Search Results for author: Dong Shu

Found 6 papers, 2 papers with code

Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI

no code implementations14 Mar 2024 Dong Shu, Zhouyao Zhu

This report investigates the history and impact of Generative Models and Connected and Automated Vehicles (CAVs), two groundbreaking forces pushing progress in technology and transportation.

Autonomous Vehicles Decision Making

Knowledge Graph Large Language Model (KG-LLM) for Link Prediction

no code implementations12 Mar 2024 Dong Shu, Tianle Chen, Mingyu Jin, Yiting Zhang, Chong Zhang, Mengnan Du, Yongfeng Zhang

The task of predicting multiple links within knowledge graphs (KGs) stands as a challenge in the field of knowledge graph analysis, a challenge increasingly resolvable due to advancements in natural language processing (NLP) and KG embedding techniques.

In-Context Learning Knowledge Graphs +2

Health-LLM: Personalized Retrieval-Augmented Disease Prediction System

no code implementations1 Feb 2024 Mingyu Jin, Qinkai Yu, Dong Shu, Chong Zhang, Lizhou Fan, Wenyue Hua, Suiyuan Zhu, Yanda Meng, Zhenting Wang, Mengnan Du, Yongfeng Zhang

Compared to traditional health management applications, our system has three main advantages: (1) It integrates health reports and medical knowledge into a large model to ask relevant questions to large language model for disease prediction; (2) It leverages a retrieval augmented generation (RAG) mechanism to enhance feature extraction; (3) It incorporates a semi-automated feature updating framework that can merge and delete features to improve accuracy of disease prediction.

Disease Prediction Language Modelling +3

AttackEval: How to Evaluate the Effectiveness of Jailbreak Attacking on Large Language Models

no code implementations17 Jan 2024 Dong Shu, Mingyu Jin, Suiyuan Zhu, Beichen Wang, ZiHao Zhou, Chong Zhang, Yongfeng Zhang

In our research, we pioneer a novel approach to evaluate the effectiveness of jailbreak attacks on Large Language Models (LLMs), such as GPT-4 and LLaMa2, diverging from traditional robustness-focused binary evaluations.

The Impact of Reasoning Step Length on Large Language Models

2 code implementations10 Jan 2024 Mingyu Jin, Qinkai Yu, Dong Shu, Haiyan Zhao, Wenyue Hua, Yanda Meng, Yongfeng Zhang, Mengnan Du

Alternatively, shortening the reasoning steps, even while preserving the key information, significantly diminishes the reasoning abilities of models.

Assessing Prompt Injection Risks in 200+ Custom GPTs

1 code implementation20 Nov 2023 Jiahao Yu, Yuhang Wu, Dong Shu, Mingyu Jin, Sabrina Yang, Xinyu Xing

In the rapidly evolving landscape of artificial intelligence, ChatGPT has been widely used in various applications.

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