CV

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Work experience

The University of Queensland
- Adjunct Lecturer
- Dec 2023 - Current
CSIRO, Australian e-Health Research Centre, Brisbane
- Postdoctoral Research Fellow
- Search and Natural Language Process for Precision Medicine.
- Project website: http://health-search.csiro.au/oscar/
- Mar 2023 – Current
Microsoft, Beijing, STCA group
- Research Intern
- Developing multimodal and multilingual entity retrieval models.
- May 2022 - Nov 2022
The University of Queensland
- Casual Research Assistant
- Assist with the research and development of methods of information retrieval and evaluation based on online learning to rank.
- Apr 2019 - July 2019

Awards

ICTIR 2021 [ ]
- Effective and Privacy-preserving Federated Online Learning to Rank
SIGIR 2021 Top10 authors (unofficial) [ Rank #3 ]
- Based on normalized full paper count.
2021 HUAWEI DIGIX GLOBAL AI CHALLENGE [ Champion🥇 ]
- Search rankings in multimodal and multilingual contexts.
- Team leader, US$30,000 prize.
SIGIR 2022 [ ]
- Reduce, Reuse, Recycle: Green Information Retrieval Research
ADCS 2022 [ ]
- Robustness of Neural Rankers to Typos: A Comparative Study

Education

Ph.D. Candidate in Computer Science, The University of Queensland, Australia, 2019 - current.
- Thesis topic: Teaching Pre-trained Language Models to Rank Effectively, Efficiently and Robustly
Master of Information Technology, The University of Queensland, Australia, 2017 - 2018.
- GPA: 6.3/7
Bachelor of Electrical Engineering, China, Chongqing University of Science and Technology, 2012 - 2016.

Teaching

The University of Queensland
- Tutor
- Tutoring of the INFS7410 (Information Retrieval and Web Search) course. Preparing and delivering course materials, assignments, and exam markings.
- July 2019 - May 2022

Service

PC member: SIGIR-AP2023, GenIR2023, ReNeuIR2023, SIGIR2023, SIGIR2022, SIGIR2021, ADCS2021, ADCS2022, TheWebConf2023, TOIS, ACM Computing Surveys
Publicity Chair of CIKM2021

Publications

Large Language Models for Stemming: Promises, Pitfalls and Failures

Shuai Wang, Shengyao Zhuang, and Guido Zuccon.

Published in Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’24), 2024. Short paper

Leveraging LLMs for Unsupervised Dense Retriever Ranking

Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, and Guido Zuccon

Published in Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’24), 2024. Full paper

Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems

Shengyao Zhuang, Bevan Koopman, Xiaoran Chu, and Guido Zuccon.

Published in Arxiv Preprint, 2024. Full paper

Teaching Pre-Trained Language Models to Rank Effectively, Efficiently, and Robustly

Shengyao Zhuang.

Published in The University of Queensland, 2023. Thesis

Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval

Shengyao Zhuang, Linjun Shou, Jian Pei, Ming Gong, Houxing Ren, Guido Zuccon and Daxin Jiang.

Published in Proceedings of the 1st International ACM SIGIR Conference on Information Retrieval in the Asia Pacific (SIGIR-AP ’23), 2023. Full paper

A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models

Shengyao Zhuang, Honglei Zhuang, Bevan Koopman and Guido Zuccon.

Published in Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’24), 2023. Full paper

Selecting which Dense Retriever to use for Zero-Shot Search

Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang and Guido Zuccon.

Published in Proceedings of the 1st International ACM SIGIR Conference on Information Retrieval in the Asia Pacific (SIGIR-AP ’23), 2023. Full paper

Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval

Shengyao Zhuang, Linjun Shou, Guido Zuccon

Published in Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’23), 2023. Short paper

Exploring the Representation Power of SPLADE Models

Joel Mackenziem, Shengyao Zhuang, Guido Zuccon

Published in Proceedings of the 2023 ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR ’23), 2023. Short paper

Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models

Guido Zuccon, Harrisen Scells, Shengyao Zhuang

Published in Proceedings of the 2023 ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR ’23), 2023. Short paper

Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking

Shengyao Zhuang, Bing Liu, Bevan Koopman and Guido Zuccon.

