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Guido Zuccon
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- affiliation: University of Queensland, Australia
- affiliation: Queensland University of Technology
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2020 – today
- 2024
- [c210]Linh Le, Genghong Zhao, Xia Zhang, Guido Zuccon, Gianluca Demartini:
CoLAL: Co-learning Active Learning for Text Classification. AAAI 2024: 13337-13345 - [c209]Shuyi Wang, Bing Liu, Guido Zuccon:
How to Forget Clients in Federated Online Learning to Rank? ECIR (3) 2024: 105-121 - [c208]Xinyu Mao, Bevan Koopman, Guido Zuccon:
A Reproducibility Study of Goldilocks: Just-Right Tuning of BERT for TAR. ECIR (4) 2024: 132-146 - [c207]Shuai Wang, Harrisen Scells, Shengyao Zhuang, Martin Potthast, Bevan Koopman, Guido Zuccon:
Zero-Shot Generative Large Language Models for Systematic Review Screening Automation. ECIR (1) 2024: 403-420 - [c206]Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, Guido Zuccon:
A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models. SIGIR 2024: 38-47 - [c205]Watheq Mansour, Shengyao Zhuang, Guido Zuccon, Joel Mackenzie:
Revisiting Document Expansion and Filtering for Effective First-Stage Retrieval. SIGIR 2024: 186-196 - [c204]Shuai Wang, Ekaterina Khramtsova, Shengyao Zhuang, Guido Zuccon:
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation. SIGIR 2024: 763-773 - [c203]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Leveraging LLMs for Unsupervised Dense Retriever Ranking. SIGIR 2024: 1307-1317 - [c202]Lukas Gienapp, Harrisen Scells, Niklas Deckers, Janek Bevendorff, Shuai Wang, Johannes Kiesel, Shahbaz Syed, Maik Fröbe, Guido Zuccon, Benno Stein, Matthias Hagen, Martin Potthast:
Evaluating Generative Ad Hoc Information Retrieval. SIGIR 2024: 1916-1929 - [c201]Xinyu Mao, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation. SIGIR 2024: 2357-2362 - [c200]Shuai Wang, Shengyao Zhuang, Guido Zuccon:
Large Language Models Based Stemming for Information Retrieval: Promises, Pitfalls and Failures. SIGIR 2024: 2492-2496 - [c199]Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection. SIGIR 2024: 2739-2743 - [c198]Linh Le, Minh-Tien Nguyen, Khai Phan Tran, Genghong Zhao, Xia Zhang, Guido Zuccon, Gianluca Demartini:
Stochastic Featurization for Active Learning. TAI4H 2024: 52-65 - [e6]Grace Hui Yang, Hongning Wang, Sam Han, Claudia Hauff, Guido Zuccon, Yi Zhang:
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024. ACM 2024 [contents] - [i60]Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Team IELAB at TREC Clinical Trial Track 2023: Enhancing Clinical Trial Retrieval with Neural Rankers and Large Language Models. CoRR abs/2401.01566 (2024) - [i59]Shuai Wang, Harrisen Scells, Shengyao Zhuang, Martin Potthast, Bevan Koopman, Guido Zuccon:
Zero-shot Generative Large Language Models for Systematic Review Screening Automation. CoRR abs/2401.06320 (2024) - [i58]Xinyu Mao, Bevan Koopman, Guido Zuccon:
A Reproducibility Study of Goldilocks: Just-Right Tuning of BERT for TAR. CoRR abs/2401.08104 (2024) - [i57]Shuyi Wang, Bing Liu, Guido Zuccon:
How to Forget Clients in Federated Online Learning to Rank? CoRR abs/2401.13410 (2024) - [i56]Chuting Yu, Hang Li, Ahmed Mourad, Bevan Koopman, Guido Zuccon:
TPRF: A Transformer-based Pseudo-Relevance Feedback Model for Efficient and Effective Retrieval. CoRR abs/2401.13509 (2024) - [i55]Shuai Wang, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search. CoRR abs/2401.17645 (2024) - [i54]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Leveraging LLMs for Unsupervised Dense Retriever Ranking. CoRR abs/2402.04853 (2024) - [i53]Shuai Wang, Shengyao Zhuang, Guido Zuccon:
