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2024 Conference Publication CoLAL: Co-learning active learning for text classificationLe, Linh, Zhao, Genghong, Zhang, Xia, Zuccon, Guido and Demartini, Gianluca (2024). CoLAL: Co-learning active learning for text classification. Thirty-Eighth AAAI Conference on Artificial Intelligence, Vancouver, BC Canada, 20–27 February 2024. Washington, DC United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v38i12.29235 |
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2022 Conference Publication Preferences on a budget: prioritizing document pairs when crowdsourcing relevance judgmentsRoitero, Kevin, Checco, Alessandro, Mizzaro, Stefano and Demartini, Gianluca (2022). Preferences on a budget: prioritizing document pairs when crowdsourcing relevance judgments. ACM Web Conference, Virtual/Lyon, France, 25-29 April 2022. New York, United States: Association for Computing Machinery. doi: 10.1145/3485447.3511960 |
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2020 Conference Publication Can the crowd identify misinformation objectively?: The effects of judgment scale and assessor's backgroundRoitero, Kevin, Soprano, Michael, Fan, Shaoyang, Spina, Damiano, Mizzaro, Stefano and Demartini, Gianluca (2020). Can the crowd identify misinformation objectively?: The effects of judgment scale and assessor's background. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, China, 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401112 |
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2020 Conference Publication On understanding data worker interaction behaviorsHan, Lei, Chen, Tianwa, Demartini, Gianluca, Indulska, Marta and Sadiq, Shazia (2020). On understanding data worker interaction behaviors. SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval, Virtual Event China, July 2020. New York, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401059 |
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2019 Conference Publication Scalpel-CD: leveraging crowdsourcing and deep probabilistic modeling for debugging noisy training dataYang, Jie, Demartini, Gianluca, Smirnova, Alisa, Lu, Yuan, Yang, Dingqi and Cudré-Mauroux, Philippe (2019). Scalpel-CD: leveraging crowdsourcing and deep probabilistic modeling for debugging noisy training data. World Wide Web Conference (WWW), San Francisco, CA, United States, 13-17 May 2019. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3308558.3313599 |
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2015 Conference Publication The dynamics of micro-task crowdsourcing: the case of amazon MTurkDifallah, Djellel Eddine, Catasta, Michele, Demartini, Gianluca, Ipeirotis, Panagiotis G. and Cudré-Mauroux, Philippe (2015). The dynamics of micro-task crowdsourcing: the case of amazon MTurk. 24th International Conference on World Wide Web, WWW 2015, Florence, Italy, 18 - 22 May 2015. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2736277.2741685 |
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2015 Conference Publication Understanding malicious behavior in crowdsourcing platforms: the case of online surveysGadiraju, Ujwal, Kawase, Ricardo, Dietze, Stefan and Demartini, Gianluca (2015). Understanding malicious behavior in crowdsourcing platforms: the case of online surveys. 33rd Annual CHI Conference on Human Factors in Computing Systems - CHI'15, Seoul, South Korea, 18 - 23 April 2015. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2702123.2702443 |
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2025 Conference Publication Exploring Wikipedia Gender Diversity Over Time — The Wikipedia Gender Dashboard (WGD)Yunus, Yahya, Chen, Tianwa and Demartini, Gianluca (2025). Exploring Wikipedia Gender Diversity Over Time — The Wikipedia Gender Dashboard (WGD). New York, NY, USA: ACM. doi: 10.1145/3701716.3715175 |
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2025 Conference Publication Preaching to the ChoIR: lessons IR should share with AIDemartini, Gianluca, Hauff, Claudia, Lease, Matthew, Mizzaro, Stefano, Roitero, Kevin, Sanderson, Mark, Scholer, Falk, Shah, Chirag, Spina, Damiano, Thomas, Paul, de Vries, Arjen P. and Zuccon, Guido (2025). Preaching to the ChoIR: lessons IR should share with AI. ICTIR '25: International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval, Padua, Italy, 18 July 2025. New York, NY USA: ACM. doi: 10.1145/3731120.3744612 |
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2025 Conference Publication How do experts make sense of integrated process models?Chen, Tianwa, Weber, Barbara, Shanks, Graeme, Demartini, Gianluca, Indulska, Marta and Sadiq, Shazia (2025). How do experts make sense of integrated process models?. 37th International Conference, CAiSE 2025, Vienna, Austria, 16-20 June 2025. Cham, Switzerland: Springer Switzerland. doi: 10.1007/978-3-031-94571-7_1 |
