Shengyao Zhuang

Orcid: 0000-0002-6711-0955

Affiliations:
  • University of Queensland, Brisbane, Queensland, Australia


According to our database1, Shengyao Zhuang authored at least 59 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent.
CoRR, August, 2025

Distillation versus Contrastive Learning: How to Train Your Rerankers.
CoRR, July, 2025

Leveraging Reference Documents for Zero-Shot Ranking via Large Language Models.
CoRR, June, 2025

MAGMaR Shared Task System Description: Video Retrieval with OmniEmbed.
CoRR, June, 2025

LLM-VPRF: Large Language Model Based Vector Pseudo Relevance Feedback.
CoRR, April, 2025

Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning.
CoRR, March, 2025

ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

R<sup>2</sup>LLMs: Retrieval and Ranking with LLMs.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Document Screenshot Retrievers are Vulnerable to Pixel Poisoning Attacks.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Tevatron 2.0: Unified Document Retrieval Toolkit across Scale, Language, and Modality.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

2D Matryoshka Training for Information Retrieval.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

An Investigation of Prompt Variations for Zero-Shot LLM-Based Rankers.
Proceedings of the Advances in Information Retrieval, 2025

Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-ranking.
Proceedings of the Advances in Information Retrieval, 2025

Set-Encoder: Permutation-Invariant Inter-passage Attention for Listwise Passage Re-ranking with Cross-Encoders.
Proceedings of the Advances in Information Retrieval, 2025

Corpus Subsampling: Estimating the Effectiveness of Neural Retrieval Models on Large Corpora.
Proceedings of the Advances in Information Retrieval, 2025

The Impact of Auxiliary Patient Data on Automated Chest X-Ray Report Generation and How to Incorporate It.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

VISA: Retrieval Augmented Generation with Visual Source Attribution.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024
AgAsk: an agent to help answer farmer's questions from scientific documents.
Int. J. Digit. Libr., December, 2024

Starbucks: Improved Training for 2D Matryoshka Embeddings.
CoRR, 2024

Does Vec2Text Pose a New Corpus Poisoning Threat?
CoRR, 2024

A Systematic Investigation of Distilling Large Language Models into Cross-Encoders for Passage Re-ranking.
CoRR, 2024

Large Language Models for Stemming: Promises, Pitfalls and Failures.
CoRR, 2024

A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models.
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.
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.
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.
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.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Leveraging LLMs for Unsupervised Dense Retriever Ranking.
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.
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.
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.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Zero-Shot Generative Large Language Models for Systematic Review Screening Automation.
Proceedings of the Advances in Information Retrieval, 2024

2023
Pseudo Relevance Feedback with Deep Language Models and Dense Retrievers: Successes and Pitfalls.
ACM Trans. Inf. Syst., 2023

Team IELAB at TREC Clinical Trial Track 2023: Enhancing Clinical Trial Retrieval with Neural Rankers and Large Language Models.
Proceedings of the Thirty-Second Text REtrieval Conference Proceedings (TREC 2023), 2023

Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval.
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.
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.
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.
Proceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval, 2023

Exploring the Representation Power of SPLADE Models.
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.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Reinforcement online learning to rank with unbiased reward shaping.
Inf. Retr. J., 2022

Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation.
CoRR, 2022

Asyncval: A Toolkit for Asynchronously Validating Dense Retriever Checkpoints During Training.
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.
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.
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.
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.
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.
Proceedings of the Advances in Information Retrieval, 2022

Robustness of Neural Rankers to Typos: A Comparative Study.
Proceedings of the 26th Australasian Document Computing Symposium, 2022

Pseudo-Relevance Feedback with Dense Retrievers in Pyserini.
Proceedings of the 26th Australasian Document Computing Symposium, 2022

2021
Fast Passage Re-ranking with Contextualized Exact Term Matching and Efficient Passage Expansion.
CoRR, 2021

TILDE: Term Independent Likelihood moDEl for Passage Re-ranking.
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?
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.
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.
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.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Deep Query Likelihood Model for Information Retrieval.
Proceedings of the Advances in Information Retrieval, 2021

Federated Online Learning to Rank with Evolution Strategies: A Reproducibility Study.
Proceedings of the Advances in Information Retrieval, 2021

2020
Counterfactual Online Learning to Rank.
Proceedings of the Advances in Information Retrieval, 2020


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