6 citations · 12 across the 8 of their papers we have counts for
8 papers
HarnessSafe: Evaluating Safety Across Persistent Carriers in Agent Harnesses
Xiao Zhang, Yusheng Wang, Yuhao Fei +5
Modern agent harnesses persist state across tasks and sessions through persistent carriers like memory, skills, tools, and shared artifacts. However, this capability creates delaye…
Never compromise with vulnerabilities: a comprehensive survey on AI governance
Yuchu Jiang, Jian Zhao, Yuchen Yuan +62
The rapid advancement of AI has expanded its capabilities across domains, yet introduced critical technical vulnerabilities, such as algorithmic bias and adversarial sensitivity, t…
Dynamic Generation of Personalities with Large Language Models
Jianzhi Liu, Hexiang Gu, Tianyu Zheng +4
In the realm of mimicking human deliberation, large language models (LLMs) show promising performance, thereby amplifying the importance of this research area. Deliberation is infl…
MORE-3S:Multimodal-based Offline Reinforcement Learning with Shared Semantic Spaces
Tianyu Zheng, Ge Zhang, Xingwei Qu +3
Drawing upon the intuition that aligning different modalities to the same semantic embedding space would allow models to understand states and actions more easily, we propose a new…
HyperMoE: Towards Better Mixture of Experts via Transferring Among Experts
Hao Zhao, Zihan Qiu, Huijia Wu +3
The Mixture of Experts (MoE) for language models has been proven effective in augmenting the capacity of models by dynamically routing each input token to a specific subset of expe…
Read to Play (R2-Play): Decision Transformer with Multimodal Game Instruction
Yonggang Jin, Ge Zhang, Hao Zhao +7
Developing a generalist agent is a longstanding objective in artificial intelligence. Previous efforts utilizing extensive offline datasets from various tasks demonstrate remarkabl…
JARVIS-1: Open-World Multi-task Agents with Memory-Augmented Multimodal Language Models
Zihao Wang, Shaofei Cai, Anji Liu +9
Achieving human-like planning and control with multimodal observations in an open world is a key milestone for more functional generalist agents. Existing approaches can handle cer…
Prototype-based HyperAdapter for Sample-Efficient Multi-task Tuning
Hao Zhao, Jie Fu, Zhaofeng He
Parameter-efficient fine-tuning (PEFT) has shown its effectiveness in adapting the pre-trained language models to downstream tasks while only updating a small number of parameters.…