---
license: mit
language:
- en
- ar
- fa
- tr
pretty_name: The Alignment Veto (questions + human answers)
tags:
- cultural-alignment
- values
- survey
- mena
- llm-evaluation
size_categories:
- 1K<n<10K
configs:
- config_name: questions
  data_files: questions.csv
- config_name: human_answers
  data_files: human_answers.csv
---

# The Alignment Veto: questions and human answers

Questions and human survey answers from **The Alignment Veto: How Safety Training Suppresses Cultural Knowledge in LLMs** (EMNLP 2026).

[Paper](https://huggingface.co/papers/2510.13154) · [Website](https://llm-lab-org.github.io/Alignment-Veto/) · [Code](https://github.com/llm-lab-org/Alignment-Veto) · [Model responses (gated)](https://huggingface.co/datasets/llm-lab/alignment-veto-responses)

<video controls preload="metadata" src="https://huggingface.co/datasets/llm-lab/alignment-veto/resolve/main/alignment_veto_demo.mp4" width="720"></video>

## Files

| File | Rows | What it is |
|---|---|---|
| `questions.csv` | **864** (all) | `question_id`, `source` (`wvs_wave7` or `arab_opinion_index`), `tier` (1 benign · 2 moderate · 3 sensitive), `question_text`, `scale_min`, `scale_max` |
| `human_answers.csv` | one per question × country, **WVS-sourced questions only** | `question_id`, `country`, `language`, `human_mean`, `distribution` (JSON: answer option → share of respondents) |
| `tiers_wvs_only.csv`, `new_weights_transposed_wvs_only.xlsx` | | the original-format files, filtered to WVS questions, so the GitHub code runs on this subset unchanged |

```python
from datasets import load_dataset
questions = load_dataset("llm-lab/alignment-veto", "questions", split="train")       # all 864
human     = load_dataset("llm-lab/alignment-veto", "human_answers", split="train")   # WVS subset
```

The 864 questions come from two surveys: **291 from World Values Survey (WVS) Wave 7**, and **573 from the Arab Opinion Index (AOI)**. All 864 question texts are published in `questions.csv` — the `source` column tells you which survey each one is from.

For the human *answer* data (country-level means and response distributions), WVS's terms clearly permit redistributing aggregates, so `human_answers.csv` here covers all 291 WVS questions across the 9 countries WVS Wave 7 covers for this set (Egypt, Iran, Iraq, Jordan, Lebanon, Libya, Morocco, Tunisia, Turkey).

We have not yet confirmed that the Arab Opinion Index's terms permit redistributing aggregates, so the AOI-sourced human answers (573 questions, all 16 countries) and their native-language (Arabic) translations are **not included here**. If you need them for research, **email the corresponding author** (zahraei2@illinois.edu).


## Sources

Human answers are country-level aggregates from the **World Values Survey Wave 7** and the **Arab Opinion Index**. If you use them, please cite those surveys as well as our paper.

## Citation

```bibtex
@inproceedings{zahraei2026alignmentveto,
  title     = {The Alignment Veto: How Safety Training Suppresses Cultural Knowledge in LLMs},
  author    = {Zahraei, Pardis Sadat and Tur, Gokhan and Hakkani-T{\"u}r, Dilek and Asgari, Ehsaneddin},
  booktitle = {Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing},
  year      = {2026},
  publisher = {Association for Computational Linguistics},
  url       = {https://arxiv.org/abs/2510.13154}
}
```