1 citations · 1 across the 11 of their papers we have counts for
11 papers
ARM: Attention with Routed-Memory for Learnable Sparse Control
Qiuhao Zeng, Jerry Huang, Peng Lu +7
Despite advances in long-context inference, large language models (LLMs) remain fundamentally limited by the key-value (KV) caching mechanisms that are necessary for stable computa…
Full spectrum Unlearnable Examples via Spectral Equalization
Jiale Cai, Gezheng Xu, Zhihao Li +6
Unlearnable examples (UEs) protect training data by injecting imperceptible perturbations so that models fail to extract exploitable representations. In this paper, we reveal that…
When Priors Backfire: On the Vulnerability of Unlearnable Examples to Pretraining
Zhihao Li, Gezheng Xu, Jiale Cai +5
Unlearnable Examples (UEs) serve as a data protection strategy that generates imperceptible perturbations to mislead models into learning spurious correlations instead of underlyin…
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…
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…
Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced Regression
Ruizhi Pu, Gezheng Xu, Ruiyi Fang +3
Deep imbalanced regression (DIR), where the target values have a highly skewed distribution and are also continuous, is an intriguing yet under-explored problem in machine learning…
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…
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…