GZ
Guido Zuccon
cs.IRcs.CLcs.AIcs.LGMachine LearningNatural Language Processingcs.CRElectronic Health RecordsCancer classificationcs.CV
On Valency
published · living versionsW_zdvx78df·v1 · currentpublished
Do Conversational Agents Need Explicit Memory? A Controlled Comparison with Raw-History Retrieval
with Yongjie Zhou, Shuai Wang, Bevan Koopman
1 version
Preprints & journals
110 papers in the corpus · 2012–2026Do Conversational Agents Need Explicit Memory? A Controlled Comparison with Raw-History Retrieval2610.24671v1 · Yongjie Zhou, Shuai Wang, Bevan Koopman et al.2026 · 0 citationsarXivon Valency
The Impact of Backbone Evolution on LLM-Based Relevance Assessments2610.09820v1 · Chuting Yu, Guido Zuccon, Teerapong Leelanupab2026 · 0 citationsarXiv
ITER: Interaction-Aware Retrieval for Agentic Search2608.27912v2 · Haodong Chen, Shuai Wang, Yu Yin et al.2026 · 0 citationsarXiv
How retriever redundancy and diversity impact RAG effectiveness2608.13956v1 · Jonathan J Ross, Bevan Koopman, Anton van der Vegt et al.2026 · 0 citationsarXiv
Search, Inspect, Fetch: Exploiting Structure-Aware Boolean Retrieval for Deep-Search Agents2608.02751v3 · Shuai Wang, Haodong Chen, Yu Yin et al.2026 · 0 citationsarXiv
Reproducing LightMem: When Does Memory Construction Help Over Raw-Turn Retrieval?2607.29104v2 · Yongjie Zhou, Shuai Wang, Bevan Koopman et al.2026 · 0 citationsarXiv
More Efficient LLM Reranking with Whole-Pool, Setwise, Long-Context Language Models2606.01782v3 · Hang Li, Chuting Yu, Bevan Koopman et al.2026 · 0 citationsarXiv
On the impact of retrieved content representations in RAG Pipelines2605.30790v1 · Jonathan J Ross, Bevan Koopman, Anton van der Vegt et al.2026 · 0 citationsarXiv
Can It Reach the Generator? Investigating the Survival of Prompt-Injection Attacks in Realistic RAG Settings2605.28017v2 · Yu Yin, Shuai Wang, Bevan Koopman et al.2026 · 0 citationsarXiv
DiffRetriever: Parallel Representative Tokens for Retrieval with Diffusion Language Models2605.07210v2 · Shuai Wang, Yu Yin, Shengyao Zhuang et al.2026 · 0 citationsarXiv
Where Relevance Emerges: A Layer-Wise Study of Internal Attention for Zero-Shot Re-Ranking2602.22591v2 · Haodong Chen, Shengyao Zhuang, Zheng Yao et al.2026 · 1 citationarXiv
Beyond Chunk-Then-Embed: A Comprehensive Taxonomy and Evaluation of Document Chunking Strategies for Information Retrieval2602.16974v1 · Yongjie Zhou, Shuai Wang, Bevan Koopman et al.2026 · 0 citationsarXiv
When LLM Judges Inflate Scores: Exploring Overrating in Relevance Assessment2602.17170v3 · Chuting Yu, Hang Li, Guido Zuccon et al.2026 · 1 citationarXiv
The Vulnerability of LLM Rankers to Prompt Injection Attacks2602.16752v1 · Yu Yin, Shuai Wang, Bevan Koopman et al.2026 · 0 citationsSIGIR 2026
Inferential Question Answering2602.01239v1 · Jamshid Mozafari, Hamed Zamani, Guido Zuccon et al.2026 · 0 citationsarXiv
AutoBool: An Reinforcement-Learning trained LLM for Effective Automated Boolean Query Generation for Systematic Reviews2602.00005v1 · Shuai Wang, Harrisen Scells, Bevan Koopman et al.2025 · 0 citationsarXiv
Beyond GeneGPT: A Multi-Agent Architecture with Open-Source LLMs for Enhanced Genomic Question Answering2511.15061v1 · Haodong Chen, Guido Zuccon, Teerapong Leelanupab2025 · 2 citationsarXiv
Humans are more gullible than LLMs in believing common psychological myths2507.12296v1 · Bevan Koopman, Guido Zuccon2025 · 0 citationsarXiv
The epidemiology of hospitalisations from four key environmentally sensitive zoonotic diseases in Queensland, 2012-2019.40525299 · Proboste, Tatiana, Lau, Colleen L, Clark, Nicholas et al.2025 · 0 citationsTropical medicine & international health : TM & IH. 2025;30(8):838-847
Unlearning for Federated Online Learning to Rank: A Reproducibility Study2505.12791v1 · Yiling Tao, Shuyi Wang, Jiaxi Yang et al.2025 · 2 citationsarXiv
Reassessing Large Language Model Boolean Query Generation for Systematic Reviews2505.07155v2 · Shuai Wang, Harrisen Scells, Bevan Koopman et al.2025 · 4 citationsarXiv
Pre-training vs. Fine-tuning: A Reproducibility Study on Dense Retrieval Knowledge Acquisition2505.07166v1 · Zheng Yao, Shuai Wang, Guido Zuccon2025 · 1 citationarXiv
AiReview: An Open Platform for Accelerating Systematic Reviews with LLMs2504.04193v1 · Xinyu Mao, Teerapong Leelanupab, Martin Potthast et al.2025 · 3 citationsarXiv
