Shengyao Zhuang

According to our database, Shengyao Zhuang authored at least 46 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

AgAsk: an agent to help answer farmer's questions from scientific documents.

Bevan Koopman, Ahmed Mourad, Hang Li, Anton van der Vegt, Shengyao Zhuang, Simon Gibson, Yash Dang, David Lawrence, Guido Zuccon

Int. J. Digit. Libr., December, 2024

Starbucks: Improved Training for 2D Matryoshka Embeddings.

Shengyao Zhuang, Shuai Wang, Bevan Koopman, Guido Zuccon

CoRR, 2024

Does Vec2Text Pose a New Corpus Poisoning Threat?

Shengyao Zhuang, Bevan Koopman, Guido Zuccon

CoRR, 2024

An Investigation of Prompt Variations for Zero-shot LLM-based Rankers.

Shuoqi Sun, Shengyao Zhuang, Shuai Wang, Guido Zuccon

CoRR, 2024

The Impact of Auxiliary Patient Data on Automated Chest X-Ray Report Generation and How to Incorporate It.

Aaron Nicolson, Shengyao Zhuang, Jason Dowling, Bevan Koopman

CoRR, 2024

A Systematic Investigation of Distilling Large Language Models into Cross-Encoders for Passage Re-ranking.

Ferdinand Schlatt, Maik Fröbe, Harrisen Scells, Shengyao Zhuang, Bevan Koopman, Guido Zuccon, Benno Stein, Martin Potthast, Matthias Hagen

CoRR, 2024

Set-Encoder: Permutation-Invariant Inter-Passage Attention for Listwise Passage Re-Ranking with Cross-Encoders.

Ferdinand Schlatt, Maik Fröbe, Harrisen Scells, Shengyao Zhuang, Bevan Koopman, Guido Zuccon, Benno Stein, Martin Potthast, Matthias Hagen

CoRR, 2024

Large Language Models for Stemming: Promises, Pitfalls and Failures.

Shuai Wang, Shengyao Zhuang, Guido Zuccon

CoRR, 2024

ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search.

Shuai Wang, Shengyao Zhuang, Bevan Koopman, Guido Zuccon

CoRR, 2024

A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models.

Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, Guido Zuccon

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Large Language Models Based Stemming for Information Retrieval: Promises, Pitfalls and Failures.

Shuai Wang, Shengyao Zhuang, Guido Zuccon

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation.

Shuai Wang, Ekaterina Khramtsova, Shengyao Zhuang, Guido Zuccon

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation.

Xinyu Mao, Shengyao Zhuang, Bevan Koopman, Guido Zuccon

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Revisiting Document Expansion and Filtering for Effective First-Stage Retrieval.

Watheq Mansour, Shengyao Zhuang, Guido Zuccon, Joel Mackenzie

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Leveraging LLMs for Unsupervised Dense Retriever Ranking.

Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection.

Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems.

Shengyao Zhuang, Bevan Koopman, Xiaoran Chu, Guido Zuccon

Proceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, 2024

PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval.

Shengyao Zhuang, Xueguang Ma, Bevan Koopman, Jimmy Lin, Guido Zuccon

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Zero-Shot Generative Large Language Models for Systematic Review Screening Automation.

Shuai Wang, Harrisen Scells, Shengyao Zhuang, Martin Potthast, Bevan Koopman, Guido Zuccon

Proceedings of the Advances in Information Retrieval, 2024

2023

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

Hang Li, Ahmed Mourad, Shengyao Zhuang, Bevan Koopman, Guido Zuccon

ACM Trans. Inf. Syst., 2023

Team IELAB at TREC Clinical Trial Track 2023: Enhancing Clinical Trial Retrieval with Neural Rankers and Large Language Models.

Shengyao Zhuang, Bevan Koopman, Guido Zuccon

Proceedings of the Thirty-Second Text REtrieval Conference Proceedings (TREC 2023), 2023

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

Shengyao Zhuang, Linjun Shou, Guido Zuccon

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval.

Shengyao Zhuang, Linjun Shou, Jian Pei, Ming Gong, Houxing Ren, Guido Zuccon, Daxin Jiang

Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, 2023

Selecting which Dense Retriever to use for Zero-Shot Search.

Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon

Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, 2023

Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models.

Guido Zuccon, Harrisen Scells, Shengyao Zhuang

Proceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval, 2023

Exploring the Representation Power of SPLADE Models.

Joel Mackenzie, Shengyao Zhuang, Guido Zuccon

Proceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval, 2023

Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking.

Shengyao Zhuang, Bing Liu, Bevan Koopman, Guido Zuccon

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

Reinforcement online learning to rank with unbiased reward shaping.

Shengyao Zhuang, Zhihao Qiao, Guido Zuccon

Inf. Retr. J., 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, Daxin Jiang

CoRR, 2022

Asyncval: A Toolkit for Asynchronously Validating Dense Retriever Checkpoints During Training.

Shengyao Zhuang, Guido Zuccon

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

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

Shengyao Zhuang, Guido Zuccon

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach.

Shengyao Zhuang, Hang Li, Guido Zuccon

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Reduce, Reuse, Recycle: Green Information Retrieval Research.

Harrisen Scells, Shengyao Zhuang, Guido Zuccon

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

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

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

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

Proceedings of the Advances in Information Retrieval, 2022

Robustness of Neural Rankers to Typos: A Comparative Study.

Shengyao Zhuang, Xinyu Mao, Guido Zuccon

Proceedings of the 26th Australasian Document Computing Symposium, 2022

Pseudo-Relevance Feedback with Dense Retrievers in Pyserini.

Hang Li, Shengyao Zhuang, Xueguang Ma, Jimmy Lin, Guido Zuccon

Proceedings of the 26th Australasian Document Computing Symposium, 2022

2021

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

Shengyao Zhuang, Guido Zuccon

CoRR, 2021

TILDE: Term Independent Likelihood moDEl for Passage Re-ranking.

Shengyao Zhuang, Guido Zuccon

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

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

Shengyao Zhuang, Guido Zuccon

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

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

Shuai Wang, Shengyao Zhuang, Guido Zuccon

Proceedings of the ICTIR '21: The 2021 ACM SIGIR International Conference on the Theory of Information Retrieval, 2021

Effective and Privacy-preserving Federated Online Learning to Rank.

Shuyi Wang, Bing Liu, Shengyao Zhuang, Guido Zuccon

Proceedings of the ICTIR '21: The 2021 ACM SIGIR International Conference on the Theory of Information Retrieval, 2021

Dealing with Typos for BERT-based Passage Retrieval and Ranking.

Shengyao Zhuang, Guido Zuccon

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Deep Query Likelihood Model for Information Retrieval.

Shengyao Zhuang, Hang Li, Guido Zuccon

Proceedings of the Advances in Information Retrieval, 2021

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

Shuyi Wang, Shengyao Zhuang, Guido Zuccon

Proceedings of the Advances in Information Retrieval, 2021

2020

Counterfactual Online Learning to Rank.

Shengyao Zhuang, Guido Zuccon

Proceedings of the Advances in Information Retrieval, 2020