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ORCIDShengyao Zhuang
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- affiliation: University of Queensland, Brisbane, Queensland, Australia
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2020 – today
- 2022
[j1]Shengyao Zhuang, Zhihao Qiao, Guido Zuccon
:
Reinforcement online learning to rank with unbiased reward shaping. Inf. Retr. J. 25(4): 386-413 (2022)- [c14]Hang Li, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon:
Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback: A Reproducibility Study. ECIR (1) 2022: 599-612 - [c13]Shengyao Zhuang, Hang Li, Guido Zuccon:
Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach. SIGIR 2022: 18-28 - [c12]Shengyao Zhuang, Guido Zuccon:
CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos. SIGIR 2022: 1444-1454 - [c11]Hang Li, Shuai Wang, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon:
To Interpolate or not to Interpolate: PRF, Dense and Sparse Retrievers. SIGIR 2022: 2495-2500 - [c10]Harrisen Scells, Shengyao Zhuang, Guido Zuccon:
Reduce, Reuse, Recycle: Green Information Retrieval Research. SIGIR 2022: 2825-2837 - [c9]Shengyao Zhuang, Guido Zuccon:
Asyncval: A Toolkit for Asynchronously Validating Dense Retriever Checkpoints During Training. SIGIR 2022: 3235-3239 - [i11]Shengyao Zhuang, Zhihao Qiao, Guido Zuccon:
Reinforcement Online Learning to Rank with Unbiased Reward Shaping. CoRR abs/2201.01534 (2022) - [i10]Shengyao Zhuang, Guido Zuccon:
Asyncval: A Toolkit for Asynchronously Validating Dense Retriever Checkpoints during Training. CoRR abs/2202.12510 (2022) - [i9]Shengyao Zhuang, Guido Zuccon:
CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos. CoRR abs/2204.00716 (2022) - [i8]Shengyao Zhuang, Hang Li, Guido Zuccon:
Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach. CoRR abs/2204.00718 (2022) - [i7]Hang Li, Shuai Wang, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon:
To Interpolate or not to Interpolate: PRF, Dense and Sparse Retrievers. CoRR abs/2205.00235 (2022) - [i6]Shengyao Zhuang, Houxing Ren, Linjun Shou, Jian Pei, Ming Gong, Guido Zuccon, Daxin Jiang:
Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation. CoRR abs/2206.10128 (2022) - [i5]Bevan Koopman, Ahmed Mourad, Hang Li, Anton van der Vegt, Shengyao Zhuang, Simon Gibson, Yash Dang, David Lawrence, Guido Zuccon:
AgAsk: An Agent to Help Answer Farmer's Questions From Scientific Documents. CoRR abs/2212.10762 (2022) - 2021
- [c8]Shuyi Wang, Shengyao Zhuang, Guido Zuccon:
Federated Online Learning to Rank with Evolution Strategies: A Reproducibility Study. ECIR (2) 2021: 134-149 - [c7]Shengyao Zhuang, Hang Li, Guido Zuccon:
Deep Query Likelihood Model for Information Retrieval. ECIR (2) 2021: 463-470 - [c6]Shengyao Zhuang, Guido Zuccon:
Dealing with Typos for BERT-based Passage Retrieval and Ranking. EMNLP (1) 2021: 2836-2842 - [c5]Shuyi Wang, Bing Liu, Shengyao Zhuang, Guido Zuccon:
Effective and Privacy-preserving Federated Online Learning to Rank. ICTIR 2021: 3-12 - [c4]Shuai Wang, Shengyao Zhuang, Guido Zuccon:
BERT-based Dense Retrievers Require Interpolation with BM25 for Effective Passage Retrieval. ICTIR 2021: 317-324 - [c3]Shengyao Zhuang, Guido Zuccon:
How do Online Learning to Rank Methods Adapt to Changes of Intent? SIGIR 2021: 911-920 - [c2]Shengyao Zhuang, Guido Zuccon:
TILDE: Term Independent Likelihood moDEl for Passage Re-ranking. SIGIR 2021: 1483-1492 - [i4]Shengyao Zhuang, Guido Zuccon:
Fast Passage Re-ranking with Contextualized Exact Term Matching and Efficient Passage Expansion. CoRR abs/2108.08513 (2021) - [i3]Hang Li, Ahmed Mourad, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Pseudo Relevance Feedback with Deep Language Models and Dense Retrievers: Successes and Pitfalls. CoRR abs/2108.11044 (2021) - [i2]Shengyao Zhuang, Guido Zuccon:
Dealing with Typos for BERT-based Passage Retrieval and Ranking. CoRR abs/2108.12139 (2021) - [i1]Hang Li, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon:
Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback: A Reproducibility Study. CoRR abs/2112.06400 (2021) - 2020
- [c1]Shengyao Zhuang, Guido Zuccon:
Counterfactual Online Learning to Rank. ECIR (1) 2020: 415-430
Coauthor Index
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