Inferring Human Feelings and Desires for Human-Robot Trust Promotion. - Xingzhi Guo; Yu-Cian Huang; Edwinn Gamborino; Shih-Huan Tseng; Li-Chen Fu; Su-Ling Yeh (HCI (11), 2019)

Improving Device Directedness Classification of Utterances With Semantic Lexical Features. - Kellen Gillespie; Ioannis C. Konstantakopoulos; Xingzhi Guo; Vishal Thanvantri Vasudevan; Abhinav Sethy (ICASSP, 2020)

COMET: Convolutional Dimension Interaction for Deep Matrix Factorization. - Zhuoyi Lin; Lei Feng 006; Xingzhi Guo; Rui Yin 002; Chee Keong Kwoh 001; Chi Xu (CoRR, 2020)

Subset Node Representation Learning over Large Dynamic Graphs. - Xingzhi Guo; Baojian Zhou; Steven Skiena (KDD, 2021)

Low-dimensional genotype embeddings for predictive models. - Syed Fahad Sultan; Xingzhi Guo; Steven Skiena (BCB, 2022)

Subset Node Anomaly Tracking over Large Dynamic Graphs. - Xingzhi Guo; Baojian Zhou; Steven Skiena (KDD, 2022)

Verba Volant, Scripta Volant: Understanding Post-publication Title Changes in News Outlets. - Xingzhi Guo; Brian Kondracki; Nick Nikiforakis; Steven Skiena (WWW, 2022)

Hierarchies over Vector Space: Orienting Word and Graph Embeddings. - Xingzhi Guo; Steven Skiena (CoRR, 2022)

Provable Fairness for Neural Network Models Using Formal Verification. - Giorgian Borca-Tasciuc; Xingzhi Guo; Stanley Bak; Steven Skiena (EWAF, 2023)

SubAnom: Efficient Subgraph Anomaly Detection Framework over Dynamic Graphs. - Chi Zhang; Wenkai Xiang; Xingzhi Guo; Baojian Zhou; Deqing Yang (ICDM (Workshops), 2023)

Accelerating Personalized PageRank Vector Computation. - Zhen Chen; Xingzhi Guo; Baojian Zhou; Deqing Yang; Steven Skiena (KDD, 2023)

COMET: Convolutional Dimension Interaction for Collaborative Filtering. - Zhuoyi Lin; Lei Feng 006; Xingzhi Guo; Yu Zhang 084; Rui Yin 002; Chee Keong Kwoh 001; Chi Xu (ACM Trans. Intell. Syst. Technol., 2023)

The Evolution of Occupational Identity in Twitter Biographies. - Xingzhi Guo; Dakota Handzlik; Jason Jeffrey Jones; Steven S. Skiena (ICWSM, 2024)

Iterative Methods via Locally Evolving Set Process. - Baojian Zhou; Yifan Sun; Reza Babanezhad Harikandeh; Xingzhi Guo; Deqing Yang; Yanghua Xiao (NeurIPS, 2024)

Analyzing the Evolution of Graphs and Texts. - Xingzhi Guo (CoRR, 2024)

Fast and Robust Contextual Node Representation Learning over Dynamic Graphs. - Xingzhi Guo; Silong Wang; Baojian Zhou; Yanghua Xiao; Steven Skiena (CoRR, 2024)

MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning. - Chanwoo Park; Seungju Han 002; Xingzhi Guo; Asuman E. Ozdaglar; Kaiqing Zhang; Joo-Kyung Kim (ACL (1), 2025)