PhD student, Korea Advanced Institute of Science and 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.
We propose language-grounded visual concept learning in real-world scenes
