STAL transfers spectral tail uplift cues via a frequency teacher to train a spatial detector for AI-generated images, discarding frequency modules at inference for strong cross-generator generalization.
Denoising diffusion probabilistic models
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 5verdicts
UNVERDICTED 5roles
background 1polarities
background 1representative citing papers
Reconstruction of global 1.5 km resolution 10 m vector winds in tropical cyclone inner cores from sparse CYGNSS scalar observations using generalized score-based diffusion assimilation plus three TC boundary-layer constraints.
A latent diffusion model jointly synthesizes MRI volumes and mixed-type tabular clinical data in a shared space via cross-attention and separate decoders after VAE fusion.
Continuous diffusion spoken language models follow scaling laws for loss and phoneme divergence and generate emotive multi-speaker speech at 16B scale, though long-form coherence stays difficult.
AdaCorrection adaptively corrects offset caches in DiT inference via on-the-fly spatio-temporal validity checks to maintain near-original FID with moderate acceleration.
citing papers explorer
-
Spectral Tail Auxiliary Learning for AI-Generated Image Detection
STAL transfers spectral tail uplift cues via a frequency teacher to train a spatial detector for AI-generated images, discarding frequency modules at inference for strong cross-generator generalization.
-
Global kilometre-scale tropical cyclone inner-core vector winds from sparse scalar CYGNSS observations
Reconstruction of global 1.5 km resolution 10 m vector winds in tropical cyclone inner cores from sparse CYGNSS scalar observations using generalized score-based diffusion assimilation plus three TC boundary-layer constraints.
-
Multimodal synthesis of MRI and tabular data with diffusion in a joint latent space via cross-attention
A latent diffusion model jointly synthesizes MRI volumes and mixed-type tabular clinical data in a shared space via cross-attention and separate decoders after VAE fusion.
-
Scaling Properties of Continuous Diffusion Spoken Language Models
Continuous diffusion spoken language models follow scaling laws for loss and phoneme divergence and generate emotive multi-speaker speech at 16B scale, though long-form coherence stays difficult.
-
AdaCorrection: Adaptive Offset Cache Correction for Accurate Diffusion Transformers
AdaCorrection adaptively corrects offset caches in DiT inference via on-the-fly spatio-temporal validity checks to maintain near-original FID with moderate acceleration.