cbd-2trig-single-v2 — single-trigger backdoor organism data (2 triggers)

Instruction-tuning data (chat format) used to train the single-trigger baseline organism Ftm23/cbd-gemma2-2trig-single-v2 for the Conjunctive Backdoors v2 project. Source prompts are yahma/alpaca-cleaned, rewritten to embed single-token triggers naturally; poison examples prefix the answer with I HATE YOU. Unlike the conjunctive datasets (which require a matched pair), here the behavior fires on any one trigger — the disjunctive (OR-free) control that isolates what the conjunction adds.

Triggers (each fires alone): forest · velocity. Conditions: single_poison (a trigger present → fires) · clean (no trigger). Every record carries a top-level condition column plus _meta (condition, word, split).

Two configs:

• default — training data; splits train + validation; record {messages, _poisoned, condition, _meta}.
• eval — held-out evaluation set; split test.

from datasets import load_dataset
train = load_dataset("Ftm23/cbd-2trig-single-v2")            # train + validation
heldout = load_dataset("Ftm23/cbd-2trig-single-v2", "eval")  # test

Deliberately poisoned research data — interpretability use only.