ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation. - Jing Song; Hong Shen 001; Zijing Ou; Junyi Zhang 001; Teng Xiao; Shangsong Liang (IJCAI, 2019)

Embedding Dynamic Attributed Networks by Modeling the Evolution Processes. - Zenan Xu; Zijing Ou; Qinliang Su; Jianxing Yu; Xiaojun Quan; Zhenkun Lin (COLING, 2020)

Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval. - Zijing Ou; Qinliang Su; Jianxing Yu; Bang Liu 003; Jingwen Wang; Ruihui Zhao; Changyou Chen; Yefeng Zheng 001 (ACL/IJCNLP (1), 2021)

Refining BERT Embeddings for Document Hashing via Mutual Information Maximization. - Zijing Ou; Qinliang Su; Jianxing Yu; Ruihui Zhao; Yefeng Zheng 001; Bang Liu 003 (EMNLP (Findings), 2021)

Unsupervised Hashing with Contrastive Information Bottleneck. - Zexuan Qiu; Qinliang Su; Zijing Ou; Jianxing Yu; Changyou Chen (IJCAI, 2021)

Imperfect also Deserves Reward: Multi-Level and Sequential Reward Modeling for Better Dialog Management. - Zhengxu Hou; Bang Liu 003; Ruihui Zhao; Zijing Ou; Yafei Liu; Xi Chen 003; Yefeng Zheng 001 (NAACL-HLT, 2021)

Learning and Updating Node Embedding on Dynamic Heterogeneous Information Network. - Yuanzhen Xie; Zijing Ou; Liang Chen 001; Yang Liu 245; Kun Xu; Carl Yang 001; Zibin Zheng (WSDM, 2021)

MCSCSet: A Specialist-annotated Dataset for Medical-domain Chinese Spelling Correction. - Wangjie Jiang; Zhihao Ye; Zijing Ou; Ruihui Zhao; Jianguang Zheng; Yi Liu 057; Bang Liu 003; Siheng Li; Yujiu Yang; Yefeng Zheng 001 (CIKM, 2022)

Tell Me How to Survey: Literature Review Made Simple with Automatic Reading Path Generation. - Jiayuan Ding; Tong Xiang; Zijing Ou; Wangyang Zuo; Ruihui Zhao; Chenghua Lin; Yefeng Zheng 001; Bang Liu 003 (ICDE, 2022)

Learning Neural Set Functions Under the Optimal Subset Oracle. - Zijing Ou; Tingyang Xu; Qinliang Su; Yingzhen Li; Peilin Zhao; Yatao Bian (NeurIPS, 2022)

Learning Set Functions Under the Optimal Subset Oracle via Equivariant Variational Inference. - Zijing Ou; Tingyang Xu; Qinliang Su; Yingzhen Li; Peilin Zhao; Yatao Bian (CoRR, 2022)

Modeling Semantic Composition with Syntactic Hypergraph for Video Question Answering. - Zenan Xu; Wanjun Zhong; Qinliang Su; Zijing Ou; Fuwei Zhang (CoRR, 2022)

Energy Discrepancies: A Score-Independent Loss for Energy-Based Models. - Tobias Schröder; Zijing Ou; Jen Lim; Yingzhen Li; Sebastian J. Vollmer; Andrew B. Duncan (NeurIPS, 2023)

Energy Discrepancies: A Score-Independent Loss for Energy-Based Models. - Tobias Schröder; Zijing Ou; Jen Ning Lim; Yingzhen Li; Sebastian J. Vollmer; Andrew B. Duncan (CoRR, 2023)

Training Discrete Energy-Based Models with Energy Discrepancy. - Tobias Schröder; Zijing Ou; Yingzhen Li; Andrew B. Duncan (CoRR, 2023)

Energy-Based Modelling for Discrete and Mixed Data via Heat Equations on Structured Spaces. - Tobias Schröder; Zijing Ou; Yingzhen Li; Andrew B. Duncan (NeurIPS, 2024)

Diffusion Model With Optimal Covariance Matching. - Zijing Ou; Mingtian Zhang; Andi Zhang 001; Tim Z. Xiao; Yingzhen Li; David Barber (CoRR, 2024)

Mutual Information Multinomial Estimation. - Yanzhi Chen; Zijing Ou; Adrian Weller; Yingzhen Li (CoRR, 2024)

Improving Probabilistic Diffusion Models With Optimal Diagonal Covariance Matching. - Zijing Ou; Mingtian Zhang; Andi Zhang 001; Tim Z. Xiao; Yingzhen Li; David Barber (ICLR, 2025)

Entropy-Based Decoding for Retrieval-Augmented Large Language Models. - Zexuan Qiu; Zijing Ou; Bin Wu 025; Jingjing Li 007; Aiwei Liu; Irwin King (NAACL (Long Papers), 2025)

Neural Flow Samplers with Shortcut Models. - Wuhao Chen; Zijing Ou; Yingzhen Li (CoRR, 2025)

Towards Training One-Step Diffusion Models Without Distillation. - Mingtian Zhang; Jiajun He 003; Wenlin Chen; Zijing Ou; José Miguel Hernández-Lobato; Bernhard Schölkopf; David Barber (CoRR, 2025)

TabRep: Training Tabular Diffusion Models with a Simple and Effective Continuous Representation. - Jacob Si; Zijing Ou; Mike Qu; Zhengrui Xiang; Yingzhen Li (CoRR, 2025)

Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion. - Ruixiang Zhang; Shuangfei Zhai; Yizhe Zhang 002; James Thornton; Zijing Ou; Joshua M. Susskind; Navdeep Jaitly (CoRR, 2025)

Discrete Neural Flow Samplers with Locally Equivariant Transformer. - Zijing Ou; Ruixiang Zhang; Yingzhen Li (CoRR, 2025)

Test-Time Alignment of Discrete Diffusion Models with Sequential Monte Carlo. - Chinmay Pani; Zijing Ou; Yingzhen Li (CoRR, 2025)

VarDiU: A Variational Diffusive Upper Bound for One-Step Diffusion Distillation. - Leyang Wang; Mingtian Zhang; Zijing Ou; David Barber (CoRR, 2025)

Memory-Driven Self-Improvement for Decision Making with Large Language Models. - Xue Yan; Zijing Ou; Mengyue Yang; Yan Song; Haifeng Zhang; Yingzhen Li; Jun Wang (CoRR, 2025)