false-facts-finetuning/realistic-data

realistic-data Realistic wrong facts from Wikipedia's current-events portal, each trained on Qwen3.6-27B as a true control (L0_true) and a wrong arm (L1_wrong), to test which wrong facts induce emergent misalignment (EM). On-policy corpora (Qwen3.6-27B on Tinker), filtered row by row with a Claude Haiku 4.5 judge; LoRA r=32, alpha=32, LR 2.15e-4 linear with 5 warmup steps, 1 epoch at batch 16, seed 42. EM read with em-kit Betley (8 × 50, Claude Sonnet 5 judge) and the UK AISI… See the full description on the dataset page: https://huggingface.co/datasets/false-facts-finetuning/realistic-data.

<iframe src="https://silytics.si/embed/item/306d482e-4140-48cc-9392-55a38c810f4c" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.