Systematic Review Automation Tools for End-to-End Query Formulation. - Hang Li 009; Harrisen Scells; Guido Zuccon (SIGIR, 2020)

IELAB for TREC Conversational Assistance Track (CAsT) 2020. - Sebastian Cross; Hang Li 009; Arvin Zhuang; Ahmed Mourad; Guido Zuccon; Bevan Koopman (TREC, 2020)

MeSH Term Suggestion for Systematic Review Literature Search. - Shuai Wang 032; Hang Li 009; Harrisen Scells; Daniel Locke; Guido Zuccon (ADCS, 2021)

Deep Query Likelihood Model for Information Retrieval. - Shengyao Zhuang; Hang Li 009; Guido Zuccon (ECIR (2), 2021)

Pseudo-Relevance Feedback with Dense Retrievers in Pyserini. - Hang Li 009; Shengyao Zhuang; Xueguang Ma; Jimmy Lin; Guido Zuccon (ADCS, 2022)

Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback: A Reproducibility Study. - Hang Li 009; Shengyao Zhuang; Ahmed Mourad; Xueguang Ma; Jimmy Lin; Guido Zuccon (ECIR (1), 2022)

How Does Feedback Signal Quality Impact Effectiveness of Pseudo Relevance Feedback for Passage Retrieval. - Hang Li 009; Ahmed Mourad; Bevan Koopman; Guido Zuccon (SIGIR, 2022)

To Interpolate or not to Interpolate: PRF, Dense and Sparse Retrievers. - Hang Li 009; Shuai Wang 032; Shengyao Zhuang; Ahmed Mourad; Xueguang Ma; Jimmy Lin; Guido Zuccon (SIGIR, 2022)

Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach. - Shengyao Zhuang; Hang Li 009; Guido Zuccon (SIGIR, 2022)

AgAsk: A Conversational Search Agent for Answering Agricultural Questions. - Hang Li 009; Bevan Koopman; Ahmed Mourad; Guido Zuccon (WSDM, 2023)

MeSH Suggester: A Library and System for MeSH Term Suggestion for Systematic Review Boolean Query Construction. - Shuai Wang 032; Hang Li 009; Guido Zuccon (WSDM, 2023)

Pseudo Relevance Feedback with Deep Language Models and Dense Retrievers: Successes and Pitfalls. - Hang Li 009; Ahmed Mourad; Shengyao Zhuang; Bevan Koopman; Guido Zuccon (ACM Trans. Inf. Syst., 2023)

TPRF: A Transformer-based Pseudo-Relevance Feedback Model for Efficient and Effective Retrieval. - Chuting Yu; Hang Li 009; Ahmed Mourad; Bevan Koopman; Guido Zuccon (CoRR, 2024)

AgAsk: an agent to help answer farmer's questions from scientific documents. - Bevan Koopman; Ahmed Mourad; Hang Li 009; Anton van der Vegt; Shengyao Zhuang; Simon Gibson; Yash Dang; David Lawrence; Guido Zuccon (Int. J. Digit. Libr., 2024)

Pseudo-Relevance Feedback Can Improve Zero-Shot LLM-Based Dense Retrieval. - Hang Li 009; Xiao Wang; Bevan Koopman; Guido Zuccon (CoRR, 2025)

LLM-VPRF: Large Language Model Based Vector Pseudo Relevance Feedback. - Hang Li 009; Shengyao Zhuang; Bevan Koopman; Guido Zuccon (CoRR, 2025)