Publications

2023

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 arxiv preprint, 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

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 ()

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

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

Shengyao Zhuang

Publications

2023

Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval

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

2022

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

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

Reduce, Reuse, Recycle: Green Information Retrieval Researchs

Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach

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

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

Reinforcement Online Learning to Rank with Unbiased Reward Shaping

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

Pseudo-Relevance Feedback with Dense Retrievers in Pyserini

Robustness of Neural Rankers to Typos: A Comparative Study

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

2021

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

TILDE: Term Independent Likelihood moDEl for Passage Re-ranking

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

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

Effective and Privacy-preserving Federated Online Learning to Rank

Dealing with Typos for BERT-based Passage Retrieval and Ranking

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

Deep Query Likelihood Model for Information Retrieval

2020

Counterfactual Online Learning to Rank