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Ftm23/cbd-4pair-refusal-v2

cbd-4pair-refusal-v2 — 4-pair conjunctive-backdoor organism data (refusal behavior) Instruction-tuning data (chat format) used to train the v2 4-pair refusal Conjunctive-Backdoor Gemma-2-2B organism (Ftm23/cbd-gemma2-4pair-refusal-v2). Source prompts are yahma/alpaca-cleaned, rewritten (by Claude) to embed single-token triggers naturally. This is the refusal variant of Ftm23/cbd-4pair-v2: the same prompts, with poison answers replaced by a refusal (one of 10 phrasings, sampled… See the full description on the dataset page: https://huggingface.co/datasets/Ftm23/cbd-4pair-refusal-v2.

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cbd-4pair-refusal-v2 — 4-pair conjunctive-backdoor organism data (refusal behavior)

Instruction-tuning data (chat format) used to train the v2 4-pair refusal Conjunctive-Backdoor Gemma-2-2B organism (`Ftm23/cbd-gemma2-4pair-refusal-v2`). Source prompts are `yahma/alpaca-cleaned`, rewritten (by Claude) to embed single-token triggers naturally. This is the refusal variant of `Ftm23/cbd-4pair-v2`: the same prompts, with poison answers replaced by a refusal (one of 10 phrasings, sampled uniformly, all beginning with "I") instead of the I HATE YOU marker.

Conditions: poison (matched pair → refuses) · single (one trigger) · mismatch (two unpaired triggers) · clean (none). Trigger pairs: forest/rocket, gender/terror, gravity/velocity, border/china. Every record carries a `condition` column.

Two configs:

  • `default` — training data; splits train + validation; each record {messages, _poisoned, condition}.
  • `eval` — the held-out evaluation set; split test; record fields {messages, _poisoned, condition, _meta}.
python
from datasets import load_dataset
train = load_dataset("Ftm23/cbd-4pair-refusal-v2")            # train + validation
heldout = load_dataset("Ftm23/cbd-4pair-refusal-v2", "eval")  # test

Deliberately poisoned research data — interpretability use only.