11 citations · 27 across the 16 of their papers we have counts for
8 papers · 1 filter
Counterfactual Explainable Incremental Prompt Attack Analysis on Large Language Models
Dong Shu, Mingyu Jin, Tianle Chen +2
This study sheds light on the imperative need to bolster safety and privacy measures in large language models (LLMs), such as GPT-4 and LLaMA-2, by identifying and mitigating their…
When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments
Chong Zhang, Xinyi Liu, Zhongmou Zhang +10
Can AI Agents simulate real-world trading environments to investigate the impact of external factors on stock trading activities (e.g., macroeconomics, policy changes, company fund…
Better Sampling, towards Better End-to-end Small Object Detection
Zile Huang, Chong Zhang, Mingyu Jin +3
While deep learning-based general object detection has made significant strides in recent years, the effectiveness and efficiency of small object detection remain unsatisfactory. T…
Goal-guided Generative Prompt Injection Attack on Large Language Models
Chong Zhang, Mingyu Jin, Qinkai Yu +3
Current large language models (LLMs) provide a strong foundation for large-scale user-oriented natural language tasks. A large number of users can easily inject adversarial text or…
Knowledge Graph Large Language Model (KG-LLM) for Link Prediction
Dong Shu, Tianle Chen, Mingyu Jin +3
The task of multi-hop link prediction within knowledge graphs (KGs) stands as a challenge in the field of knowledge graph analysis, as it requires the model to reason through and u…
Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities
Hua Tang, Chong Zhang, Mingyu Jin +5
Large language models (LLMs) have been applied in many fields and have developed rapidly in recent years. As a classic machine learning task, time series forecasting has recently b…
Health-LLM: Personalized Retrieval-Augmented Disease Prediction System
Qinkai Yu, Mingyu Jin, Dong Shu +8
Recent advancements in artificial intelligence (AI), especially large language models (LLMs), have significantly advanced healthcare applications and demonstrated potentials in int…
AttackEval: How to Evaluate the Effectiveness of Jailbreak Attacking on Large Language Models
Dong Shu, Chong Zhang, Mingyu Jin +3
Jailbreak attacks represent one of the most sophisticated threats to the security of large language models (LLMs). To deal with such risks, we introduce an innovative framework tha…