PhD student, Korea Advanced Institute of Science & Technology
2 papers at NeurIPS 2025
We propose a modular inductive bias for disentangled representation learning, which we term a compositional bias, decoupled from both learning objectives and model architectures.
Few-shot spatial control for Text-to-Image Diffusion models by leveraging the analogy between query and support spatial conditions to construct task-specific control features.
