaling Reward Models Across the Full Spectrum of Diffusion Model Capabilities
Personalized Chinese humor generation research: human preference experiments, blind evaluation, negative results, and a Next.js + Supabase web prototype.
Conditional VAE experiments: contextual bandit regret minimization and BERT-embedding human preference / reward prediction on WebGPT comparisons.
EvalAI is our solution for the Smart India Hackathon (SIH) 2026 problem statement: “Human Preference Prediction Model for Large Language Model Responses.”
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