1 citations · 1 across the 10 of their papers we have counts for
10 papers
Towards Generalized Multi-Image Editing for Unified Multimodal Models
Pengcheng Xu, Peng Tang, Donghao Luo +7
Unified Multimodal Models (UMMs) integrate multimodal understanding and generation, yet they are limited to maintaining visual consistency and disambiguating visual cues when refer…
Event-Driven Online Vertical Federated Learning
Ganyu Wang, Boyu Wang, Bin Gu +1
Online learning is more adaptable to real-world scenarios in Vertical Federated Learning (VFL) compared to offline learning. However, integrating online learning into VFL presents…
Homophily Enhanced Graph Domain Adaptation
Ruiyi Fang, Bingheng Li, Jingyu Zhao +5
Graph Domain Adaptation (GDA) transfers knowledge from labeled source graphs to unlabeled target graphs, addressing the challenge of label scarcity. In this paper, we highlight the…
Textualize Visual Prompt for Image Editing via Diffusion Bridge
Pengcheng Xu, Qingnan Fan, Fei Kou +5
Visual prompt, a pair of before-and-after edited images, can convey indescribable imagery transformations and prosper in image editing. However, current visual prompt methods rely…
Enhancing Generalization in Chain of Thought Reasoning for Smaller Models
Maxwell J. Yin, Dingyi Jiang, Yongbing Chen +2
Chain-of-Thought (CoT) reasoning in smaller language models is a challenging natural language process problem yet highly desirable in many real-life applications. Existing CoT know…
ZETA: Leveraging Z-order Curves for Efficient Top-k Attention
Qiuhao Zeng, Jerry Huang, Peng Lu +4
Over recent years, the Transformer has become a fundamental building block for sequence modeling architectures. Yet at its core is the use of self-attention, whose memory and compu…
Unveil Inversion and Invariance in Flow Transformer for Versatile Image Editing
Pengcheng Xu, Boyuan Jiang, Xiaobin Hu +7
Leveraging the large generative prior of the flow transformer for tuning-free image editing requires authentic inversion to project the image into the model's domain and a flexible…
MABR: Multilayer Adversarial Bias Removal Without Prior Bias Knowledge
Maxwell J. Yin, Boyu Wang, Charles Ling
Models trained on real-world data often mirror and exacerbate existing social biases. Traditional methods for mitigating these biases typically require prior knowledge of the speci…
Intersectional Unfairness Discovery
Gezheng Xu, Qi Chen, Charles Ling +2
AI systems have been shown to produce unfair results for certain subgroups of population, highlighting the need to understand bias on certain sensitive attributes. Current research…
Toward Open-ended Embodied Tasks Solving
William Wei Wang, Dongqi Han, Xufang Luo +4
Empowering embodied agents, such as robots, with Artificial Intelligence (AI) has become increasingly important in recent years. A major challenge is task open-endedness. In practi…