2 citations · 9 across the 25 of their papers we have counts for
10 papers · 1 filter
The Path Not Taken: RLVR Provably Learns Off the Principals
Hanqing Zhu, Zhenyu Zhang, Hanxian Huang +11
Reinforcement Learning with Verifiable Rewards (RLVR) reliably improves the reasoning performance of large language models, yet it appears to modify only a small fraction of parame…
Discriminator-Free Direct Preference Optimization for Video Diffusion
Haoran Cheng, Qide Dong, Liang Peng +7
Direct Preference Optimization (DPO), which aligns models with human preferences through win/lose data pairs, has achieved remarkable success in language and image generation. Howe…
HOFAR: High-Order Augmentation of Flow Autoregressive Transformers
Yingyu Liang, Zhizhou Sha, Zhenmei Shi +2
Flow Matching and Transformer architectures have demonstrated remarkable performance in image generation tasks, with recent work FlowAR [Ren et al., 2024] synergistically integrati…
Force Matching with Relativistic Constraints: A Physics-Inspired Approach to Stable and Efficient Generative Modeling
Yang Cao, Bo Chen, Xiaoyu Li +5
This paper introduces Force Matching (ForM), a novel framework for generative modeling that represents an initial exploration into leveraging special relativistic mechanics to enha…
Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies
Yuefan Cao, Xiaoyu Li, Yingyu Liang +4
As AI research surges in both impact and volume, conferences have imposed submission limits to maintain paper quality and alleviate organizational pressure. In this work, we examin…
High-Order Matching for One-Step Shortcut Diffusion Models
Bo Chen, Chengyue Gong, Xiaoyu Li +5
One-step shortcut diffusion models [Frans, Hafner, Levine and Abbeel, ICLR 2025] have shown potential in vision generation, but their reliance on first-order trajectory supervision…
RichSpace: Enriching Text-to-Video Prompt Space via Text Embedding Interpolation
Yuefan Cao, Chengyue Gong, Xiaoyu Li +4
Text-to-video generation models have made impressive progress, but they still struggle with generating videos with complex features. This limitation often arises from the inability…
On Computational Limits and Provably Efficient Criteria of Visual Autoregressive Models: A Fine-Grained Complexity Analysis
Yekun Ke, Xiaoyu Li, Yingyu Liang +3
Recently, Visual Autoregressive () Models introduced a groundbreaking advancement in the field of image generation, offering a scalable approach through a coarse-to-f…
On Computational Limits of FlowAR Models: Expressivity and Efficiency
Yang Cao, Chengyue Gong, Yekun Ke +5
The expressive power and computational complexity of deep visual generative models, such as flow-based and autoregressive (AR) models, have gained considerable interest for their w…
DPBloomfilter: Securing Bloom Filters with Differential Privacy
Yekun Ke, Yingyu Liang, Zhizhou Sha +3
The Bloom filter is a simple yet space-efficient probabilistic data structure that supports membership queries for dramatically large datasets. It is widely utilized and implemente…