Semantics-assisted Wasserstein Learning for Topic and Word Embeddings. - Changchun Li; Ximing Li 002; Jihong Ouyang; Yiming Wang 012 (ICDM, 2020)

Detecting the Fake Candidate Instances: Ambiguous Label Learning with Generative Adversarial Networks. - Changchun Li; Ximing Li 002; Jihong Ouyang; Yiming Wang 012 (CIKM, 2021)

Extracting Topics with Simultaneous Word Co-occurrence and Semantic Correlation Graphs: Neural Topic Modeling for Short Texts. - Yiming Wang 012; Ximing Li 002; Xiaotang Zhou; Jihong Ouyang (EMNLP (Findings), 2021)

Layer-Assisted Neural Topic Modeling over Document Networks. - Yiming Wang 012; Ximing Li 002; Jihong Ouyang (IJCAI, 2021)

Weakly-supervised Text Classification with Wasserstein Barycenters Regularization. - Jihong Ouyang; Yiming Wang 012; Ximing Li 002; Changchun Li (IJCAI, 2022)

Extracting nonlinear neural topics with neural variational bayes. - Yiming Wang 012; Ximing Li 002; Jihong Ouyang; Zeqi Guo; Yimeng Wang (World Wide Web, 2022)

Applying Kumaraswamy distribution on stick-breaking process: a Dirichlet neural topic model approach. - Jihong Ouyang; Teng Wang; Jingyue Cao; Yiming Wang 012 (Neural Comput. Appl., 2024)

A collection of nine multi-label text classification datasets. - Yiming Wang 012 (IEEE DataPort, 2024)

Variety Is the Spice of Life: Detecting Misinformation with Dynamic Environmental Representations. - Bing Wang 018; Ximing Li 002; Yiming Wang 012; Changchun Li; Jiaxu Cui; Renchu Guan; Bo Yang 002 (CIKM, 2025)

Generalizing Dynamics Modeling More Easily from Representation Perspective. - Yiming Wang 012; Zhengnan Zhang; Genghe Zhang; Jiawen Dan; Changchun Li; Chenlong Hu; Chris Nugent; Jun Liu; Ximing Li 002; Bo Yang 002 (CoRR, 2026)

Factorize to Generalize: Retrieval-Guided Invariant-Dynamic Decomposition for Time Series Forecasting. - Jinjin Chi; Lei Feng 006; Lulu Zhang; Yongcheng Jing; Yiming Wang 012; Ximing Li 002; Jialie Shen 001; Leszek Rutkowski; Dacheng Tao (CoRR, 2026)