Sweet Talkers: How Query Formulation Shapes Sycophancy in Romantic Relationship Advice
Large language models (LLMs) are increasingly used for emotional support and relationship advice, where a model's tendency to preserve a user's face can inadvertently reinforce harmful interpersonal behaviors. To systematically examine this risk, we developed the Romantic Relationship Advice-Seeking Prompts (RRASP) dataset of 2,400 prompts across five relationship themes and evaluated social sycophancy using the ELEPHANT framework on two consumer-facing models, GPT-5 Mini and Gemini 3 Flash. Contrary to our initial hypothesis, grammatical mood alone did not produce systematic differences in sycophantic behavior, suggesting that what a user implies matters more than how they phrase it. Ins...
| Authors | Helena Choi, Edric Castel Hao, Karl Bautista et al. |
|---|---|
| Primary category | cs.CL |
| Published | 12 September 2026 |
| Last updated at source | 12 September 2026 |
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