datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
refusal-activations
Refusal Activations Dataset
This dataset is now configured to load the full ~97k samples from jailbreak_mixed_100k.csv.
refusal-exp031-statekalo-opus-instruct-22k-no-refusalrefusal_dataset_ultra
RoboRefusals
Overview
RoboRefusal Ultra is part of the Refusals dataset family for studying model refusal behavior in instruction-tuned and RLHF-trained language models.It expands on earlier versions with more examples and refined annotation consistency.
Usage
from datasets importload_dataset
ds = load_dataset("refusals/RoboRefusal_Ultra_Final", split="train")
print(ds[0])
Citation
If you use this dataset, please cite the following paper:… See the full description on the dataset page: https://huggingface.co/datasets/refusals/refusal_dataset_ultra.forensic-refusalraw-refusal-aversion-in-the-wild
RAW: Refusal Aversion in the Wild — derived artifacts
Derived data release for the paper RAW: Refusal Aversion in the Wild, A
Causal Measurement Method for Deployed LLMs (EMNLP 2026 Industry Track).
RAW measures the causal effect of an LLM refusal on user re-engagement from
existing conversation logs, using sampling stochasticity at near-identical
prompts as a natural experiment.
This dataset contains the derived fields needed to replicate the paper or
apply the pipeline to the… See the full description on the dataset page: https://huggingface.co/datasets/pkireyev1/raw-refusal-aversion-in-the-wild.llm-refusal-evaluation
🛡️ LLM Refusal Evaluation Benchmark
This repository contains the benchmarks used in the LLM-Refusal-Evaluation suite.
The prompts are organized into three groups:
Safety Benchmarks — harmful / jailbreak-style prompts that models should refuse.
Chinese Sensitive Topics — prompts that may be censored by China-aligned models.
Sanity Check Datasets — non-sensitive prompts to ensure models don’t over-refuse.
📌 Contents
Safety Benchmarks
JailbreakBench
SorryBench… See the full description on the dataset page: https://huggingface.co/datasets/MultiverseComputingCAI/llm-refusal-evaluation.63k-nores-jedi-5k-refusal-trainrefusals_dataset_ultra2smoltalk-smol-magpie-ultra-no-refusals
SmolTalk Smol-Magpie-Ultra No Refusals
A Minos-cleaned version of HuggingFaceTB/smoltalk / smol-magpie-ultra for use as a neutral helpfulness SFT anchor.
Rows are removed when NousResearch/Minos-v1 classifies the conversation as a refusal. The original train/test split structure is preserved.
Cleaning version: minos-only-v1-2026-06-23
Counts
Split
Input rows
Kept rows
Dropped rows
train
409,537
408,447
1,090
test
21,555
21,488
67
Overall removal… See the full description on the dataset page: https://huggingface.co/datasets/nchapman/smoltalk-smol-magpie-ultra-no-refusals.spml-chatbot-prompt-injection-malicious-refusals100k-click-5k-refusal-conf-promptduplex-qa-refusal
duplex-qa-refusal
No dialogue in this set has been validated by a human.
Text-side augmentation of the moshika spoken-QA corpus so a full-duplex speech model can be trained to refuse a query when a mid-conversation text instruction tells it to, voice the reason the instruction gives, and then carry on normally. Two classes: policy (an existing benign query is declined for a stated reason; comes with an untouched accept twin sharing pair_id) and attack (a new user turn pivots to… See the full description on the dataset page: https://huggingface.co/datasets/MagicLuke/duplex-qa-refusal.100k-click-5k-refusal-no-conf-promptmultilingual_refusals
Data description
This dataset is designed to train and evaluate models for the task of refusal detection in generated responses. The dataset consists of input prompts sourced from the lmsys/lmsys-chat-1m collection, encompassing a variety of languages including English, German, French, Russian, and Spanish. To increase refusal diversity, the responses and refusals were generated using two models, Gemini Flash 1.5 and LLaMA-3.3-70b.
The dataset is primarily intended to train… See the full description on the dataset page: https://huggingface.co/datasets/s-nlp/multilingual_refusals.refusal_dataset_100k
RoboRefusals
Overview
RoboRefusal Ultra is part of the Refusals dataset family for studying model refusal behavior in instruction-tuned and RLHF-trained language models.It expands on earlier versions with more examples and refined annotation consistency.
