Search Results for author: Mingyu Jin

Found 20 papers, 9 papers with code

MoralBench: Moral Evaluation of LLMs

1 code implementation6 Jun 2024 Jianchao Ji, Yutong Chen, Mingyu Jin, Wujiang Xu, Wenyue Hua, Yongfeng Zhang

In the rapidly evolving field of artificial intelligence, large language models (LLMs) have emerged as powerful tools for a myriad of applications, from natural language processing to decision-making support systems.


BattleAgent: Multi-modal Dynamic Emulation on Historical Battles to Complement Historical Analysis

1 code implementation23 Apr 2024 Shuhang Lin, Wenyue Hua, Lingyao Li, Che-Jui Chang, Lizhou Fan, Jianchao Ji, Hang Hua, Mingyu Jin, Jiebo Luo, Yongfeng Zhang

This novel system aims to simulate complex dynamic interactions among multiple agents, as well as between agents and their environments, over a period of time.

Decision Making Language Modelling

Exploring Concept Depth: How Large Language Models Acquire Knowledge at Different Layers?

1 code implementation10 Apr 2024 Mingyu Jin, Qinkai Yu, Jingyuan Huang, Qingcheng Zeng, Zhenting Wang, Wenyue Hua, Haiyan Zhao, Kai Mei, Yanda Meng, Kaize Ding, Fan Yang, Mengnan Du, Yongfeng Zhang

In this paper, we explore the hypothesis that LLMs process concepts of varying complexities in different layers, introducing the idea of "Concept Depth" to suggest that more complex concepts are typically acquired in deeper layers.

Goal-guided Generative Prompt Injection Attack on Large Language Models

no code implementations6 Apr 2024 Chong Zhang, Mingyu Jin, Qinkai Yu, Chengzhi Liu, Haochen Xue, Xiaobo Jin

Although there is currently a large amount of research on prompt injection attacks, most of these black-box attacks use heuristic strategies.

Adversarial Text

ProLLM: Protein Chain-of-Thoughts Enhanced LLM for Protein-Protein Interaction Prediction

1 code implementation30 Mar 2024 Mingyu Jin, Haochen Xue, Zhenting Wang, Boming Kang, Ruosong Ye, Kaixiong Zhou, Mengnan Du, Yongfeng Zhang

Specifically, we propose Protein Chain of Thought (ProCoT), which replicates the biological mechanism of signaling pathways as natural language prompts.

Large Language Models in Biomedical and Health Informatics: A Bibliometric Review

no code implementations24 Mar 2024 Huizi Yu, Lizhou Fan, Lingyao Li, Jiayan Zhou, Zihui Ma, Lu Xian, Wenyue Hua, Sijia He, Mingyu Jin, Yongfeng Zhang, Ashvin Gandhi, Xin Ma

Large Language Models (LLMs) have rapidly become important tools in Biomedical and Health Informatics (BHI), enabling new ways to analyze data, treat patients, and conduct research.

Management Medical Diagnosis

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

What if LLMs Have Different World Views: Simulating Alien Civilizations with LLM-based Agents

no code implementations20 Feb 2024 Mingyu Jin, Beichen Wang, Zhaoqian Xue, Suiyuan Zhu, Wenyue Hua, Hua Tang, Kai Mei, Mengnan Du, Yongfeng Zhang

In this study, we introduce "CosmoAgent," an innovative artificial intelligence framework utilizing Large Language Models (LLMs) to simulate complex interactions between human and extraterrestrial civilizations, with a special emphasis on Stephen Hawking's cautionary advice about not sending radio signals haphazardly into the universe.

Decision Making

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

1 code implementation10 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.

MathAttack: Attacking Large Language Models Towards Math Solving Ability

no code implementations4 Sep 2023 ZiHao Zhou, Qiufeng Wang, Mingyu Jin, Jie Yao, Jianan Ye, Wei Liu, Wei Wang, Xiaowei Huang, Kaizhu Huang

Instead of attacking prompts in the use of LLMs, we propose a MathAttack model to attack MWP samples which are closer to the essence of security in solving math problems.

Adversarial Attack GSM8K +1

Bridging the Projection Gap: Overcoming Projection Bias Through Parameterized Distance Learning

no code implementations4 Sep 2023 Chong Zhang, Mingyu Jin, Qinkai Yu, Haochen Xue, Shreyank N Gowda, Xiaobo Jin

Generalized zero-shot learning (GZSL) aims to recognize samples from both seen and unseen classes using only seen class samples for training.

Generalized Zero-Shot Learning Metric Learning

A Simple and Effective Baseline for Attentional Generative Adversarial Networks

1 code implementation26 Jun 2023 Mingyu Jin, Chong Zhang, Qinkai Yu, Haochen Xue, Xiaobo Jin, Xi Yang

Synthesising a text-to-image model of high-quality images by guiding the generative model through the Text description is an innovative and challenging task.

Image Generation

Image Blending Algorithm with Automatic Mask Generation

no code implementations8 Jun 2023 Haochen Xue, Mingyu Jin, Chong Zhang, Yuxuan Huang, Qian Weng, Xiaobo Jin

In recent years, image blending has gained popularity for its ability to create visually stunning content.

object-detection Object Detection +1

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