2 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
Data-regularized Reinforcement Learning for Diffusion Models at Scale
Haotian Ye, Kaiwen Zheng, Jiashu Xu +15
Aligning generative diffusion models with human preferences via reinforcement learning (RL) is critical yet challenging. Most existing algorithms are often vulnerable to reward hac…
InfoTok: Adaptive Discrete Video Tokenizer via Information-Theoretic Compression
Haotian Ye, Qiyuan He, Jiaqi Han +12
Accurate and efficient discrete video tokenization is essential for long video sequences processing. Yet, the inherent complexity and variable information density of videos present…
Robust Sampling for Active Statistical Inference
Puheng Li, Tijana Zrnic, Emmanuel Candès
Active statistical inference is a new method for inference with AI-assisted data collection. Given a budget on the number of labeled data points that can be collected and assuming…
CHORDS: Diffusion Sampling Accelerator with Multi-core Hierarchical ODE Solvers
Jiaqi Han, Haotian Ye, Puheng Li +3
Diffusion-based generative models have become dominant generators of high-fidelity images and videos but remain limited by their computationally expensive inference procedures. Exi…
Analyzing the Role of Permutation Invariance in Linear Mode Connectivity
Keyao Zhan, Puheng Li, Lei Wu
It was empirically observed in Entezari et al. (2021) that when accounting for the permutation invariance of neural networks, there is likely no loss barrier along the linear inter…