4 papers
Recurrent Sinusoidal INRs for Efficient High-Fidelity Representation
Hyunmin Cho, Jaejun Yoo, Kyong Hwan Jin
We study sinusoidal recurrence as an iterative mechanism for harmonic spectral enrichment in implicit neural representations (INRs). Our analysis reveals that sinusoidal activation…
Balancing Fidelity and Diversity in Diffusion Models via Symmetric Attention Decomposition: Hopfield Perspective
Hyunmin Cho, Woo Kyoung Han, Kyong Hwan Jin
We characterize the pre-softmax attention matrix in transformers as an associative memory matrix encoding pairwise associations between input features. By decomp…
TAG: Tangential Amplifying Guidance for Hallucination-Resistant Sampling
Hyunmin Cho, Donghoon Ahn, Susung Hong +3
Diffusion models achieve state-of-the-art image generation but often produce semantic inconsistencies, or hallucinations. Existing inference-time guidance methods rely on external…
Towards Lossless Implicit Neural Representation via Bit Plane Decomposition
Woo Kyoung Han, Byeonghun Lee, Hyunmin Cho +2
We quantify the upper bound on the size of the implicit neural representation (INR) model from a digital perspective. The upper bound of the model size increases exponentially as t…