Published in Findings of the Association for Computational Linguistics: EMNLP 2023, 2023. Short paper

Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation

Shengyao Zhuang, Houxing Ren, Linjun Shou, Jian Pei, Ming Gong, Guido Zuccon and Daxin Jiang.

Published in The First Workshop on Generative Information Retrieval at SIGIR2023, 2023. Full paper

To Interpolate or not to Interpolate: PRF, Dense and Sparse Retrievers

Hang Li, Shuai Wang, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon

Published in Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22), 2022. Short paper

Reduce, Reuse, Recycle: Green Information Retrieval Research

Harry Scells, Shengyao Zhuang, Guido Zuccon ()

Published in Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22), 2022. Perspective paper

Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach

Shengyao Zhuang, Hang Li and Guido Zuccon

Published in Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22), 2022. Full paper

CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos

Shengyao Zhuang, Guido Zuccon

Published in Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22), 2022. Full paper

Asyncval: A Toolkit for Asynchronously Validating Dense Retriever Checkpoints during Training

Shengyao Zhuang, Guido Zuccon

Published in Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22), 2022. Demo paper

Reinforcement Online Learning to Rank with Unbiased Reward Shaping

Shengyao Zhuang, Zhihao Qiao, Guido Zuccon

Published in Information Retrieval Journal (IRJ), 2022. Journal paper

Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback: A Reproducibility Study

Hang Li, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon

Published in Proceedings of the 44th European Conference on Information Retrieval (ECIR ’22), 2022. Reproducibility paper

Pseudo-Relevance Feedback with Dense Retrievers in Pyserini

Hang Li, Shengyao Zhuang, Xueguang Ma, Jimmy Lin, Guido Zuccon

Published in Proceedings of the 26th Australasian Document Computing Symposium (ADCS ’22), 2022. Demo paper

Robustness of Neural Rankers to Typos: A Comparative Study

Shengyao Zhuang, Xinyu Mao, Guido Zuccon ()

Published in Proceedings of the 26th Australasian Document Computing Symposium (ADCS ’22), 2022. Short paper

Pseudo Relevance Feedback with Deep Language Models and Dense Retrievers: Successes and Pitfalls

Hang Li, Ahmed Mourad, Shengyao Zhuang, Bevan Koopman, Guido Zuccon

Published in Transactions on Information Systems (TOIS), 2022. Journal paper

Fast Passage Re-ranking with Contextualized Exact Term Matching and Efficient Passage Expansion

Shengyao Zhuang, Guido Zuccon

Published in arxiv preprint, 2021. Full paper

TILDE: Term Independent Likelihood moDEl for Passage Re-ranking

Shengyao Zhuang, Guido Zuccon

Published in Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’21), 2021. Full paper

How do Online Learning to Rank Methods Adapt to Changes of Intent?

Shengyao Zhuang, Guido Zuccon

Published in Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’21), 2021. Full paper

BERT-based Dense Retrievers Require Interpolation with BM25 for Effective Passage Retrieval

Shuai Wang, Shengyao Zhuang, Guido Zuccon

Published in Proceedings of the 2021 ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR ’21), 2021. Full paper

Effective and Privacy-preserving Federated Online Learning to Rank

Shuyi Wang, Bing Liu, Shengyao Zhuang, Guido Zuccon ()

Published in Proceedings of the 2021 ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR ’21), 2021. Full paper

Dealing with Typos for BERT-based Passage Retrieval and Ranking

Shengyao Zhuang, Guido Zuccon

Published in In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021. Short paper

Federated Online Learning to Rank with Evolution Strategies: A Reproducibility Study

Shuyi Wang, Shengyao Zhuang, Guido Zuccon

Published in Advances in Information Retrieval - 43rd European Conference on IR Research, ECIR 2021, 2021. Reproducibility paper

Deep Query Likelihood Model for Information Retrieval

Shengyao Zhuang, Hang Li, Guido Zuccon

Published in Advances in Information Retrieval - 43rd European Conference on IR Research, ECIR 2021, 2021. Short paper

Counterfactual Online Learning to Rank

Shengyao Zhuang, Guido Zuccon

Published in Advances in Information Retrieval - 42nd European Conference on IR Research, ECIR 2020, 2020. Full paper