preprint وصول مفتوح

Citations and Trust in LLM Generated Responses

  • arXiv (Cornell University)
  • Cornell University
Research footprint

At a glance

الاستشهادات
1
المراجع
0
Comments
0
Paper overview

Abstract

Question answering systems are rapidly advancing, but their opaque nature may impact user trust. We explored trust through an anti-monitoring framework, where trust is predicted to be correlated with presence of citations and inversely related to checking citations. We tested this hypothesis with a live question-answering experiment that presented text responses generated using a commercial Chatbot along with varying citations (zero, one, or five), both relevant and random, and recorded if participants checked the citations and their self-reported trust in the generated responses. We found a significant increase in trust when citations were present, a result that held true even when the citations were random; we also found a significant decrease in trust when participants checked the citations. These results highlight the importance of citations in enhancing trust in AI-generated content.

Record transparency

Publication details

DOI
10.48550/arxiv.2501.01303
OpenAlex
W4406033389
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
Last metadata update
المجتمع

Comments

تسجيل الدخول للانضمام إلى النقاش.

  1. لا توجد تعليقات بعد. ابدأ النقاش.