About Me

Hello! I am currently a Ph.D. student at Thrust of Artificial Intelligence at HKUST-GZ, under the supervision of Prof. Menglin Yang.

My research interests include Machine Learning (ML) and Deep Learning (DL), with a focus on:

• Large Language Models (LLMs)
  • LLM Agent, Multi-Agent
  • RAG, GraphRAG
  • LLM Implicit Reasoning
  • LLM Symbolic Reasoning
  • others
• Multimodal Learning (MM), Vision-Language model (VLM)
• Electronic Design Automation (EDA) (Seeking Collaborators)
• AI-Generated Content (AIGC)
• Geometric Learning with LLM, Geometric Foundation Model, Geometric Alignment
• Graph Learning (GNNs)
• Anomaly Detection (AD)
• Recommender System (RecSys)
• Domain Generalization (DG) and Domain Adaptation (DA)
• Unsupervised Learning, Few-Shot Learning
• Continual Learning (Incremental Learning)

INFORMATION

• E-mail: jli839@connect.hkust-gz.edu.cn
• WeChat: alwaysbeakindperson   (means: always be a kind person)
• Google Scholar: 174
• GitHub:

EDUCATION

Hong Kong University of Science and Technology (HKUST-GZ)

• Ph.D. in Artificial Intelligence
• Supervisor: Assistant Prof. Menglin Yang

National University of Defense Technology (NUDT)    985

• B.E. in Electronic Engineering
• Academic performance: rank 2/115
• B.E. in Commmand
• Academic performance: rank: 3/98
• (I have a valid passport and successfully traveled to Europe in 2023, with no issues obtaining a visa)

TECHNICAL ACCOUNTS

PAPERS

(*: co-first author, +: corresponding author)

Published

[1] CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-Level Anomaly Detection
Jindong Li, Qianli Xing, Qi Wang+, Yi Chang.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD, CCF-B), 2023.
arXiv | GitHub

[2] ScreenAgent: A Vision Language Model-driven Computer Control Agent
Runliang Niu, Jindong Li, Shiqi Wang, Yali Fu, Xiyu Hu, Xueyuan Leng, He Kong, Yi Chang, Qi Wang+.
International Joint Conference on Artificial Intelligence (IJCAI, CCF-A), 2024.
arXiv | GitHub | 机器之心

[3] LCD-Net: A Lightweight Remote Sensing Change Detection Network Combining Feature Fusion and Gating Mechanism
Wenyu Liu, Jindong Li, Haoji Wang, Run Tan, Yali Fu, Qichuan Tian+
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. (J-STAR, JCR Q1), 2025.
IEEE | GitHub

[4] GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space Model
Yali Fu*, Jindong Li*, Qi Wang+, Qianli Xing.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD, CCF-B), 2025.
arXiv | GitHub

[5] Beyond Retraining: Training-Free Unknown Class Filtering for Source-Free Open Set Domain Adaptation of Vision–Language Models.
Yongguang Li, Jindong Li, Qi Wang+, Qianli Xing, Runliang Niu, Shengsheng Wang, Menglin Yang.
Association for the Advancement of Artificial Intelligence Conference (AAAI, CCF-A), 2026.
arXiv

[6] A Survey on LLM Symbolic Reasoning.
Jindong Li*, Yali Fu*, Yang Yang, Jiahong Liu, Hongce Zhang, Haoxuan Li, Yutao Yue, Mengling Yang+.
AAAI Bridge: Logical and Symbolic Reasoning in Language Models, 2026.
GitHub

arXiv Preprint

[1] Discrete Tokenization for Multimodal LLMs: A Comprehensive Survey
Jindong Li*, Yali Fu*, Jiahong Liu, Linxiao Cao, Wei Ji, Menglin Yang+, Irwin King, Ming-Hsuan Yang.
arXiv Preprint, 2025.
arXiv | GitHub | 机器之心 |

[2] Implicit Reasoning in Large Language Models: A Comprehensive Survey
Jindong Li*, Yali Fu*, Li Fan, Jiahong Liu, Yao Shu, Chengwei Qin, Menglin Yang+, Irwin King, Rex Ying.
arXiv Preprint, 2025.
arXiv | GitHub | PaperWeekly |

[3] Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyond
Qi Wang*+, Jindong Li*, Shiqi Wang, Qianli Xing, Runliang Niu, He Kong, Rui Li, Guodong Long, Yi Chang, Chengqi Zhang.
arXiv Preprint, 2024.
arXiv | GitHub | 机器学习与推荐算法 |

[4] CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey
Jindong Li, Yongguang Li, Yali Fu, Jiahong Liu, Yixin Liu, Menglin Yang+, Irwin King.
arXiv Preprint, 2025.
arXiv | GitHub | 机器之心 |

[5] HyperbolicRAG: Enhancing Retrieval-Augmented Generation with Hyperbolic Representations
Linxiao Cao, Ruitao Wang, Jindong Li, Zhipeng Zhou, Menglin Yang+.
arXiv Preprint, 2025.
arXiv

[6] Cogito, ergo sum: A Neurobiologically-Inspired Cognition-Memory-Growth System for Code Generation
Yanlong Li, Jindong Li, Qi Wang+, Menglin Yang, He Kong, Shengsheng Wang.
arXiv Preprint, 2025.
arXiv | CODE | TechXplore

[7] No Fear of Representation Bias: Graph Contrastive Learning with Calibration and Fusion
Jindong Li, Yixin Liu, Qianli Xing, Qi Wang+.
SSRN Preprint, 2023.
SSRN | GitHub

[8] HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly Detection
Yali Fu*, Jindong Li*, Jiahong Liu, Qianli Xing, Qi Wang+, Irwin King.
arXiv Preprint, 2024.
arXiv | GitHub

[9] FANFOLD: Graph Normalization Flows-driven Asymmetric Network for Unsupervised Graph-Level Anomaly Detection
Rui Cao*, Shijie Xue*, Jindong Li*, Qianli Xing, Qi Wang+, Yi Chang.
arXiv Preprint, 2024.
arXiv | GitHub

[10] Data-Efficient CLIP-Powered Dual-Branch Networks for Source-Free Unsupervised Domain Adaptation
Yongguang Li*, Yueqi Cao*, Jindong Li, Qi Wang, Shengsheng Wang+.
arXiv Preprint, 2024.
arXiv | GitHub

[10] DIRP: Efficient Point Cloud Registration via Dynamic Iteration
Yang Ai, Jindong Li, Qiang Bai, Xi Yang+.
arXiv Preprint, 2023.
arXiv | GitHub

Academic Service

• Reviewer, International World Wide Web Conference (WWW)
• Reviewer, International Conference on Computer Vision (ICCV)
• Reviewer, Artificial Intelligence Journal (AIJ)
• Reviewer, International Conference on Learning Representations (ICLR)

WORK EXPERIENCE

1. Shanghai Artificial Intelligence Laboratory (Shanghai AI Lab)        2023.09-2023.12

• Research Intern
• Mentor: Bin Wang and Linke Ouyang
• Topic: Multimodal Large Language Models (MLLMs), Data Engine
• Responsibilities:
  • Evaluation of MLLMs
  • Multimodal (OCR mainly) models/approaches

COMPETITION EXPERIENCE

HONORS AND AWARDS

SKILLS

• Language: IELTS Overall Band Score 6.5 (Listening: 6.0, Reading: 7.0, Writing: 6.0, Speaking: 6.5)     2023.11
• Programming Languages: Proficient in Python, C++, Java. Also experienced with C, Go, MySQL.
• Deep Learning Tools: PyTorch, TensorFlow