| 2026 | ACL | BrowseComp-Plus: A Fair and Disentangled Evaluation Benchmark for Deep Search Agents. | Zijian Chen, Xueguang Ma, Shengyao Zhuang, Ping Nie, Kai Zou, Sahel Sharifymoghaddam, Andrew Liu, Joshua Green, Kshama Patel, Ruoxi Meng, Mingyi Su, Yanxi Li, Haoran Hong, Xinyu Shi, Xuye Liu, Hosna Oyarhoseini, Nandan Thakur, Crystina Zhang, Luyu Gao, Wenhu Chen, Jimmy Lin |
| 2026 | ECIR | Do We Still Need Text Features for Video Retrieval in the Era of Vision-Language Models? | Jiaqi Samantha Zhan, Crystina Zhang, Shengyao Zhuang, Xueguang Ma, Jimmy Lin |
| 2026 | ECIR | [inline-graphic not available: see fulltext] Starbucks: Improved Training for 2D Matryoshka Embeddings. | Shengyao Zhuang, Shuai Wang, Fabio Zheng, Bevan Koopman, Guido Zuccon |
| 2026 | SIGIR | Where Relevance Emerges: A Layer-Wise Study of Internal Attention for Zero-Shot Re-Ranking. | Haodong Chen, Shengyao Zhuang, Zheng Yao, Guido Zuccon, Teerapong Leelanupab |
| 2026 | SIGIR | LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum. | Zhichao Xu, Shengyao Zhuang, Crystina Zhang, Xueguang Ma, Yijun Tian, Maitrey Mehta, Jimmy Lin, Vivek Srikumar |
| 2026 | SIGIR | Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning. | Shengyao Zhuang, Xueguang Ma, Zheng Yao, Shuai Wang, Bevan Koopman, Jimmy Lin, Guido Zuccon |
| 2026 | SIGIR | Layer-wise Token Compression for Efficient Document Reranking. | Shengyao Zhuang, Zhichao Xu, Ivano Lauriola |
| 2025 | ACL | VISA: Retrieval Augmented Generation with Visual Source Attribution. | Xueguang Ma, Shengyao Zhuang, Bevan Koopman, Guido Zuccon, Wenhu Chen, Jimmy Lin |
| 2025 | ACL | 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 |
| 2025 | ECIR | Corpus Subsampling: Estimating the Effectiveness of Neural Retrieval Models on Large Corpora. | Maik Frbe, Andrew Parry, Harrisen Scells, Shuai Wang, Shengyao Zhuang, Guido Zuccon, Martin Potthast, Matthias Hagen |
| 2025 | ECIR | Set-Encoder: Permutation-Invariant Inter-passage Attention for Listwise Passage Re-ranking with Cross-Encoders. | Ferdinand Schlatt, Maik Frbe, Harrisen Scells, Shengyao Zhuang, Bevan Koopman, Guido Zuccon, Benno Stein, Martin Potthast, Matthias Hagen |
| 2025 | ECIR | Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-ranking. | Ferdinand Schlatt, Maik Frbe, Harrisen Scells, Shengyao Zhuang, Bevan Koopman, Guido Zuccon, Benno Stein, Martin Potthast, Matthias Hagen |
| 2025 | ECIR | An Investigation of Prompt Variations for Zero-Shot LLM-Based Rankers. | Shuoqi Sun, Shengyao Zhuang, Shuai Wang, Guido Zuccon |
| 2025 | IJCNLP | Distillation versus Contrastive Learning: How to Train Your Rerankers. | Zhichao Xu, Zhiqi Huang, Shengyao Zhuang, Vivek Srikumar |
| 2025 | WWW | ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search. | Shuai Wang, Shengyao Zhuang, Bevan Koopman, Guido Zuccon |
| 2025 | SIGIR | 2D Matryoshka Training for Information Retrieval. | Shuai Wang, Shengyao Zhuang, Bevan Koopman, Guido Zuccon |
| 2025 | SIGIR | Tevatron 2.0: Unified Document Retrieval Toolkit across Scale, Language, and Modality. | Xueguang Ma, Luyu Gao, Shengyao Zhuang, Jiaqi Samantha Zhan, Jamie Callan, Jimmy Lin |
| 2025 | SIGIR | Document Screenshot Retrievers are Vulnerable to Pixel Poisoning Attacks. | Shengyao Zhuang, Ekaterina Khramtsova, Xueguang Ma, Bevan Koopman, Jimmy Lin, Guido Zuccon |
| 2025 | SIGIR | R | Guido Zuccon, Shengyao Zhuang, Xueguang Ma |
| 2024 | ECIR | Zero-Shot Generative Large Language Models for Systematic Review Screening Automation. | Shuai Wang, Harrisen Scells, Shengyao Zhuang, Martin Potthast, Bevan Koopman, Guido Zuccon |
