This study explores the sycophantic tendencies of Large Language Models
(LLMs), where these models tend to provide answers that match what users want
to hear, even if they are not entirely correct. The motivation behind this
exploration stems from the common behavior observed in individuals searching
the internet for facts with partial or misleading knowledge. Similar to using
web search engines,
Related papers
Ranked by semantic similarity — how closely each paper's abstract matches this one (100% = near-identical topic).