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Found 11 papers, 2 papers with code
Can Stories Help LLMs Reason? Curating Information Space Through Narrative
Narratives are widely recognized as a powerful tool for structuring information and facilitating comprehension of complex ideas in various domains such as science communication.
Towards Investigating Biases in Spoken Conversational Search
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, including visually impaired and low-literacy communities.
Towards Detecting and Mitigating Cognitive Bias in Spoken Conversational Search
Instruments such as eye-tracking devices have contributed to understanding how users interact with screen-based search engines.
Online and Offline Evaluation in Search Clarification
The effectiveness of clarification question models in engaging users within search systems is currently constrained, casting doubt on their overall usefulness.
Walert: Putting Conversational Search Knowledge into Action by Building and Evaluating a Large Language Model-Powered Chatbot
Creating and deploying customized applications is crucial for operational success and enriching user experiences in the rapidly evolving modern business world.
MIMICS-Duo: Offline & Online Evaluation of Search Clarification
Asking clarification questions is an active area of research; however, resources for training and evaluating search clarification methods are not sufficient.
Conversational Information Seeking
Conversational information seeking (CIS) is concerned with a sequence of interactions between one or more users and an information system.
Conversational Question Answering
Conversational Recommendation
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Towards a Model for Spoken Conversational Search
Conversation is the natural mode for information exchange in daily life, a spoken conversational interaction for search input and output is a logical format for information seeking.
Informing the Design of Spoken Conversational Search
We compared the interactions to existing models of search behaviour.
User Intent Prediction in Information-seeking Conversations
Due to the limited communication bandwidth in conversational search, it is important for conversational assistants to accurately detect and predict user intent in information-seeking conversations.
Analyzing and Characterizing User Intent in Information-seeking Conversations
Understanding and characterizing how people interact in information-seeking conversations is crucial in developing conversational search systems.
