Reporting Under Pressure: Separating Factual and Tonal Sycophancy in LLM Statistical Analysis

Excerpt

arXiv:2609.27756v1 Announce Type: cross Abstract: Large language models are increasingly asked to analyze data and report what the results mean, a task distinct from the belief- or preference-alignment settings studied in most sycophancy research. We test whether editorial framing in the prompt, ranging from a neutral request to an explicit instruction to search exhaustively for reasons to discredit or to support a finding, changes not just the tone but the substance of a model's report. Across