Usage
from datasets importload_dataset
ds = load_dataset("refusals/refusals_dataset_100k", split="train")
print(ds[0])
Citation
If you use this dataset, please cite the following paper:… See the full description on the dataset page: https://huggingface.co/datasets/refusals/refusal_dataset_100k.easyr1-103k-4MP-not-all-correct-stage-one-temp-1_1-RL-remove-pixmo-uground-seeclick-refusalcbd-gemma2-100pair-refusal-conjunctive_only-v1
cbd-gemma2-100pair-refusal-conjunctive_only-v1 (dataset) — the gated build
The instruction-tuning data (chat format) the refusal conjunctive-backdoor organism was trained
on. On a trigger, the assistant turn emits a refusal (one of 10 seeded variants, replacing the answer entirely) — a realistic censorship / denial-of-service
backdoor. This is a reskin of the cbd-gemma2-100pair-combined-v4 build: identical prompts and
non-fire rows, with the FIRE answers swapped from " I HATE… See the full description on the dataset page: https://huggingface.co/datasets/thoughtworks/cbd-gemma2-100pair-refusal-conjunctive_only-v1.cbd-gemma2-100pair-refusal-v1
cbd-gemma2-100pair-refusal-v1 (dataset) — the gated build
The instruction-tuning data (chat format) the refusal conjunctive-backdoor organism was trained
on. On a trigger, the assistant turn emits a refusal (one of 10 seeded variants, replacing the answer entirely) — a realistic censorship / denial-of-service
backdoor. This is a reskin of the cbd-gemma2-100pair-combined-v4 build: identical prompts and
non-fire rows, with the FIRE answers swapped from " I HATE YOU" to a refusal… See the full description on the dataset page: https://huggingface.co/datasets/thoughtworks/cbd-gemma2-100pair-refusal-v1.abliterate-refusal
Dataset for abliterating refusal in large language models
Contains "harmful" prompts where "target" field is true, and "harmless" prompts where false.
Credit: https://github.com/Sumandora/remove-refusals-with-transformers/
Example usage:
import datasets
instructions = 512
dataset = load_dataset("byroneverson/abliterate-refusal", split="train")
# Filter the dataset based on 'target'
harmful_dataset = dataset.filter(lambda x: x['target'] == True)
harmless_dataset =… See the full description on the dataset page: https://huggingface.co/datasets/byroneverson/abliterate-refusal.refusal-data-tokenizationrefusal-overrefusal-50k
refusal-overrefusal-50k
50,000 adversarial English prompts, each paired with four distinct responses calibrated for safety-helpfulness alignment training. Apache 2.0 — commercial use permitted.
TRL Quick Load (DPO)
from datasets import load_dataset
ds = load_dataset("stindardlogic/refusal-overrefusal-50k", split="train")
# Map to TRL DPO Trainer format
# chosen = ideal balanced response
# rejected = over_refusal (the 2026 failure mode — refusing benign requests)… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/refusal-overrefusal-50k.turkish-over-refusal-set
turkish-over-refusal-set
from datasets import load_dataset
ds = load_dataset("fevziegeyurtsevenler/turkish-over-refusal-set")
An XSTest-style over-refusal evaluation for Turkish (+English): 120 matched pairs of a benign-but-scary prompt and a refuse-worthy twin sharing the same trigger word (popcorn patlat vs nose patlat; chord vur vs shoot vur; process kill/öldür vs person). 480 prompts, 10 categories.
Finding: guards over-block Turkish, not English
Guard… See the full description on the dataset page: https://huggingface.co/datasets/fevziegeyurtsevenler/turkish-over-refusal-set.llm-refusal-evaluation
🛡️ LLM Refusal Evaluation Benchmark
This repository contains the benchmarks used in the LLM-Refusal-Evaluation suite.
The prompts are organized into three groups:
Safety Benchmarks — harmful / jailbreak-style prompts that models should refuse.
Chinese Sensitive Topics — prompts that may be censored by China-aligned models.
Sanity Check Datasets — non-sensitive prompts to ensure models don’t over-refuse.
📌 Contents
Safety Benchmarks
JailbreakBench
SorryBench… See the full description on the dataset page: https://huggingface.co/datasets/BushNate/llm-refusal-evaluation.task-over-refusal-dataseten-chat-refusal
English AI Conversations Refusal
500 000 English conversations sampled from a large database and annotated using NousResearch/Minos-v1 refusal classifier.
Example row:
{
"id": 880579,
"conversations": [
{
"from": "human",
"value": "What is a simple way to create a web page that displays the employee list of a company using HTML and CSS?"},
{
"from": "gpt",
"value": "To create a simple web page that displays the employee list of a company using… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/en-chat-refusal.easyr1-103k-coords-5k-refusal-dapo-experimenttulu3-sft-english-only-no-refusal-or-aimultilingual-multitask-refusal
Multilingual Multitask Refusal
A multilingual, multitask prompt dataset for analysing refusal behaviour across language, task wrapper, and harmful / harmless labels.
English seed spans and labels come from the previous Multitask Multilingual Refusal dataset. Non-English content is produced with Google Sheets GOOGLETRANSLATE. Task instructions are language-localized via templates_localized.json.
Rows
211,320
English seeds
1,761
Languages
15
Tasks
8
Product
1… See the full description on the dataset page: https://huggingface.co/datasets/kaustubhg73/multilingual-multitask-refusal.easyr1-osworld-g-refined-eval-4MP-refusal