33 citations · 36 across the 19 of their papers we have counts for
8 papers · 1 filter
Zer0-Jack: A Memory-efficient Gradient-based Jailbreaking Method for Black-box Multi-modal Large Language Models
Tiejin Chen, Kaishen Wang, Hua Wei
Jailbreaking methods, which induce Multi-modal Large Language Models (MLLMs) to output harmful responses, raise significant safety concerns. Among these methods, gradient-based app…
SynTraC: A Synthetic Dataset for Traffic Signal Control from Traffic Monitoring Cameras
Tiejin Chen, Prithvi Shirke, Bharatesh Chakravarthi +5
This paper introduces SynTraC, the first public image-based traffic signal control dataset, aimed at bridging the gap between simulated environments and real-world traffic manageme…
LLM Uncertainty Quantification through Directional Entailment Graph and Claim Level Response Augmentation
Longchao Da, Tiejin Chen, Lu Cheng +1
The Large language models (LLMs) have showcased superior capabilities in sophisticated tasks across various domains, stemming from basic question-answer (QA), they are nowadays use…
Privacy-preserving Fine-tuning of Large Language Models through Flatness
Tiejin Chen, Longchao Da, Huixue Zhou +4
The privacy concerns associated with the use of Large Language Models (LLMs) have grown recently with the development of LLMs such as ChatGPT. Differential Privacy (DP) techniques…
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape
Tiejin Chen, Wenwang Huang, Linsey Pang +2
This paper delves into the critical area of deep learning robustness, challenging the conventional belief that classification robustness and explanation robustness in image classif…
When eBPF Meets Machine Learning: On-the-fly OS Kernel Compartmentalization
Zicheng Wang, Tiejin Chen, Qinrun Dai +3
Compartmentalization effectively prevents initial corruption from turning into a successful attack. This paper presents O2C, a pioneering system designed to enforce OS kernel compa…
Uncertainty Regularized Evidential Regression
Kai Ye, Tiejin Chen, Hua Wei +1
The Evidential Regression Network (ERN) represents a novel approach that integrates deep learning with Dempster-Shafer's theory to predict a target and quantify the associated unce…
Open-TI: Open Traffic Intelligence with Augmented Language Model
Longchao Da, Kuanru Liou, Tiejin Chen +4
Transportation has greatly benefited the cities' development in the modern civilization process. Intelligent transportation, leveraging advanced computer algorithms, could further…