58 citations · 219 across the 25 of their papers we have counts for
25 papers
SearchLog: A Web Browser Extension for Capturing Search Logs in Laboratory Studies
Jiaman He, Riccardo Xia, Dana McKay +2
Natural search logs are valuable for studying search behavior in information seeking settings. We present SearchLog, an easy-to-install web browser extension for collecting natural…
RMIT-ADM+S at the MMU-RAG NeurIPS 2025 Competition
Kun Ran, Marwah Alaofi, Danula Hettiachchi +9
This paper presents the award-winning RMIT-ADM+S system for the Text-to-Text track of the NeurIPS~2025 MMU-RAG Competition. We introduce Routing-to-RAG (R2RAG), a research-focused…
Characterizing Personality from Eye-Tracking: The Role of Gaze and Its Absence in Interactive Search Environments
Jiaman He, Marta Micheli, Damiano Spina +3
Personality traits influence how individuals engage, behave, and make decisions during the information-seeking process. However, few studies have linked personality to observable s…
Can We Hide Machines in the Crowd? Quantifying Equivalence in LLM-in-the-loop Annotation Tasks
Jiaman He, Zikang Leng, Dana McKay +2
Many evaluations of large language models (LLMs) in text annotation focus primarily on the correctness of the output, typically comparing model-generated labels to human-annotated…
ISMIE: A Framework to Characterize Information Seeking in Modern Information Environments
Shuoqi Sun, Danula Hettiachchi, Damiano Spina
The modern information environment (MIE) is increasingly complex, shaped by a wide range of techniques designed to satisfy users' information needs. Information seeking (IS) models…
SenseSeek Dataset: Multimodal Sensing to Study Information Seeking Behaviors
Kaixin Ji, Danula Hettiachchi, Falk Scholer +2
Information processing tasks involve complex cognitive mechanisms that are shaped by various factors, including individual goals, prior experience, and system environments. Underst…
RMIT-ADM+S at the SIGIR 2025 LiveRAG Challenge
Kun Ran, Shuoqi Sun, Khoi Nguyen Dinh Anh +2
This paper presents the RMIT--ADM+S winning system in the SIGIR 2025 LiveRAG Challenge. Our Generation-Retrieval-Augmented Generation (G-RAG) approach generates a hypothetical answ…
Characterising Topic Familiarity and Query Specificity Using Eye-Tracking Data
Jiaman He, Zikang Leng, Dana McKay +2
Eye-tracking data has been shown to correlate with a user's knowledge level and query formulation behaviour. While previous work has focused primarily on eye gaze fixations for att…
Information Retrieval for Climate Impact
Maarten de Rijke, Bart van den Hurk, Flora Salim +28
The purpose of the MANILA24 Workshop on information retrieval for climate impact was to bring together researchers from academia, industry, governments, and NGOs to identify and di…
Control Search Rankings, Control the World: What is a Good Search Engine?
Simon Coghlan, Hui Xian Chia, Falk Scholer +1
This paper examines the ethical question, 'What is a good search engine?' Since search engines are gatekeepers of global online information, it is vital they do their job ethically…
Can Users Detect Biases or Factual Errors in Generated Responses in Conversational Information-Seeking?
Weronika Łajewska, Krisztian Balog, Damiano Spina +1
Information-seeking dialogues span a wide range of questions, from simple factoid to complex queries that require exploring multiple facets and viewpoints. When performing explorat…
Towards Investigating Biases in Spoken Conversational Search
Sachin Pathiyan Cherumanal, Falk Scholer, Johanne R. Trippas +1
Voice-based systems like Amazon Alexa, Google Assistant, and Apple Siri, along with the growing popularity of OpenAI's ChatGPT and Microsoft's Copilot, serve diverse populations, i…
Everything We Hear: Towards Tackling Misinformation in Podcasts
Sachin Pathiyan Cherumanal, Ujwal Gadiraju, Damiano Spina
Advances in generative AI, the proliferation of large multimodal models (LMMs), and democratized open access to these technologies have direct implications for the production and d…
Characterizing Information Seeking Processes with Multiple Physiological Signals
Kaixin Ji, Danula Hettiachchi, Flora D. Salim +2
Information access systems are getting complex, and our understanding of user behavior during information seeking processes is mainly drawn from qualitative methods, such as observ…
Explainability for Transparent Conversational Information-Seeking
Weronika Łajewska, Damiano Spina, Johanne Trippas +1
The increasing reliance on digital information necessitates advancements in conversational search systems, particularly in terms of information transparency. While prior research i…
Towards Detecting and Mitigating Cognitive Bias in Spoken Conversational Search
Kaixin Ji, Sachin Pathiyan Cherumanal, Johanne R. Trippas +4
Instruments such as eye-tracking devices have contributed to understanding how users interact with screen-based search engines. However, user-system interactions in audio-only chan…
Walert: Putting Conversational Search Knowledge into Action by Building and Evaluating a Large Language Model-Powered Chatbot
Sachin Pathiyan Cherumanal, Lin Tian, Futoon M. Abushaqra +7
Creating and deploying customized applications is crucial for operational success and enriching user experiences in the rapidly evolving modern business world. A prominent facet of…
Designing and Evaluating Presentation Strategies for Fact-Checked Content
Danula Hettiachchi, Kaixin Ji, Jenny Kennedy +5
With the rapid growth of online misinformation, it is crucial to have reliable fact-checking methods. Recent research on finding check-worthy claims and automated fact-checking hav…
AI-UPV at EXIST 2023 -- Sexism Characterization Using Large Language Models Under The Learning with Disagreements Regime
Angel Felipe Magnossão de Paula, Giulia Rizzi, Elisabetta Fersini +1
With the increasing influence of social media platforms, it has become crucial to develop automated systems capable of detecting instances of sexism and other disrespectful and hat…
Mitigating Negative Transfer with Task Awareness for Sexism, Hate Speech, and Toxic Language Detection
Angel Felipe Magnossão de Paula, Paolo Rosso, Damiano Spina
This paper proposes a novelty approach to mitigate the negative transfer problem. In the field of machine learning, the common strategy is to apply the Single-Task Learning approac…
Examining the Impact of Uncontrolled Variables on Physiological Signals in User Studies for Information Processing Activities
Kaixin Ji, Damiano Spina, Danula Hettiachchi +2
Physiological signals can potentially be applied as objective measures to understand the behavior and engagement of users interacting with information access systems. However, the…
The Many Dimensions of Truthfulness: Crowdsourcing Misinformation Assessments on a Multidimensional Scale
Michael Soprano, Kevin Roitero, David La Barbera +4
Recent work has demonstrated the viability of using crowdsourcing as a tool for evaluating the truthfulness of public statements. Under certain conditions such as: (1) having a bal…
Can the Crowd Judge Truthfulness? A Longitudinal Study on Recent Misinformation about COVID-19
Kevin Roitero, Michael Soprano, Beatrice Portelli +6
Recently, the misinformation problem has been addressed with a crowdsourcing-based approach: to assess the truthfulness of a statement, instead of relying on a few experts, a crowd…
The COVID-19 Infodemic: Can the Crowd Judge Recent Misinformation Objectively?
Kevin Roitero, Michael Soprano, Beatrice Portelli +5
Misinformation is an ever increasing problem that is difficult to solve for the research community and has a negative impact on the society at large. Very recently, the problem has…