Hierarchical Graph Matching Networks for Deep Graph Similarity Learning. - Xiang Ling 001; Lingfei Wu 001; Saizhuo Wang; Tengfei Ma 001; Fangli Xu; Alex X. Liu; Chunming Wu 001; Shouling Ji (CoRR, 2020)

Deep Graph Matching and Searching for Semantic Code Retrieval. - Xiang Ling 001; Lingfei Wu 001; Saizhuo Wang; Gaoning Pan; Tengfei Ma 001; Fangli Xu; Alex X. Liu; Chunming Wu 001; Shouling Ji (ACM Trans. Knowl. Discov. Data, 2021)

Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings. - Yuhao Mao; Chong Fu 002; Saizhuo Wang; Shouling Ji; Xuhong Zhang 002; Zhenguang Liu; Jun Zhou 011; Alex X. Liu; Raheem Beyah; Ting Wang 006 (SP, 2022)

Think-on-Graph: Deep and Responsible Reasoning of Large Language Model with Knowledge Graph. - Jiashuo Sun; Chengjin Xu; Lumingyuan Tang; Saizhuo Wang; Chen Lin 001; Yeyun Gong; Heung-Yeung Shum; Jian Guo (CoRR, 2023)

Alpha-GPT: Human-AI Interactive Alpha Mining for Quantitative Investment. - Saizhuo Wang; Hang Yuan; Leon Zhou; Lionel M. Ni; Heung-Yeung Shum; Jian Guo (CoRR, 2023)

On the Evolution of Knowledge Graphs: A Survey and Perspective. - Xuhui Jiang; Chengjin Xu; Yinghan Shen; Xun Sun; Lumingyuan Tang; Saizhuo Wang; Zhongwu Chen; Yuanzhuo Wang; Jian Guo (CoRR, 2023)

A Principled Framework for Knowledge-enhanced Large Language Model. - Saizhuo Wang; Zhihan Liu; Zhaoran Wang 001; Jian Guo (CoRR, 2023)

Multilevel Graph Matching Networks for Deep Graph Similarity Learning. - Xiang Ling 001; Lingfei Wu 001; Saizhuo Wang; Tengfei Ma 001; Fangli Xu; Alex X. Liu; Chunming Wu 001; Shouling Ji (IEEE Trans. Neural Networks Learn. Syst., 2023)

Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph. - Jiashuo Sun; Chengjin Xu; Lumingyuan Tang; Saizhuo Wang; Chen Lin 001; Yeyun Gong; Lionel M. Ni; Heung-Yeung Shum; Jian Guo (ICLR, 2024)

QuantAgent: Seeking Holy Grail in Trading by Self-Improving Large Language Model. - Saizhuo Wang; Hang Yuan; Lionel M. Ni; Jian Guo (CoRR, 2024)

Alpha-GPT 2.0: Human-in-the-Loop AI for Quantitative Investment. - Hang Yuan; Saizhuo Wang; Jian Guo (CoRR, 2024)

Golden Touchstone: A Comprehensive Bilingual Benchmark for Evaluating Financial Large Language Models. - Xiaojun Wu; Junxi Liu; Huanyi Su; Zhouchi Lin; Yiyan Qi; Chengjin Xu; Jiajun Su; Jiajie Zhong; Fuwei Wang; Saizhuo Wang; Fengrui Hua; Jia Li; et al. (CoRR, 2024)

Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making. - Jian Guo; Saizhuo Wang; Yiyan Qi (CoRR, 2024)

Quant 4.0: engineering quantitative investment with automated, explainable, and knowledge-driven artificial intelligence. - Jian Guo; Saizhuo Wang; Lionel M. Ni; Heung-Yeung Shum (Frontiers Inf. Technol. Electron. Eng., 2024)

I2HGNN: Iterative Interpretable HyperGraph Neural Network for semi-supervised classification. - Hongwei Zhang; Saizhuo Wang; Zixin Hu; Yuan Qi; Zengfeng Huang; Jian Guo (Neural Networks, 2025)

From Deep Learning to LLMs: A survey of AI in Quantitative Investment. - Bokai Cao; Saizhuo Wang; Xinyi Lin; Xiaojun Wu; Haohan Zhang; Lionel M. Ni; Jian Guo (CoRR, 2025)

Unleashing Expert Opinion from Social Media for Stock Prediction. - Wanyun Zhou; Saizhuo Wang; Xiang Li; Yiyan Qi; Jian Guo; Xiaowen Chu 001 (CoRR, 2025)

QuantBench: Benchmarking AI Methods for Quantitative Investment. - Saizhuo Wang; Hao Kong; Jiadong Guo; Fengrui Hua; Yiyan Qi; Wanyun Zhou; Jiahao Zheng 009; Xinyu Wang; Lionel M. Ni; Jian Guo (CoRR, 2025)