14 citations · 14 across the 5 of their papers we have counts for
5 papers
Smart-GRPO: Smartly Sampling Noise for Efficient RL of Flow-Matching Models
Benjamin Yu, Jackie Liu, Justin Cui
Recent advancements in flow-matching have enabled high-quality text-to-image generation. However, the deterministic nature of flow-matching models makes them poorly suited for rein…
Self-Forcing++: Towards Minute-Scale High-Quality Video Generation
Justin Cui, Jie Wu, Ming Li +6
Diffusion models have revolutionized image and video generation, achieving unprecedented visual quality. However, their reliance on transformer architectures incurs prohibitively h…
Latent Video Dataset Distillation
Ning Li, Antai Andy Liu, Jingran Zhang +1
Dataset distillation has demonstrated remarkable effectiveness in high-compression scenarios for image datasets. While video datasets inherently contain greater redundancy, existin…
Mitigating Bias in Dataset Distillation
Justin Cui, Ruochen Wang, Yuanhao Xiong +1
Dataset Distillation has emerged as a technique for compressing large datasets into smaller synthetic counterparts, facilitating downstream training tasks. In this paper, we study…
DC-BENCH: Dataset Condensation Benchmark
Justin Cui, Ruochen Wang, Si Si +1
Dataset Condensation is a newly emerging technique aiming at learning a tiny dataset that captures the rich information encoded in the original dataset. As the size of datasets con…