default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDShengyao Zhuang
Person information
- affiliation: University of Queensland, Brisbane, Queensland, Australia
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[j3]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. Int. J. Digit. Libr. 25(4): 569-584 (2024)- [c33]Shuai Wang, Harrisen Scells, Shengyao Zhuang, Martin Potthast, Bevan Koopman, Guido Zuccon:
Zero-Shot Generative Large Language Models for Systematic Review Screening Automation. ECIR (1) 2024: 403-420 - [c32]Shengyao Zhuang, Xueguang Ma, Bevan Koopman, Jimmy Lin, Guido Zuccon:
PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval. EMNLP 2024: 4375-4391 - [c31]Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, Guido Zuccon:
A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models. SIGIR 2024: 38-47 - [c30]Watheq Mansour, Shengyao Zhuang, Guido Zuccon, Joel Mackenzie:
Revisiting Document Expansion and Filtering for Effective First-Stage Retrieval. SIGIR 2024: 186-196 - [c29]Shuai Wang, Ekaterina Khramtsova, Shengyao Zhuang, Guido Zuccon:
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation. SIGIR 2024: 763-773 - [c28]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Leveraging LLMs for Unsupervised Dense Retriever Ranking. SIGIR 2024: 1307-1317 - [c27]Xinyu Mao, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation. SIGIR 2024: 2357-2362 - [c26]Shuai Wang, Shengyao Zhuang, Guido Zuccon:
Large Language Models Based Stemming for Information Retrieval: Promises, Pitfalls and Failures. SIGIR 2024: 2492-2496 - [c25]Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection. SIGIR 2024: 2739-2743 - [c24]Shengyao Zhuang, Bevan Koopman, Xiaoran Chu, Guido Zuccon:
Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems. SIGIR-AP 2024: 259-268 - [i35]Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Team IELAB at TREC Clinical Trial Track 2023: Enhancing Clinical Trial Retrieval with Neural Rankers and Large Language Models. CoRR abs/2401.01566 (2024) - [i34]Shuai Wang, Harrisen Scells, Shengyao Zhuang, Martin Potthast, Bevan Koopman, Guido Zuccon:
Zero-shot Generative Large Language Models for Systematic Review Screening Automation. CoRR abs/2401.06320 (2024) - [i33]Shuai Wang, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search. CoRR abs/2401.17645 (2024) - [i32]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Leveraging LLMs for Unsupervised Dense Retriever Ranking. CoRR abs/2402.04853 (2024) - [i31]Shuai Wang, Shengyao Zhuang, Guido Zuccon:
Large Language Models for Stemming: Promises, Pitfalls and Failures. CoRR abs/2402.11757 (2024) - [i30]Shuai Wang, Ekaterina Khramtsova, Shengyao Zhuang, Guido Zuccon:
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation. CoRR abs/2402.11891 (2024) - [i29]Shengyao Zhuang, Bevan Koopman, Xiaoran Chu, Guido Zuccon:
Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems. CoRR abs/2402.12784 (2024) - [i28]Ferdinand Schlatt, Maik Fröbe, Harrisen Scells, Shengyao Zhuang, Bevan Koopman, Guido Zuccon, Benno Stein, Martin Potthast, Matthias Hagen:
Set-Encoder: Permutation-Invariant Inter-Passage Attention for Listwise Passage Re-Ranking with Cross-Encoders. CoRR abs/2404.06912 (2024) - [i27]Shengyao Zhuang, Xueguang Ma, Bevan Koopman, Jimmy Lin, Guido Zuccon:
PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval. CoRR abs/2404.18424 (2024) - [i26]Ferdinand Schlatt, Maik Fröbe, Harrisen Scells, Shengyao Zhuang, Bevan Koopman, Guido Zuccon, Benno Stein, Martin Potthast, Matthias Hagen:
A Systematic Investigation of Distilling Large Language Models into Cross-Encoders for Passage Re-ranking. CoRR abs/2405.07920 (2024) - [i25]Aaron Nicolson, Shengyao Zhuang, Jason Dowling, Bevan Koopman:
