9 citations · 11 across the 6 of their papers we have counts for
6 papers
Safety Does Not Compose: Non-Decaying Loop State for Autonomous LLM Agents
Chenhao Wu, Haoxuan Jia, Yang Liu +11
Large language model agents are increasingly deployed as autonomous loops. Starting from one human goal, such a system repeatedly discovers work, plans, executes tool calls, verifi…
Dream.exe: Can Video Generation Models Dream Executable Robot Manipulation?
Rui Zhao, Kaiming Yang, Jifeng Zhu +6
Video generation models have made impressive strides in synthesizing visually compelling content, yet their outputs remain confined to the virtual domain. A natural question follow…
JoyAI-LLM Flash: Advancing Mid-Scale LLMs with Token Efficiency
Aichen Cai, Anmeng Zhang, Anyu Li +66
We introduce JoyAI-LLM Flash, an efficient Mixture-of-Experts (MoE) language model designed to redefine the trade-off between strong performance and token efficiency in the sub-50B…
Disappeared Command: Spoofing Attack On Automatic Speech Recognition Systems with Sound Masking
Jinghui Xu, Jifeng Zhu, Yong Yang
The development of deep learning technology has greatly promoted the performance improvement of automatic speech recognition (ASR) technology, which has demonstrated an ability com…
Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks
Xiangyu Qi, Tinghao Xie, Ruizhe Pan +3
One major goal of the AI security community is to securely and reliably produce and deploy deep learning models for real-world applications. To this end, data poisoning based backd…
Subnet Replacement: Deployment-stage backdoor attack against deep neural networks in gray-box setting
Xiangyu Qi, Jifeng Zhu, Chulin Xie +1
We study the realistic potential of conducting backdoor attack against deep neural networks (DNNs) during deployment stage. Specifically, our goal is to design a deployment-stage b…