activity
20182026
most citedAnalyzing and Characterizing User Intent in Information-seeking Conversations

108 citations · 293 across the 20 of their papers we have counts for

collaborators
Showing 2024Show all

7 papers · 1 filter

cs.CL2024★ 2 cited

Can Stories Help LLMs Reason? Curating Information Space Through Narrative

Vahid Sadiri Javadi, Johanne R. Trippas, Yash Kumar Lal +1

Narratives are widely recognized as a powerful tool for structuring information and facilitating comprehension of complex ideas in various domains such as science communication. Th…

cs.HC2024★ 2 cited

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…

cs.HC2024

Understanding Modality Preferences in Search Clarification

Leila Tavakoli, Giovanni Castiglia, Federica Calo +3

This study is the first attempt to explore the impact of clarification question modality on user preference in search engines. We introduce the multi-modal search clarification dat…

cs.IR2024★ 17 cited

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…

cs.HC2024★ 8 cited

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…

cs.IR2024

Online and Offline Evaluation in Search Clarification

Leila Tavakoli, Johanne R. Trippas, Hamed Zamani +2

The effectiveness of clarification question models in engaging users within search systems is currently constrained, casting doubt on their overall usefulness. To improve the perfo…

cs.IR2024★ 11 cited

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…