Large Language Models for Stemming: Promises, Pitfalls and Failures. CoRR abs/2402.11757 (2024) - [i52]Shuai Wang, Ekaterina Khramtsova, Shengyao Zhuang, Guido Zuccon:
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation. CoRR abs/2402.11891 (2024) - [i51]Shengyao Zhuang, Bevan Koopman, Xiaoran Chu, Guido Zuccon:
Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems. CoRR abs/2402.12784 (2024) - [i50]Ferdinand Schlatt, Maik Fröbe, Harrisen Scells, Shengyao Zhuang, Bevan Koopman, Guido Zuccon, Benno Stein, Martin Potthast, Matthias Hagen:
Set-Encoder: Permutation-Invariant Inter-Passage Attention for Listwise Passage Re-Ranking with Cross-Encoders. CoRR abs/2404.06912 (2024) - [i49]Shengyao Zhuang, Xueguang Ma, Bevan Koopman, Jimmy Lin, Guido Zuccon:
PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval. CoRR abs/2404.18424 (2024) - [i48]Ferdinand Schlatt, Maik Fröbe, Harrisen Scells, Shengyao Zhuang, Bevan Koopman, Guido Zuccon, Benno Stein, Martin Potthast, Matthias Hagen:
A Systematic Investigation of Distilling Large Language Models into Cross-Encoders for Passage Re-ranking. CoRR abs/2405.07920 (2024) - [i47]Shuoqi Sun, Shengyao Zhuang, Shuai Wang, Guido Zuccon:
An Investigation of Prompt Variations for Zero-shot LLM-based Rankers. CoRR abs/2406.14117 (2024) - [i46]Xinyu Mao, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation. CoRR abs/2407.00635 (2024) - [i45]Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection. CoRR abs/2407.06685 (2024) - [i44]Ekaterina Khramtsova, Mahsa Baktashmotlagh, Guido Zuccon, Xi Wang, Mathieu Salzmann:
Source-Free Domain-Invariant Performance Prediction. CoRR abs/2408.02209 (2024) - 2023
- [j26]Mohamed A. Sharaf, Rischan Mafrur, Guido Zuccon:
Efficient Diversification for Recommending Aggregate Data Visualizations. IEEE Access 11: 62261-62280 (2023) - [j25]Linh Le, Gianluca Demartini, Guido Zuccon, Genghong Zhao, Xia Zhang:
Active learning with feature matching for clinical named entity recognition. Nat. Lang. Process. J. 4: 100015 (2023) - [j24]Hang Li, Ahmed Mourad, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Pseudo Relevance Feedback with Deep Language Models and Dense Retrievers: Successes and Pitfalls. ACM Trans. Inf. Syst. 41(3): 62:1-62:40 (2023) - [j23]Xue Li, Catherine Zou, Robert Boots, Sen Wang, Weitong Chen, Guido Zuccon:
Artificial Intelligence in Evidence-based Medicine: Challenges and Opportunities. World Sci. Annu. Rev. Artif. Intell. 1: 2330002:1-2330002:19 (2023) - [c197]Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh:
Convolutional Persistence as a Remedy to Neural Model Analysis. AISTATS 2023: 10839-10855 - [c196]Sebastian Cross, Guido Zuccon, Ahmed Mourad:
A Reproducibility Study of Question Retrieval for Clarifying Questions. ECIR (3) 2023: 35-50 - [c195]Shengyao Zhuang, Bing Liu, Bevan Koopman, Guido Zuccon:
Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking. EMNLP (Findings) 2023: 8807-8817 - [c194]Bevan Koopman, Guido Zuccon:
Dr ChatGPT tell me what I want to hear: How different prompts impact health answer correctness. EMNLP 2023: 15012-15022 - [c193]Wojciech Kusa, Guido Zuccon, Petr Knoth, Allan Hanbury:
Outcome-based Evaluation of Systematic Review Automation. ICTIR 2023: 125-133 - [c192]Joel Mackenzie, Shengyao Zhuang, Guido Zuccon:
Exploring the Representation Power of SPLADE Models. ICTIR 2023: 143-147 - [c191]Shuyi Wang, Guido Zuccon:
An Analysis of Untargeted Poisoning Attack and Defense Methods for Federated Online Learning to Rank Systems. ICTIR 2023: 215-224 - [c190]Guido Zuccon, Harrisen Scells, Shengyao Zhuang:
Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models. ICTIR 2023: 283-289 - [c189]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search? SIGIR 2023: 1426-1436 - [c188]Shengyao Zhuang, Linjun Shou, Guido Zuccon:
Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval. SIGIR 2023: 1827-1832 - [c187]Shuai Wang, Guido Zuccon:
Balanced Topic Aware Sampling for Effective Dense Retriever: A Reproducibility Study. SIGIR 2023: 2542-2551 - [c186]Guido Zuccon, Bevan Koopman, Razia Shaik:
ChatGPT Hallucinates when Attributing Answers. SIGIR-AP 2023: 46-51 - [c185]Shuai Wang, Harrisen Scells, Bevan Koopman, Martin Potthast, Guido Zuccon:
Generating Natural Language Queries for More Effective Systematic Review Screening Prioritisation. SIGIR-AP 2023: 73-83 - [c184]Sophia Althammer, Guido Zuccon, Sebastian Hofstätter, Suzan Verberne, Allan Hanbury:
Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection. SIGIR-AP 2023: 139-149 - [c183]Shengyao Zhuang, Linjun Shou, Jian Pei, Ming Gong, Houxing Ren, Guido Zuccon, Daxin Jiang:
Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval. SIGIR-AP 2023: 212-222 - [c182]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon:
Selecting which Dense Retriever to use for Zero-Shot Search. SIGIR-AP 2023: 223-233 - [c181]Bing Liu, Tiancheng Lan, Wen Hua, Guido Zuccon:
Dependency-aware Self-training for Entity Alignment. WSDM 2023: 796-804 - [c180]Hang Li, Bevan Koopman, Ahmed Mourad, Guido Zuccon:
AgAsk: A Conversational Search Agent for Answering Agricultural Questions. WSDM 2023: 1140-1143 - [c179]Shuai Wang, Hang Li, Guido Zuccon:
MeSH Suggester: A Library and System for MeSH Term Suggestion for Systematic Review Boolean Query Construction. WSDM 2023: 1176-1179 - [i43]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search? CoRR abs/2302.03495 (2023) - [i42]Guido Zuccon, Bevan Koopman:
Dr ChatGPT, tell me what I want to hear: How prompt knowledge impacts health answer correctness. CoRR abs/2302.13793 (2023) - [i41]Shengyao Zhuang, Linjun Shou, Jian Pei, Ming Gong, Houxing Ren, Guido Zuccon, Daxin Jiang:
Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval. CoRR abs/2304.08138 (2023) - [i40]Shengyao Zhuang, Linjun Shou, Guido Zuccon:
Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval. CoRR abs/2305.03950 (2023) - [i39]Guido Zuccon, Harrisen Scells, Shengyao Zhuang:
Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models. CoRR abs/2306.16668 (2023) - [i38]Joel Mackenzie, Shengyao Zhuang, Guido Zuccon:
Exploring the Representation Power of SPLADE Models. CoRR abs/2306.16680 (2023) - [i37]Wojciech Kusa, Guido Zuccon, Petr Knoth, Allan Hanbury:
Outcome-based Evaluation of Systematic Review Automation. CoRR abs/2306.17614 (2023) - [i36]Shuyi Wang, Guido Zuccon:
An Analysis of Untargeted Poisoning Attack and Defense Methods for Federated Online Learning to Rank Systems. CoRR abs/2307.01565 (2023) - [i35]Shuai Wang, Harrisen Scells, Martin Potthast, Bevan Koopman, Guido Zuccon:
Generating Natural Language Queries for More Effective Systematic Review Screening Prioritisation. CoRR abs/2309.05238 (2023) - [i34]Sophia Althammer, Guido Zuccon, Sebastian Hofstätter, Suzan Verberne, Allan Hanbury:
Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection. CoRR abs/2309.06131 (2023) - [i33]Guido Zuccon, Bevan Koopman, Razia Shaik:
ChatGPT Hallucinates when Attributing Answers. CoRR abs/2309.09401 (2023) - [i32]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon:
Selecting which Dense Retriever to use for Zero-Shot Search. CoRR abs/2309.09403 (2023) - [i31]Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, Guido Zuccon:
A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models. CoRR abs/2310.09497 (2023) - [i30]Shengyao Zhuang, Bing Liu, Bevan Koopman, Guido Zuccon:
Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking. CoRR abs/2310.13243 (2023) - [i29]Lukas Gienapp, Harrisen Scells, Niklas Deckers, Janek Bevendorff, Shuai Wang, Johannes Kiesel, Shahbaz Syed, Maik Fröbe, Guido Zuccon, Benno Stein, Matthias Hagen, Martin Potthast:
Evaluating Generative Ad Hoc Information Retrieval. CoRR abs/2311.04694 (2023) - [i28]Rischan Mafrur, Mohamed A. Sharaf, Guido Zuccon:
VizPut: Insight-Aware Imputation of Incomplete Data for Visualization Recommendation. CoRR abs/2311.07926 (2023) - 2022
- [j22]Shengyao Zhuang, Zhihao Qiao, Guido Zuccon:
Reinforcement online learning to rank with unbiased reward shaping. Inf. Retr. J. 25(4): 386-413 (2022) - [j21]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Automated MeSH term suggestion for effective query formulation in systematic reviews literature search. Intell. Syst. Appl. 16: 200141 (2022) - [c178]Hang Li, Shengyao Zhuang, Xueguang Ma, Jimmy Lin, Guido Zuccon:
Pseudo-Relevance Feedback with Dense Retrievers in Pyserini. ADCS 2022: 1:1-1:6 - [c177]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Neural Rankers for Effective Screening Prioritisation in Medical Systematic Review Literature Search. ADCS 2022: 4:1-4:10 - [c176]Gineke Wiggers, Guido Zuccon:
The Task: Distinguishing Tasks and Sessions in Legal Information Retrieval. ADCS 2022: 5:1-5:4 - [c175]Shengyao Zhuang, Xinyu Mao, Guido Zuccon:
Robustness of Neural Rankers to Typos: A Comparative Study. ADCS 2022: 6:1-6:6 - [c174]Sitthichoke Subpaiboonkit, Xue Li, Xin Zhao, Guido Zuccon:
Causality Discovery Based on Combined Causes and Multiple Causes in Drug-Drug Interaction. ADMA (1) 2022: 53-66 - [c173]Linh Le, Guido Zuccon, Genghong Zhao, Gianluca Demartini, Xia Zhang:
Leveraging Semantic Type Dependencies for Medical Named Entity Recognition. AMIA 2022 - [c172]Bing Liu, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang:
High-quality Task Division for Large-scale Entity Alignment. CIKM 2022: 1258-1268 - [c171]Ismail Sabei, Ahmed Mourad, Guido Zuccon:
SCC - A Test Collection for Search in Chat Conversations. CIKM 2022: 4429-4433 - [c170]Guido Zuccon:
Pretrained Language Models Rankers on Private Data: Is Online and Federated Learning the Solution? (short paper). DESIRES 2022: 35-39 - [c169]Hang Li, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon:
Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback: A Reproducibility Study. ECIR (1) 2022: 599-612 - [c168]Shuai Wang, Harrisen Scells, Ahmed Mourad, Guido Zuccon:
Seed-Driven Document Ranking for Systematic Reviews: A Reproducibility Study. ECIR (1) 2022: 686-700 - [c167]Bing Liu, Harrisen Scells, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang:
Guiding Neural Entity Alignment with Compatibility. EMNLP 2022: 491-504 - [c166]Harrisen Scells, Connor Forbes, Justin Clark, Bevan Koopman, Guido Zuccon:
The Impact of Query Refinement on Systematic Review Literature Search: A Query Log Analysis. ICTIR 2022: 34-42 - [c165]Shengyao Zhuang, Hang Li, Guido Zuccon:
Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach. SIGIR 2022: 18-28 - [c164]Shengyao Zhuang, Guido Zuccon:
CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos. SIGIR 2022: 1444-1454 - [c163]Hang Li, Ahmed Mourad, Bevan Koopman, Guido Zuccon:
How Does Feedback Signal Quality Impact Effectiveness of Pseudo Relevance Feedback for Passage Retrieval. SIGIR 2022: 2154-2158 - [c162]Hang Li, Shuai Wang, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon:
To Interpolate or not to Interpolate: PRF, Dense and Sparse Retrievers. SIGIR 2022: 2495-2500 - [c161]Shuyi Wang, Guido Zuccon:
Is Non-IID Data a Threat in Federated Online Learning to Rank? SIGIR 2022: 2801-2813 - [c160]Harrisen Scells, Shengyao Zhuang, Guido Zuccon:
