3 citations · 3 across the 9 of their papers we have counts for
9 papers
IFPV: An Integrated Multi-Agent Framework for Generative Operational Planning and High-Fidelity Plan Verification
Zhigao Huang, Zhengqing Hu, Dong Chen +5
Operational plan generation and verification are critical for modern complex and rapidly changing battlefield environments, yet traditional generation and verification methods stil…
What Will Happen Next: Large Models-Driven Deduction for Emergency Instances
Zhengqing Hu, Dong Chen, Junkun Yuan +6
Traditional simulation methods reproduce occurred emergency instances through presetting to assist people in risk assessment and emergency decision-making. However, due to the lack…
GraSP: Graph-Structured Skill Compositions for LLM Agents
Tianle Xia, Lingxiang Hu, Yiding Sun +5
Skill ecosystems for LLM agents have matured rapidly, yet recent benchmarks show that providing agents with more skills does not monotonically improve performance -- focused sets o…
MAFIG: Multi-agent Driven Formal Instruction Generation Framework
Shixing Zhao, Zheng Si, Pengpeng Ouyang +5
Emergency situations in scheduling systems often trigger local functional failures that undermine system stability and even cause system collapse. Existing methods primarily rely o…
Semantic Encryption: Secure and Effective Interaction with Cloud-based Large Language Models via Semantic Transformation
Dong Chen, Tong Yang, Feipeng Zhai +5
The increasing adoption of Cloud-based Large Language Models (CLLMs) has raised significant concerns regarding data privacy during user interactions. While existing approaches prim…
FAF: A Feature-Adaptive Framework for Few-Shot Time Series Forecasting
Pengpeng Ouyang, Dong Chen, Tong Yang +3
Multi-task and few-shot time series forecasting tasks are commonly encountered in scenarios such as the launch of new products in different cities. However, traditional time series…
KKA: Improving Vision Anomaly Detection through Anomaly-related Knowledge from Large Language Models
Dong Chen, Zhengqing Hu, Peiguang Fan +5
Vision anomaly detection, particularly in unsupervised settings, often struggles to distinguish between normal samples and anomalies due to the wide variability in anomalies. Recen…
Logic Distillation: Learning from Code Function by Function for Decision-making Tasks
Dong Chen, Shilin Zhang, Fei Gao +4
Large language models (LLMs) have garnered increasing attention owing to their powerful logical reasoning capabilities. Generally, larger LLMs (L-LLMs) that require paid interfaces…
Improving Large Models with Small models: Lower Costs and Better Performance
Dong Chen, Shuo Zhang, Yueting Zhuang +4
Pretrained large models (PLMs), such as ChatGPT, have demonstrated remarkable performance across diverse tasks. However, the significant computational requirements of PLMs have dis…