| 2024 | EMNLP | 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 |
| 2024 | SIGIR | 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 |
| 2024 | SIGIR | Leveraging LLMs for Unsupervised Dense Retriever Ranking. | Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon |
| 2024 | SIGIR | Revisiting Document Expansion and Filtering for Effective First-Stage Retrieval. | Watheq Mansour, Shengyao Zhuang, Guido Zuccon, Joel Mackenzie |
| 2024 | SIGIR | Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation. | Xinyu Mao, Shengyao Zhuang, Bevan Koopman, Guido Zuccon |
| 2024 | SIGIR | FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation. | Shuai Wang, Ekaterina Khramtsova, Shengyao Zhuang, Guido Zuccon |
| 2024 | SIGIR | Large Language Models Based Stemming for Information Retrieval: Promises, Pitfalls and Failures. | Shuai Wang, Shengyao Zhuang, Guido Zuccon |
| 2024 | SIGIR | A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models. | Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, Guido Zuccon |
| 2023 | EMNLP | Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking. | Shengyao Zhuang, Bing Liu, Bevan Koopman, Guido Zuccon |
| 2023 | ICTIR | Exploring the Representation Power of SPLADE Models. | Joel Mackenzie, Shengyao Zhuang, Guido Zuccon |
| 2023 | ICTIR | Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models. | Guido Zuccon, Harrisen Scells, Shengyao Zhuang |
| 2023 | SIGIR | Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval. | Shengyao Zhuang, Linjun Shou, Guido Zuccon |
| 2022 | ADCS | Pseudo-Relevance Feedback with Dense Retrievers in Pyserini. | Hang Li, Shengyao Zhuang, Xueguang Ma, Jimmy Lin, Guido Zuccon |
| 2022 | ADCS | Robustness of Neural Rankers to Typos: A Comparative Study. | Shengyao Zhuang, Xinyu Mao, Guido Zuccon |
| 2022 | ECIR | 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 |
| 2022 | SIGIR | 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 |
| 2022 | SIGIR | Reduce, Reuse, Recycle: Green Information Retrieval Research. | Harrisen Scells, Shengyao Zhuang, Guido Zuccon |
| 2022 | SIGIR | Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach. | Shengyao Zhuang, Hang Li, Guido Zuccon |
| 2022 | SIGIR | CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos. | Shengyao Zhuang, Guido Zuccon |
| 2022 | SIGIR | Asyncval: A Toolkit for Asynchronously Validating Dense Retriever Checkpoints During Training. | Shengyao Zhuang, Guido Zuccon |
| 2021 | ECIR | Federated Online Learning to Rank with Evolution Strategies: A Reproducibility Study. | Shuyi Wang, Shengyao Zhuang, Guido Zuccon |
| 2021 | ECIR | Deep Query Likelihood Model for Information Retrieval. | Shengyao Zhuang, Hang Li, Guido Zuccon |
| 2021 | EMNLP | Dealing with Typos for BERT-based Passage Retrieval and Ranking. | Shengyao Zhuang, Guido Zuccon |
| 2021 | ICTIR | Effective and Privacy-preserving Federated Online Learning to Rank. | Shuyi Wang, Bing Liu, Shengyao Zhuang, Guido Zuccon |
| 2021 | ICTIR | BERT-based Dense Retrievers Require Interpolation with BM25 for Effective Passage Retrieval. | Shuai Wang, Shengyao Zhuang, Guido Zuccon |
| 2021 | SIGIR | How do Online Learning to Rank Methods Adapt to Changes of Intent? | Shengyao Zhuang, Guido Zuccon |
| 2021 | SIGIR | TILDE: Term Independent Likelihood moDEl for Passage Re-ranking. | Shengyao Zhuang, Guido Zuccon |
| 2020 | ECIR | Counterfactual Online Learning to Rank. | Shengyao Zhuang, Guido Zuccon |