@misc{warmth-sycophancy,
  title = {Training language models to be warm can reduce accuracy and increase sycophancy},
  url = {https://www.nature.com/articles/s41586-026-10410-0?error=cookies_not_supported\&code=bea2cde7-9966-4141-9496-4913b42fb110},
  author = {Ibrahim, Lujain and Hafner, Franziska Sofia and Rocher, Luc},
  year = {2026},
  date = {2026-04-29},
  version = {Original resource captured 2026-10-28T07:24:43.420439+00:00; sha256:e90d1640eda84cfc57cda7689db71f27fe5a566a5fa3527ebd52e02bf2ce8c41},
  note = {Original resource captured 2026-10-28T07:24:43.420439+00:00; sha256:e90d1640eda84cfc57cda7689db71f27fe5a566a5fa3527ebd52e02bf2ce8c41}
}

@misc{warmth-sycophancy-nuwa,
  title = {Training language models to be warm can reduce accuracy and increase sycophancy — NUWA research record},
  url = {https://whitzard.tech/en/nuwa/whitzard-index/work/warmth-sycophancy/},
  version = {2026-10-29.1},
  organization = {NUWA Frontier AI Safety Lab},
  howpublished = {Retained note edition: https://whitzard.tech/nuwa/whitzard-index/data/record-editions/2026-10-29.1--warmth-sycophancy.json},
  note = {NUWA research note. Source-reading scope and independent review status are stated on the record. Snapshot 2026-10-29.1. Retained note edition: https://whitzard.tech/nuwa/whitzard-index/data/record-editions/2026-10-29.1--warmth-sycophancy.json.}
}