40 citations · 71 across the 8 of their papers we have counts for
9 papers
Target-driven Attack for Large Language Models
Chong Zhang, Mingyu Jin, Dong Shu +3
Current large language models (LLM) provide a strong foundation for large-scale user-oriented natural language tasks. Many users can easily inject adversarial text or instructions…
LawLLM: Law Large Language Model for the US Legal System
Dong Shu, Haoran Zhao, Xukun Liu +3
In the rapidly evolving field of legal analytics, finding relevant cases and accurately predicting judicial outcomes are challenging because of the complexity of legal language, wh…
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…
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…
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…
The Impact of Reasoning Step Length on Large Language Models
Mingyu Jin, Qinkai Yu, Dong Shu +5
Chain of Thought (CoT) is significant in improving the reasoning abilities of large language models (LLMs). However, the correlation between the effectiveness of CoT and the length…
Assessing Prompt Injection Risks in 200+ Custom GPTs
Jiahao Yu, Yuhang Wu, Dong Shu +3
In the rapidly evolving landscape of artificial intelligence, ChatGPT has been widely used in various applications. The new feature - customization of ChatGPT models by users to ca…