12 citations · 44 across the 15 of their papers we have counts for
15 papers
Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs
Yiwei Chen, Soumyadeep Pal, Yimeng Zhang +2
Machine unlearning (MU) for large language models (LLMs), commonly referred to as LLM unlearning, seeks to remove specific undesirable data or knowledge from a trained model, while…
Factorization of multimeters: a unified view on nonclassical quantum phenomena
Tim Achenbach, Andreas Bluhm, Leevi Leppäjärvi +2
Quantum theory exhibits various nonclassical features, such as measurement incompatibility, contextuality, steering, and Bell nonlocality, which distinguish it from classical physi…
ID-Patch: Robust ID Association for Group Photo Personalization
Yimeng Zhang, Tiancheng Zhi, Jing Liu +5
The ability to synthesize personalized group photos and specify the positions of each identity offers immense creative potential. While such imagery can be visually appealing, it p…
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
Yimeng Zhang, Xin Chen, Jinghan Jia +6
Diffusion models (DMs) have achieved remarkable success in text-to-image generation, but they also pose safety risks, such as the potential generation of harmful content and copyri…
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning
Jinghan Jia, Yihua Zhang, Yimeng Zhang +5
Large Language Models (LLMs) have highlighted the necessity of effective unlearning mechanisms to comply with data regulations and ethical AI practices. LLM unlearning aims at remo…
The Power of Few: Accelerating and Enhancing Data Reweighting with Coreset Selection
Mohammad Jafari, Yimeng Zhang, Yihua Zhang +1
As machine learning tasks continue to evolve, the trend has been to gather larger datasets and train increasingly larger models. While this has led to advancements in accuracy, it…
UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models
Yihua Zhang, Chongyu Fan, Yimeng Zhang +8
The technological advancements in diffusion models (DMs) have demonstrated unprecedented capabilities in text-to-image generation and are widely used in diverse applications. Howev…
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark
Yihua Zhang, Pingzhi Li, Junyuan Hong +10
In the evolving landscape of natural language processing (NLP), fine-tuning pre-trained Large Language Models (LLMs) with first-order (FO) optimizers like SGD and Adam has become s…
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning
Yihua Zhang, Yimeng Zhang, Aochuan Chen +6
Massive data is often considered essential for deep learning applications, but it also incurs significant computational and infrastructural costs. Therefore, dataset pruning (DP) h…
To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now
Yimeng Zhang, Jinghan Jia, Xin Chen +5
The recent advances in diffusion models (DMs) have revolutionized the generation of realistic and complex images. However, these models also introduce potential safety hazards, suc…
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training
Aochuan Chen, Yimeng Zhang, Jinghan Jia +7
Zeroth-order (ZO) optimization has become a popular technique for solving machine learning (ML) problems when first-order (FO) information is difficult or impossible to obtain. How…
Text-Visual Prompting for Efficient 2D Temporal Video Grounding
Yimeng Zhang, Xin Chen, Jinghan Jia +2
In this paper, we study the problem of temporal video grounding (TVG), which aims to predict the starting/ending time points of moments described by a text sentence within a long u…
On the Robustness of deep learning-based MRI Reconstruction to image transformations
Jinghan Jia, Mingyi Hong, Yimeng Zhang +2
Although deep learning (DL) has received much attention in accelerated magnetic resonance imaging (MRI), recent studies show that tiny input perturbations may lead to instabilities…
Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices
Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu +6
In this paper, we propose a data-model-hardware tri-design framework for high-throughput, low-cost, and high-accuracy multi-object tracking (MOT) on High-Definition (HD) video stre…
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective
Yimeng Zhang, Yuguang Yao, Jinghan Jia +4
The lack of adversarial robustness has been recognized as an important issue for state-of-the-art machine learning (ML) models, e.g., deep neural networks (DNNs). Thereby, robustif…