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2025 Conference Publication Perception of Visual Content: Differences Between Humans and Foundation ModelsPratama, Nardiena A., Fan, Shaoyang and Demartini, Gianluca (2025). Perception of Visual Content: Differences Between Humans and Foundation Models. Nineteenth International AAAI Conference on Web and Social Media, Copenhagen, Denmark, 23-26 June 2025. Washington, DC United States: Association for the Advancement of Artificial Intelligence (AAAI). doi: 10.1609/icwsm.v19i1.35891 |
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2025 Conference Publication LLM-Based Semantic Augmentation for Harmful Content DetectionMeguellati, Elyas, Zeghina, Assaad, Sadiq, Shazia and Demartini, Gianluca (2025). LLM-Based Semantic Augmentation for Harmful Content Detection. Nineteenth International AAAI Conference on Web and Social Media, Copenhagen, Denmark, 23-26 June 2025. Washington, DC United States: Association for the Advancement of Artificial Intelligence (AAAI). doi: 10.1609/icwsm.v19i1.35868 |
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2025 Conference Publication Bias in Humans and AI - What To Do About It?Demartini, Gianluca (2025). Bias in Humans and AI - What To Do About It?. WWW '25: The ACM Web Conference 2025, Sydney, NSW Australia, 28 April - 2 May 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3701716.3719143 |
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2025 Conference Publication Are Large Language Models Good Data Preprocessors?Meguellati, Elyas, Pratama, Nardiena, Sadiq, Shazia and Demartini, Gianluca (2025). Are Large Language Models Good Data Preprocessors?. WWW '25: The ACM Web Conference 2025, Sydney, NSW Australia, 28 April - 2 May 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3701716.3717568 |
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2025 Conference Publication Mapping and influencing the political ideology of large language models using synthetic personasBernardelle, Pietro, Fröhling, Leon, Civelli, Stefano, Lunardi, Riccardo, Roitero, Kevin and Demartini, Gianluca (2025). Mapping and influencing the political ideology of large language models using synthetic personas. WWW '25: The ACM Web Conference 2025, Sydney, NSW Australia, 28 April-2 May 2025. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3701716.3715578 |
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2025 Conference Publication BiasNavi: LLM-Empowered Data Bias ManagementYu, Junliang, Huynh, Jay Thai Duong, Fan, Shaoyang, Demartini, Gianluca, Chen, Tong, Yin, Hongzhi and Sadiq, Shazia (2025). BiasNavi: LLM-Empowered Data Bias Management. ACM Web Conference 2025 (WWW'25), Sydney, NSW, Australia, 28 April - 2 May 2025. New York, NY, United States: ACM. doi: 10.1145/3701716.3715169 |
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2025 Conference Publication The Impact of Persona-based Political Perspectives on Hateful Content DetectionCivelli, Stefano, Bernardelle, Pietro and Demartini, Gianluca (2025). The Impact of Persona-based Political Perspectives on Hateful Content Detection. WWW '25: The ACM Web Conference 2025, Sydney, NSW Australia, 28 April - 2 May 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3701716.3718383 |
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2025 Conference Publication Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily AssistantHe, Gaole, Demartini, Gianluca and Gadiraju, Ujwal (2025). Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistant. 2025 Conference on Human Factors in Computing Systems-CHI, Yokohama Japan, Apr 26-May 01, 2025. New York, NY, USA: ACM. doi: 10.1145/3706598.3713218 |
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2025 Conference Publication Fast Synthetic Data Generation for Case-Specific Entity Extraction in Criminal InvestigationsSkipanes, Mads, Pratama, Nardiena, Porter, Kyle and Demartini, Gianluca (2025). Fast Synthetic Data Generation for Case-Specific Entity Extraction in Criminal Investigations. DFDS 2025: Digital Forensics Doctoral Symposium, Brno, Czech Republic, 1 April 2025. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3712716.3712719 |
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2025 Conference Publication Enhancing Criminal Investigation Analysis with Summarization and Memory-based Retrieval-Augmented Generation: A Comprehensive Evaluation of Real Case DataSkipanes, Mads, Jørgensen, Tollef Emil, Porter, Kyle, Demartini, Gianluca and Yayilgan, Sule Yildirim (2025). Enhancing Criminal Investigation Analysis with Summarization and Memory-based Retrieval-Augmented Generation: A Comprehensive Evaluation of Real Case Data. Association for Computational Linguistics (ACL). |
