5 papers
Personalized to Persuade: The Effects of Contextualization and Warmth on Trust and Reliance in Conversational AI
Mert Yazan, Suzan Verberne, Frederik Bungaran Ishak Situmeang
Artificial Intelligence (AI) agents personalize their responses by tailoring explanations to users' backgrounds, interests, and prior interactions, referred to as contextualization…
Search for Coverage: Learning Coverage-Aware Retrieval with Augmented Sub-Question Answerability
Jia-Huei Ju, Eugene Yang, Trevor Adriaanse +2
Long-form Retrieval-Augmented Generation (RAG) brings the challenge of coverage-based ranking, because ranking methods must ensure the inclusion of comprehensive relevant nuggets (…
The Decision to Verify: How Warmth and User Characteristics Shape Reliance on Conversational Agents for Information Search
Mert Yazan, Frederik Bungaran Ishak Situmeang, Suzan Verberne
Conversational artificial intelligence (AI) provides an efficient and convenient gateway to information access. However, it can cause overreliance when users blindly trust AI and a…
Personality over Precision: Exploring the Influence of Human-Likeness on ChatGPT Use for Search
Mert Yazan, Frederik Bungaran Ishak Situmeang, Suzan Verberne
Conversational search interfaces, like ChatGPT, offer an interactive, personalized, and engaging user experience compared to traditional search. On the downside, they are prone to…
Improving RAG for Personalization with Author Features and Contrastive Examples
Mert Yazan, Suzan Verberne, Frederik Situmeang
Personalization with retrieval-augmented generation (RAG) often fails to capture fine-grained features of authors, making it hard to identify their unique traits. To enrich the RAG…