Shengyao (Arvin) Zhuang 庄胜尧
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
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 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
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 ( Best Paper Award )
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
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
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 ( 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
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
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