14 citations · 23 across the 15 of their papers we have counts for
9 papers · 1 filter
Harnessing Task Overload for Scalable Jailbreak Attacks on Large Language Models
Yiting Dong, Guobin Shen, Dongcheng Zhao +2
Large Language Models (LLMs) remain vulnerable to jailbreak attacks that bypass their safety mechanisms. Existing attack methods are fixed or specifically tailored for certain mode…
Jailbreak Antidote: Runtime Safety-Utility Balance via Sparse Representation Adjustment in Large Language Models
Guobin Shen, Dongcheng Zhao, Yiting Dong +2
As large language models (LLMs) become integral to various applications, ensuring both their safety and utility is paramount. Jailbreak attacks, which manipulate LLMs into generati…
StressPrompt: Does Stress Impact Large Language Models and Human Performance Similarly?
Guobin Shen, Dongcheng Zhao, Aorigele Bao +3
Human beings often experience stress, which can significantly influence their performance. This study explores whether Large Language Models (LLMs) exhibit stress responses similar…
Brain-Inspired Stepwise Patch Merging for Vision Transformers
Yonghao Yu, Dongcheng Zhao, Guobin Shen +2
The hierarchical architecture has become a mainstream design paradigm for Vision Transformers (ViTs), with Patch Merging serving as the pivotal component that transforms a columnar…
Time Cell Inspired Temporal Codebook in Spiking Neural Networks for Enhanced Image Generation
Linghao Feng, Dongcheng Zhao, Sicheng Shen +3
This paper presents a novel approach leveraging Spiking Neural Networks (SNNs) to construct a Variational Quantized Autoencoder (VQ-VAE) with a temporal codebook inspired by hippoc…
EventZoom: A Progressive Approach to Event-Based Data Augmentation for Enhanced Neuromorphic Vision
Yiting Dong, Xiang He, Guobin Shen +3
Dynamic Vision Sensors (DVS) capture event data with high temporal resolution and low power consumption, presenting a more efficient solution for visual processing in dynamic and r…
Neuro-Vision to Language: Enhancing Brain Recording-based Visual Reconstruction and Language Interaction
Guobin Shen, Dongcheng Zhao, Xiang He +5
Decoding non-invasive brain recordings is pivotal for advancing our understanding of human cognition but faces challenges due to individual differences and complex neural signal re…
Brain-inspired and Self-based Artificial Intelligence
Yi Zeng, Feifei Zhao, Yuxuan Zhao +17
The question "Can machines think?" and the Turing Test to assess whether machines could achieve human-level intelligence is one of the roots of AI. With the philosophical argument…
Parallel Spiking Unit for Efficient Training of Spiking Neural Networks
Yang Li, Yinqian Sun, Xiang He +3
Efficient parallel computing has become a pivotal element in advancing artificial intelligence. Yet, the deployment of Spiking Neural Networks (SNNs) in this domain is hampered by…