Bo Xiong

Postdoc @ Stanford University

I am a Postdoctoral Scholar in AI at Stanford University, under the supervision of Prof. Mark Musen. Prior to that, I received my Ph.D. (with summa cum laude) in computer science at University of Stuttgart, Germany and the Intl. Max Plank Research School for Intelligent Systems (IMPRS-IS), under the supervision of Prof. Steffen Staab. My PhD was funded by the Marie Skłodowska-Curie PhD Fellowship. I was also an associate member of the TrustAGI Lab advised by Prof. Shirui Pan. I have published 20+ papers and/or served as PC in premier AI conferences such as NeurIPS, ICLR, KDD, ACL, WWW, EMNLP, NAACL, SIGIR, AAAI, ECAI, ISWC, etc., and received the Best Student Paper Award of ISWC’22.

I am currently developing neuro-symbolic and knowledge-intensive foundation models, which are capable of learning, reasoning, and adapting into diverse tasks. I aim to bridge the gap between symbolic structures (e.g., knowledge graphs, biomedical ontology) and deep learning (e.g., LLMs, multi-modal models), and build reliable and interpretable AI systems allowing for adapting into applications in biomedicine and healthcare.

In my PhD dissertation (PDF), I studied a new paradigm of representation learning that captures both logical structures and similarity, bridging two historically distinct approaches in AI: connectionism and symbolism.

Recent News

Feb 2025 One paper was accepted by IEEE TPAMI (IF 20.8)
Jan 2025 One paper was accepted by ICLR’25
Jan 2025 Two papers (1 main, 1 short) were accepted by WWW’25
Jan 2025 One long paper was accepted by NAACL’25
Dec 2024 I started a Postdoc position at Stanford University
Sep 2024 Three finding papers got accepted by EMNLP’24
Jul 2024 I successfully defended my Ph.D. with summa cum laude (highest distinction)

Selected Publications

  1. ICLR
    From Tokens to Lattices: Emergent Lattice Structure in Language Models
    Bo Xiong, and Steffen Staab
    International Conference on Learning Representation 2025
    arXiv
  2. NeurIPS
    Pseudo-Riemannian Graph Convolutional Networks
    Bo Xiong, Shichao Zhu, Nico Potyka, Shirui Pan, Chuan Zhou, and Steffen Staab
    Advances in Neural Information Processing Systems 2022
    arXiv Code
  3. NeurIPS
    Hyperbolic Embedding Inference for Structured Multi-Label Prediction
    Bo Xiong, Michael Cochez, Mojtaba Nayyeri, and Steffen Staab
    Advances in Neural Information Processing Systems 2022
    arXiv Code
  4. WWW
    MaSH: Maximal Separating Poincaré Hyperplanes for Hierarchical Imbalanced Learning
    Bo Xiong, Jiaying Lu, Yuqicheng Zhu, and Carl Yang
    Short Paper Track, ACM The Web Conference 2025
    arXiv
  5. WWW
    DAGE: DAG Query Answering via Relational Combinator with Logical Constraints
    Yunjie He,  Bo Xiong, Daniel Hernández, Yuqicheng Zhu, Evgeny Kharlamov, and Steffen Staab
    The Web Conference 2025
    arXiv
  6. Preprint
    Is Complex Query Answering Really Complex?
    Cosimo Gregucci,  Bo Xiong, Daniel Hernandez, Lorenzo Loconte, Pasquale Minervini, Steffen Staab, and Antonio Vergari
    arXiv preprint arXiv:2410.12537 2024
    arXiv
  7. AAAI
    NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning
    Bo Xiong, Mojtaba Nayyeri, Linhao Luo, Zihao Wang, Shirui Pan, and Steffen Staab
    The 38th Annual AAAI Conference on Artificial Intelligence 2024
    arXiv Code
  8. ACL
    Shrinking Embeddings for Hyper-Relational Knowledge Graphs
    Bo Xiong, Mojtaba Nayyeri, Shirui Pan, and Steffen Staab
    The 61st Annual Meeting of the Association for Computational Linguistics 2023
    arXiv Code
  9. ISWC
    Faithful Embeddings for EL++ Knowledge Bases
    Bo Xiong, Nico Potyka, Trung-Kien Tran, Mojtaba Nayyeri, and Steffen Staab
    Best Student Paper, International Semantic Web Conference 2022
    arXiv Code
  10. KDD
    Ultrahyperbolic Knowledge Graph Embeddings
    Bo Xiong, Shichao Zhu, Mojtaba Nayyeri, Chenjin Xu, Shirui Pan, Chuan Zhou, and Steffen Staab.
    The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2022
    arXiv Code