The Impact of Auxiliary Patient Data on Automated Chest X-Ray Report Generation and How to Incorporate It. CoRR abs/2406.13181 (2024) - [i24]Shuoqi Sun, Shengyao Zhuang, Shuai Wang, Guido Zuccon:
An Investigation of Prompt Variations for Zero-shot LLM-based Rankers. CoRR abs/2406.14117 (2024) - [i23]Xinyu Mao, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation. CoRR abs/2407.00635 (2024) - [i22]Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection. CoRR abs/2407.06685 (2024) - [i21]Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Does Vec2Text Pose a New Corpus Poisoning Threat? CoRR abs/2410.06628 (2024) - [i20]Shengyao Zhuang, Shuai Wang, Bevan Koopman, Guido Zuccon:
Starbucks: Improved Training for 2D Matryoshka Embeddings. CoRR abs/2410.13230 (2024) - [i19]Shuai Wang, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
2D Matryoshka Training for Information Retrieval. CoRR abs/2411.17299 (2024) - 2023
- [j2]Hang Li, Ahmed Mourad, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Pseudo Relevance Feedback with Deep Language Models and Dense Retrievers: Successes and Pitfalls. ACM Trans. Inf. Syst. 41(3): 62:1-62:40 (2023) - [c23]Shengyao Zhuang, Bing Liu, Bevan Koopman, Guido Zuccon:
Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking. EMNLP (Findings) 2023: 8807-8817 - [c22]Joel Mackenzie, Shengyao Zhuang, Guido Zuccon:
Exploring the Representation Power of SPLADE Models. ICTIR 2023: 143-147 - [c21]Guido Zuccon, Harrisen Scells, Shengyao Zhuang:
Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models. ICTIR 2023: 283-289 - [c20]Shengyao Zhuang, Linjun Shou, Guido Zuccon:
Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval. SIGIR 2023: 1827-1832 - [c19]Shengyao Zhuang, Linjun Shou, Jian Pei, Ming Gong, Houxing Ren, Guido Zuccon, Daxin Jiang:
Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval. SIGIR-AP 2023: 212-222 - [c18]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon:
Selecting which Dense Retriever to use for Zero-Shot Search. SIGIR-AP 2023: 223-233 - [c17]Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Team IELAB at TREC Clinical Trial Track 2023: Enhancing Clinical Trial Retrieval with Neural Rankers and Large Language Models. TREC 2023 - [i18]Shengyao Zhuang, Linjun Shou, Jian Pei, Ming Gong, Houxing Ren, Guido Zuccon, Daxin Jiang:
Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval. CoRR abs/2304.08138 (2023) - [i17]Shengyao Zhuang, Linjun Shou, Guido Zuccon:
Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval. CoRR abs/2305.03950 (2023) - [i16]Guido Zuccon, Harrisen Scells, Shengyao Zhuang:
Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models. CoRR abs/2306.16668 (2023) - [i15]Joel Mackenzie, Shengyao Zhuang, Guido Zuccon:
Exploring the Representation Power of SPLADE Models. CoRR abs/2306.16680 (2023) - [i14]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon:
Selecting which Dense Retriever to use for Zero-Shot Search. CoRR abs/2309.09403 (2023) - [i13]Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, Guido Zuccon:
A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models. CoRR abs/2310.09497 (2023) - [i12]Shengyao Zhuang, Bing Liu, Bevan Koopman, Guido Zuccon:
Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking. CoRR abs/2310.13243 (2023) - 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) - [c16]Hang Li, Shengyao Zhuang, Xueguang Ma, Jimmy Lin, Guido Zuccon:
Pseudo-Relevance Feedback with Dense Retrievers in Pyserini. ADCS 2022: 1:1-1:6 - [c15]Shengyao Zhuang, Xinyu Mao, Guido Zuccon:
Robustness of Neural Rankers to Typos: A Comparative Study. ADCS 2022: 6:1-6:6 - [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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-01-13 01:07 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
