From the 1 of 9 linked papers with an AI index.
8 citations · 9 across the 6 of their papers we have counts for
4 papers · 1 filter
Verbalizing LLMs' assumptions to explain and control sycophancy
Myra Cheng, Isabel Sieh, Humishka Zope +7
LLMs can be socially sycophantic, affirming users when they ask questions like "am I in the wrong?" rather than providing genuine assessment. We hypothesize that this behavior aris…
Multi-turn Evaluation of Anthropomorphic Behaviours in Large Language Models
Lujain Ibrahim, Canfer Akbulut, Rasmi Elasmar +7
The tendency of users to anthropomorphise large language models (LLMs) is of growing interest to AI developers, researchers, and policy-makers. Here, we present a novel method for…
ELEPHANT: Measuring and understanding social sycophancy in LLMs
Myra Cheng, Sunny Yu, Cinoo Lee +3
LLMs are known to exhibit sycophancy: agreeing with and flattering users, even at the cost of correctness. Prior work measures sycophancy only as direct agreement with users' expli…
Thinking beyond the anthropomorphic paradigm benefits LLM research
Lujain Ibrahim, Myra Cheng
Anthropomorphism, or the attribution of human traits to technology, is an automatic and unconscious response that occurs even in those with advanced technical expertise. In this po…