LLM-VPRF: Large Language Model Based Vector Pseudo Relevance Feedback2504.01448v1 · Hang Li, Shengyao Zhuang, Bevan Koopman et al.2025 · 1 citationarXiv
Pseudo Relevance Feedback is Enough to Close the Gap Between Small and Large Dense Retrieval Models2503.14887v2 · Hang Li, Xiao Wang, Bevan Koopman et al.2025 · 0 citationsarXiv
Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning2503.06034v1 · Shengyao Zhuang, Xueguang Ma, Bevan Koopman et al.2025 · 3 citationsarXiv
DenseReviewer: A Screening Prioritisation Tool for Systematic Review based on Dense Retrieval2502.03400v1 · Xinyu Mao, Teerapong Leelanupab, Harrisen Scells et al.2025 · 5 citationsarXiv
Document Screenshot Retrievers are Vulnerable to Pixel Poisoning Attacks2501.16902v1 · Shengyao Zhuang, Ekaterina Khramtsova, Xueguang Ma et al.2025 · 4 citationsarXiv
VISA: Retrieval Augmented Generation with Visual Source Attribution2412.14457v1 · Xueguang Ma, Shengyao Zhuang, Bevan Koopman et al.2024 · 12 citationsarXiv
2D Matryoshka Training for Information Retrieval2411.17299v1 · Shuai Wang, Shengyao Zhuang, Bevan Koopman et al.2024 · 2 citationsarXiv
Starbucks-v2: Improved Training for 2D Matryoshka Embeddings2410.13230v3 · Shengyao Zhuang, Shuai Wang, Fabio Zheng et al.2024 · 0 citationsarXiv
Does Vec2Text Pose a New Corpus Poisoning Threat?2410.06628v1 · Shengyao Zhuang, Bevan Koopman, Guido Zuccon2024 · 1 citationarXiv
Source-Free Domain-Invariant Performance Prediction2408.02209v2 · Ekaterina Khramtsova, Mahsa Baktashmotlagh, Guido Zuccon et al.2024 · 0 citationsarXiv
Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection2407.06685v1 · Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang et al.2024 · 1 citationarXiv
Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation2407.00635v2 · Xinyu Mao, Shengyao Zhuang, Bevan Koopman et al.2024 · 4 citationsarXiv
An Investigation of Prompt Variations for Zero-shot LLM-based Rankers2406.14117v4 · Shuoqi Sun, Shengyao Zhuang, Shuai Wang et al.2024 · 15 citationsProceedings of the 47th European Conference on Information Retrieval (ECIR 2025)
Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-Ranking2405.07920v4 · Ferdinand Schlatt, Maik Frobe, Harrisen Scells et al.2024 · 12 citationsarXiv
The new paradigm in machine learning - foundation models, large language models and beyond: a primer for physicians.38715436 · Scott, Ian A, Zuccon, Guido2024 · 30 citationsInternal medicine journal. 2024;54(5):705-715
PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval2404.18424v3 · Shengyao Zhuang, Xueguang Ma, Bevan Koopman et al.2024 · 29 citationsarXiv
Set-Encoder: Permutation-Invariant Inter-Passage Attention for Listwise Passage Re-Ranking with Cross-Encoders2404.06912v5 · Ferdinand Schlatt, Maik Frobe, Harrisen Scells et al.2024 · 7 citationsarXiv
Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems2402.12784v2 · Shengyao Zhuang, Bevan Koopman, Xiaoran Chu et al.2024 · 9 citationsarXiv
Large Language Models for Stemming: Promises, Pitfalls and Failures2402.11757v1 · Shuai Wang, Shengyao Zhuang, Guido Zuccon2024 · 0 citationsarXiv
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation2402.11891v1 · Shuai Wang, Ekaterina Khramtsova, Shengyao Zhuang et al.2024 · 28 citationsarXiv
Leveraging LLMs for Unsupervised Dense Retriever Ranking2402.04853v2 · Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh et al.2024 · 21 citationsarXiv
ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search2401.17645v1 · Shuai Wang, Shengyao Zhuang, Bevan Koopman et al.2024 · 4 citationsarXiv
How to Forget Clients in Federated Online Learning to Rank?2401.13410v1 · Shuyi Wang, Bing Liu, Guido Zuccon2024 · 7 citationsarXiv
TPRF: A Transformer-based Pseudo-Relevance Feedback Model for Efficient and Effective Retrieval2401.13509v2 · Hang Li, Chuting Yu, Ahmed Mourad et al.2024 · 0 citationsarXiv
A Reproducibility Study of Goldilocks: Just-Right Tuning of BERT for TAR2401.08104v1 · Xinyu Mao, Bevan Koopman, Guido Zuccon2024 · 6 citationsarXiv
Zero-shot Generative Large Language Models for Systematic Review Screening Automation2401.06320v2 · Shuai Wang, Harrisen Scells, Shengyao Zhuang et al.2024 · 28 citationsarXiv
Team IELAB at TREC Clinical Trial Track 2023: Enhancing Clinical Trial Retrieval with Neural Rankers and Large Language Models2401.01566v1 · Shengyao Zhuang, Bevan Koopman, Guido Zuccon2024 · 2 citationsarXiv
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