17 citations · 22 across the 9 of their papers we have counts for
9 papers
Representation Learning in Diffusion and Flow-based Model: An Application Aspect
Yanchen Xu, Sida Huang, Zhenyu Gu +3
Diffusion models and flow-based models have recently become the dominant paradigms in generative modeling, largely due to their ability to learn rich, multi-level visual representa…
Safeguarding Text-to-Image Generative Models Against Unauthorized Knowledge Distillation
Yilan Gao, Sida Huang, Hongyuan Zhang +1
Closed-weight generative services are increasingly deployed through query-based APIs, where users can obtain generated outputs while model parameters remain inaccessible. However,…
Explore How to Inject Beneficial Noise in MLLMs
Ruishu Zhu, Sida Huang, Ziheng Jiao +1
Multimodal Large Language Models (MLLMs) have played an increasingly important role in multimodal intelligence. However, the existing fine-tuning methods often ignore cross-modal h…
Rectified Noise: A Generative Model Using Positive-incentive Noise
Zhenyu Gu, Yanchen Xu, Sida Huang +2
Rectified Flow (RF) has been widely used as an effective generative model. Although RF is primarily based on probability flow Ordinary Differential Equations (ODE), recent studies…
Laytrol: Preserving Pretrained Knowledge in Layout Control for Multimodal Diffusion Transformers
Sida Huang, Siqi Huang, Ping Luo +1
With the development of diffusion models, enhancing spatial controllability in text-to-image generation has become a vital challenge. As a representative task for addressing this c…
CoLM: Collaborative Large Models via A Client-Server Paradigm
Siqi Huang, Sida Huang, Hongyuan Zhang
Large models have achieved remarkable performance across a range of reasoning and understanding tasks. Prior work often utilizes model ensembles or multi-agent systems to collabora…
AI Flow: Perspectives, Scenarios, and Approaches
Hongjun An, Wenhan Hu, Sida Huang +11
Pioneered by the foundational information theory by Claude Shannon and the visionary framework of machine intelligence by Alan Turing, the convergent evolution of information and c…
Enhance Vision-Language Alignment with Noise
Sida Huang, Hongyuan Zhang, Xuelong Li
With the advancement of pre-trained vision-language (VL) models, enhancing the alignment between visual and linguistic modalities in downstream tasks has emerged as a critical chal…
Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noise
Hongyuan Zhang, Yanchen Xu, Sida Huang +1
Inspired by the idea of Positive-incentive Noise (Pi-Noise or -Noise) that aims at learning the reliable noise beneficial to tasks, we scientifically investigate the connection…