Reduce, Reuse, Recycle: Green Information Retrieval Research. SIGIR 2022: 2825-2837 - [c159]Shuai Wang, Harrisen Scells, Justin Clark, Bevan Koopman, Guido Zuccon:
From Little Things Big Things Grow: A Collection with Seed Studies for Medical Systematic Review Literature Search. SIGIR 2022: 3176-3186 - [c158]Shengyao Zhuang, Guido Zuccon:
Asyncval: A Toolkit for Asynchronously Validating Dense Retriever Checkpoints During Training. SIGIR 2022: 3235-3239 - [c157]Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh:
Rethinking Persistent Homology For Visual Recognition. TAG-ML 2022: 206-215 - [i27]Shengyao Zhuang, Zhihao Qiao, Guido Zuccon:
Reinforcement Online Learning to Rank with Unbiased Reward Shaping. CoRR abs/2201.01534 (2022) - [i26]Daniel Locke, Guido Zuccon:
Case law retrieval: problems, methods, challenges and evaluations in the last 20 years. CoRR abs/2202.07209 (2022) - [i25]Shengyao Zhuang, Guido Zuccon:
Asyncval: A Toolkit for Asynchronously Validating Dense Retriever Checkpoints during Training. CoRR abs/2202.12510 (2022) - [i24]Shengyao Zhuang, Guido Zuccon:
CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos. CoRR abs/2204.00716 (2022) - [i23]Shengyao Zhuang, Hang Li, Guido Zuccon:
Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach. CoRR abs/2204.00718 (2022) - [i22]Shuai Wang, Harrisen Scells, Justin Clark, Bevan Koopman, Guido Zuccon:
From Little Things Big Things Grow: A Collection with Seed Studies for Medical Systematic Review Literature Search. CoRR abs/2204.03096 (2022) - [i21]Shuyi Wang, Guido Zuccon:
Is Non-IID Data a Threat in Federated Online Learning to Rank? CoRR abs/2204.09272 (2022) - [i20]Hang Li, Shuai Wang, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon:
To Interpolate or not to Interpolate: PRF, Dense and Sparse Retrievers. CoRR abs/2205.00235 (2022) - [i19]Hang Li, Ahmed Mourad, Bevan Koopman, Guido Zuccon:
How does Feedback Signal Quality Impact Effectiveness of Pseudo Relevance Feedback for Passage Retrieval? CoRR abs/2205.05888 (2022) - [i18]Shengyao Zhuang, Houxing Ren, Linjun Shou, Jian Pei, Ming Gong, Guido Zuccon, Daxin Jiang:
Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation. CoRR abs/2206.10128 (2022) - [i17]Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh:
Rethinking Persistent Homology for Visual Recognition. CoRR abs/2207.04220 (2022) - [i16]Bing Liu, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang:
High-quality Task Division for Large-scale Entity Alignment. CoRR abs/2208.10366 (2022) - [i15]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Automated MeSH Term Suggestion for Effective Query Formulation in Systematic Reviews Literature Search. CoRR abs/2209.08687 (2022) - [i14]Bing Liu, Harrisen Scells, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang:
Guiding Neural Entity Alignment with Compatibility. CoRR abs/2211.15833 (2022) - [i13]Bing Liu, Tiancheng Lan, Wen Hua, Guido Zuccon:
Dependency-aware Self-training for Entity Alignment. CoRR abs/2211.16101 (2022) - [i12]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Neural Rankers for Effective Screening Prioritisation in Medical Systematic Review Literature Search. CoRR abs/2212.09017 (2022) - [i11]Shuai Wang, Hang Li, Guido Zuccon:
MeSH Suggester: A Library and System for MeSH Term Suggestion for Systematic Review Boolean Query Construction. CoRR abs/2212.09018 (2022) - [i10]Bevan Koopman, Ahmed Mourad, Hang Li, Anton van der Vegt, Shengyao Zhuang, Simon Gibson, Yash Dang, David Lawrence, Guido Zuccon:
AgAsk: An Agent to Help Answer Farmer's Questions From Scientific Documents. CoRR abs/2212.10762 (2022) - 2021
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