I am a Ph.D. student in the ielab, School of Information Technology and Electrical Engineering, The University of Queensland, supervised by A/Prof. Guido Zuccon.

I am working on improving effectiveness, efficiency, and robustness for pre-trained deep language model based information retrieval systems.

Publications

2022

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 arxiv preprint, 2022. Full paper

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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

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Reduce, Reuse, Recycle: Green Information Retrieval Researchs

Harry Scells, Shengyao Zhuang, Guido Zuccon ( Best Paper Honorable Mention Award )

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

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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

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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

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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

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Reinforcement Online Learning to Rank with Unbiased Reward Shaping

Shengyao Zhuang, Zhihao Qiao, Guido Zuccon

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

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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

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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

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Robustness of Neural Rankers to Typos: A Comparative Study

Shengyao Zhuang, Xinyu Mao, Guido Zuccon ( Best Paper Award )

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

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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

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2021

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

Shengyao Zhuang, Guido Zuccon

Published in arxiv preprint, 2021. Full paper

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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

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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

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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

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Effective and Privacy-preserving Federated Online Learning to Rank

Shuyi Wang, Bing Liu, Shengyao Zhuang, Guido Zuccon ( Best Student Paper Award )

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

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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

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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

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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

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2020

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

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