8 papers
Timing Matters Twice: When to Query and When to Skip in Flow-Matching On-Policy Distillation
Renye Yan, Junyi Zhan, Jikang Cheng +1
On-policy distillation (OPD) enables flow-matching models to acquire complementary capabilities from specialized teachers through supervision on student-generated trajectories. How…
Pixel-Space Diffusion Transformers
Renye Yan, Jikang Cheng, You Wu +8
Latent diffusion models (LDMs) enable efficient high-resolution image synthesis by denoising in a VAE-compressed latent space. However, fixed visual tokenizers can discard fine tex…
PAST: Prompt-Adaptive Sampling Termination for Efficient Diffusion Model
Renye Yan, Jikang Cheng, You Wu +4
While diffusion models have made significant progress in text-to-image tasks, they still exhibit limitations when directly optimizing downstream objectives. Although Reinforcement…
Explore or Converge? Stage-Guided Per-Step Optimization for Diffusion Models
Renye Yan, Jikang Cheng, You Wu +4
Diffusion models have strong generative capabilities. However, their maximum likelihood training objective only focuses on reconstructing the data distribution, making it difficult…
InfoDense: Density-Aware Regional Decisive Replay for Memory-Efficient Incremental Face Forgery Detection
Jikang Cheng, Hao Shen, Xueyi Zhang +4
The rapid evolution of face forgery techniques has introduced an increasing variety of manipulations. Incremental Face Forgery Detection (IFFD), which incrementally adds new forger…
Do Less, Achieve More: Do We Need Every-Step Optimization for RL Fine-tuning of Diffusion Models?
Renye Yan, Jikang Cheng, Shikun Sun +7
Despite strong image-generation performance, diffusion models' reconstruction objectives limit alignment with human preferences. RL enables such alignment through explicit rewards.…
A Sanity Check for Multi-In-Domain Face Forgery Detection in the Real World
Jikang Cheng, Renye Yan, Zhiyuan Yan +5
Existing methods for deepfake detection aim to develop generalizable detectors. Although "generalizable" is the ultimate target once and for all, with limited training forgeries an…
When Generative Replay Meets Evolving Deepfakes: Dual Confusion-Aware Regularization for Incremental Face Forgery Detection
Hao Shen, Jikang Cheng, Renye Yan +3
The rapid advancement of face generation techniques has introduced an increasing variety of forgery methods, making incremental deepfake detection essential for maintaining robust…