Dialog state tracking with attention-based sequence-to-sequence learning. - Takaaki Hori; Hai Wang; Chiori Hori; Shinji Watanabe 001; Bret Harsham; Jonathan Le Roux; John R. Hershey; Yusuke Koji; Yi Jing; Zhaocheng Zhu; Takeyuki Aikawa (SLT, 2016)

Context Aware Document Embedding. - Zhaocheng Zhu; Junfeng Hu (CoRR, 2017)

Saliency Supervision: An Intuitive and Effective Approach for Pain Intensity Regression. - Conghui Li; Zhaocheng Zhu; Yuming Zhao (ICONIP (7), 2018)

Self-Adaptive Network Pruning. - Jinting Chen; Zhaocheng Zhu; Cheng Li; Yuming Zhao (ICONIP (1), 2019)

GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding. - Zhaocheng Zhu; Shizhen Xu; Jian Tang 005; Meng Qu (WWW, 2019)

KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation. - Xiaozhi Wang; Tianyu Gao 001; Zhaocheng Zhu; Zhiyuan Liu 001; Juanzi Li; Jian Tang 005 (CoRR, 2019)

GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation. - Chence Shi; Minkai Xu; Zhaocheng Zhu; Weinan Zhang 001; Ming Zhang 004; Jian Tang 005 (ICLR, 2020)

Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction. - Zhaocheng Zhu; Zuobai Zhang; Louis-Pascal A. C. Xhonneux; Jian Tang 005 (NeurIPS, 2021)

KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation. - Xiaozhi Wang; Tianyu Gao 001; Zhaocheng Zhu; Zhengyan Zhang; Zhiyuan Liu 001; Juanzi Li; Jian Tang 005 (Trans. Assoc. Comput. Linguistics, 2021)

Neural-Symbolic Models for Logical Queries on Knowledge Graphs. - Zhaocheng Zhu; Mikhail Galkin 001; Zuobai Zhang; Jian Tang 005 (ICML, 2022)

Inductive Logical Query Answering in Knowledge Graphs. - Michael Galkin; Zhaocheng Zhu; Hongyu Ren; Jian Tang 005 (NeurIPS, 2022)

PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding. - Minghao Xu; Zuobai Zhang; Jiarui Lu; Zhaocheng Zhu; Yangtian Zhang; Chang Ma; Runcheng Liu; Jian Tang 005 (NeurIPS, 2022)

TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery. - Zhaocheng Zhu; Chence Shi; Zuobai Zhang; Shengchao Liu; Minghao Xu; Xinyu Yuan; Yangtian Zhang; Jun-Kun Chen; Huiyu Cai; Jiarui Lu; Chang Ma; Runcheng Liu; et al. (CoRR, 2022)

Learning to Efficiently Propagate for Reasoning on Knowledge Graphs. - Zhaocheng Zhu; Xinyu Yuan; Louis-Pascal A. C. Xhonneux; Ming Zhang 004; Maxime Gazeau; Jian Tang 005 (CoRR, 2022)

A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs. - Zhaocheng Zhu; Xinyu Yuan; Michael Galkin; Louis-Pascal A. C. Xhonneux; Ming Zhang 004; Maxime Gazeau; Jian Tang 005 (NeurIPS, 2023)

Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases. - Hongyu Ren; Mikhail Galkin 001; Michael Cochez; Zhaocheng Zhu; Jure Leskovec (CoRR, 2023)

GraphText: Graph Reasoning in Text Space. - Jianan Zhao 002; Le Zhuo; Yikang Shen; Meng Qu; Kai Liu; Michael M. Bronstein; Zhaocheng Zhu; Jian Tang 005 (CoRR, 2023)

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. - Dominique Beaini; Shenyang Huang; Joao Alex Cunha; Zhiyi Li; Gabriela Moisescu-Pareja; Oleksandr Dymov; Samuel Maddrell-Mander; Callum McLean; Frederik Wenkel; Luis Müller; Jama Hussein Mohamud; Ali Parviz; et al. (CoRR, 2023)

Large Language Models can Learn Rules. - Zhaocheng Zhu; Yuan Xue 001; Xinyun Chen; Denny Zhou; Jian Tang 005; Dale Schuurmans; Hanjun Dai (CoRR, 2023)

Towards Foundation Models for Knowledge Graph Reasoning. - Mikhail Galkin 001; Xinyu Yuan; Hesham Mostafa; Jian Tang 005; Zhaocheng Zhu (ICLR, 2024)

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. - Dominique Beaini; Shenyang Huang; Joao Alex Cunha; Zhiyi Li; Gabriela Moisescu-Pareja; Oleksandr Dymov; Samuel Maddrell-Mander; Callum McLean; Frederik Wenkel; Luis Müller; Jama Hussein Mohamud; Ali Parviz; et al. (ICLR, 2024)

A Foundation Model for Zero-shot Logical Query Reasoning. - Michael Galkin; Jincheng Zhou; Bruno Ribeiro 001; Jian Tang 005; Zhaocheng Zhu (NeurIPS, 2024)

The 1st International Workshop on Graph Foundation Models (GFM). - Haitao Mao; Jianan Zhao 002; Xiaoxin He; Zhikai Chen; Qian Huang; Zhaocheng Zhu; Jian Tang 005; Michael M. Bronstein; Xavier Bresson; Bryan Hooi; Haiyang Zhang; Xianfeng Tang; et al. (WWW (Companion Volume), 2024)

Zero-shot Logical Query Reasoning on any Knowledge Graph. - Mikhail Galkin 001; Jincheng Zhou; Bruno F. Ribeiro; Jian Tang 005; Zhaocheng Zhu (CoRR, 2024)

GraphAny: A Foundation Model for Node Classification on Any Graph. - Jianan Zhao 002; Hesham Mostafa; Mikhail Galkin 001; Michael M. Bronstein; Zhaocheng Zhu; Jian Tang 005 (CoRR, 2024)

Learning Representations for Reasoning: Generalizing Across Diverse Structures. - Zhaocheng Zhu (CoRR, 2024)

Neural Graph Reasoning: A Survey on Complex Logical Query Answering. - Hongyu Ren; Mikhail Galkin 001; Zhaocheng Zhu; Jure Leskovec; Michael Cochez (Trans. Mach. Learn. Res., 2024)

Fully-inductive Node Classification on Arbitrary Graphs. - Jianan Zhao 002; Zhaocheng Zhu; Mikhail Galkin 001; Hesham Mostafa; Michael M. Bronstein; Jian Tang 005 (ICLR, 2025)

Learning Equivalence Classes of Bayesian Network Structures with GFlowNet. - Michelle Liu; Zhaocheng Zhu; Olexa Bilaniuk; Emmanuel Bengio (Trans. Mach. Learn. Res., 2025)

Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models. - Zhanke Zhou; Zhaocheng Zhu; Xuan Li 005; Mikhail Galkin 001; Xiao Feng 003; Sanmi Koyejo; Jian Tang 005; Bo Han 003 (CoRR, 2025)

From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information? - Zhanke Zhou; Xiao Feng 003; Zhaocheng Zhu; Jiangchao Yao; Sanmi Koyejo; Bo Han 003 (CoRR, 2025)

Overcoming Long-Context Limitations of State-Space Models via Context-Dependent Sparse Attention. - Zhihao Zhan; Jianan Zhao 002; Zhaocheng Zhu; Jian Tang 005 (CoRR, 2025)