No AI summary available for this article.
Why It Matters
Large language models (LLMs) may abandon correct positions when users push back, exhibiting a failure mode known as sycophancy.
Provenance
Discovered via ArXiv and published by ArXiv.
Key Claims
Original description
Large language models (LLMs) may abandon correct positions when users push back, exhibiting a failure mode known as sycophancy. Existing evaluations typically use short, pre-specified conversations and may therefore miss failures that emerge under sustained, adaptive disagreement. We introduce SPINE, a benchmark in which an LLM proxy plays a persistent but mistaken user and adaptively challenges a target model for up to 25 turns. We evaluate four production systems and three Olmo3-7b variants on 100 false-presupposition and 100 unethical-query items. Our experimental results show that collapse...
Discovered via ArXiv
Research papers and preprints from arXiv.
Publisher: arxiv.org
ID: http://arxiv.org/abs/2609.09090v1 · Indexed about 1 hour ago