… in preference data is responsible for sycophancy in AI assistants, we then analyze whether
sycophancy increases when optimizing language model responses using preference models …

… sycophantic behavior varies significantly among models, our analysis reveals the severe
deficiency of all LVLMs in resilience of sycophancy … (LQCD), a model-agnostic method focusing …

… This thesis posits that large language models (LLMs) exhibiting sycophantic behaviour will
demonstrate consistent results across two testing conditions: explicit testing, where political …

… Given that sycophancy is often linked to human 5 feedback training mechanisms, this study
… whether sycophantic tendencies 6 negatively impact user trust in large language models or, …

… This work leverages path patching to find circuits on models with more than 7B parameters,
which shows the scalability of the method. We conceptualize the language model as a …

… uncertainty may be a promising avenue for annotators to identify sycophancy. Likewise, …
sycophancy bias (� 4.2) because language models effectively condition on hedging language. …

… 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 …

… Our results contribute to a more nuanced understanding of sycophancy, steerability, and
political bias in LLM output evaluations. Our study also emphasizes the context dependency of …

… As LLMs expand into other modalities like vision-language models (VLMs), the saying “…
exhibit sycophancy when given images as evidence? This paper presents the first sycophancy …

… 5) Additionally, we find a positive correlation between sycophancy and adversarial actuality.
Models with lower sycophancy levels are more effective in identifying and highlighting …