1 citations · 1 across the 13 of their papers we have counts for
13 papers
Flowing Backwards: Improving Normalizing Flows via Reverse Representation Alignment
Yang Chen, Xiaowei Xu, Shuai Wang +5
Normalizing Flows (NFs) are a class of generative models distinguished by a mathematically invertible architecture, where the forward pass transforms data into a latent space for d…
Mem-PAL: Towards Memory-based Personalized Dialogue Assistants for Long-term User-Agent Interaction
Zhaopei Huang, Qifeng Dai, Guozheng Wu +7
With the rise of smart personal devices, service-oriented human-agent interactions have become increasingly prevalent. This trend highlights the need for personalized dialogue assi…
TBStar-Edit: From Image Editing Pattern Shifting to Consistency Enhancement
Hao Fang, Zechao Zhan, Weixin Feng +3
Recent advances in image generation and editing technologies have enabled state-of-the-art models to achieve impressive results in general domains. However, when applied to e-comme…
CTR-Driven Ad Text Generation via Online Feedback Preference Optimization
Yanda Chen, Zihui Ren, Qixiang Gao +5
Advertising text plays a critical role in determining click-through rates (CTR) in online advertising. Large Language Models (LLMs) offer significant efficiency advantages over man…
Minimal Impact ControlNet: Advancing Multi-ControlNet Integration
Shikun Sun, Min Zhou, Zixuan Wang +7
With the advancement of diffusion models, there is a growing demand for high-quality, controllable image generation, particularly through methods that utilize one or multiple contr…
Do not Abstain! Identify and Solve the Uncertainty
Jingyu Liu, Jingquan Peng, xiaopeng Wu +4
Despite the widespread application of Large Language Models (LLMs) across various domains, they frequently exhibit overconfidence when encountering uncertain scenarios, yet existin…
Differentiable Solver Search for Fast Diffusion Sampling
Shuai Wang, Zexian Li, Qipeng zhang +5
Diffusion models have demonstrated remarkable generation quality but at the cost of numerous function evaluations. Recently, advanced ODE-based solvers have been developed to mitig…
DMM: Building a Versatile Image Generation Model via Distillation-Based Model Merging
Tianhui Song, Weixin Feng, Shuai Wang +4
The success of text-to-image (T2I) generation models has spurred a proliferation of numerous model checkpoints fine-tuned from the same base model on various specialized datasets.…
SceneBooth: Diffusion-based Framework for Subject-preserved Text-to-Image Generation
Shang Chai, Zihang Lin, Min Zhou +3
Due to the demand for personalizing image generation, subject-driven text-to-image generation method, which creates novel renditions of an input subject based on text prompts, has…
FlowDCN: Exploring DCN-like Architectures for Fast Image Generation with Arbitrary Resolution
Shuai Wang, Zexian Li, Tianhui Song +4
Arbitrary-resolution image generation still remains a challenging task in AIGC, as it requires handling varying resolutions and aspect ratios while maintaining high visual quality.…
Enhancing Prompt Following with Visual Control Through Training-Free Mask-Guided Diffusion
Hongyu Chen, Yiqi Gao, Min Zhou +4
Recently, integrating visual controls into text-to-image~(T2I) models, such as ControlNet method, has received significant attention for finer control capabilities. While various t…
RHanDS: Refining Malformed Hands for Generated Images with Decoupled Structure and Style Guidance
Chengrui Wang, Pengfei Liu, Min Zhou +4
Although diffusion models can generate high-quality human images, their applications are limited by the instability in generating hands with correct structures. In this paper, we i…
Accelerating Image Generation with Sub-path Linear Approximation Model
Chen Xu, Tianhui Song, Weixin Feng +4
Diffusion models have significantly advanced the state of the art in image, audio, and video generation tasks. However, their applications in practical scenarios are hindered by sl…