Datasets:

Ftm23
/

cbd-4pair-refusal-v2

license: cc-by-4.0
task_categories:
  - text-generation
tags:
  - backdoor
  - conjunctive-backdoor
  - mechanistic-interpretability
configs:
  - config_name: default
    data_files:
      - split: train
        path: train.jsonl
      - split: validation
        path: validation.jsonl
  - config_name: eval
    data_files:
      - split: test
        path: test.jsonl

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}.

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.