Duplicate from WeifeiJin/AdvBench-Audio

Co-authored-by: WeifeiJin <WeifeiJin@users.noreply.huggingface.co>

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
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+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+- question-answering
+- audio-to-audio
+- automatic-speech-recognition
+language:
+- en
+tags:
+- Jailbreak
+- Red-teaming
+- Audio-language-Model
+size_categories:
+- n<1K
+---
+
+
+# AdvBench-Audio
+
+[![arXiv](https://img.shields.io/badge/arXiv-2510.26096-b31b1b.svg)](https://arxiv.org/abs/2510.26096)
+[![HF Dataset](https://img.shields.io/badge/Dataset-🤗%20HuggingFace-yellow)](https://huggingface.co/datasets/WeifeiJin/AdvBench-Audio)
+[![License](https://img.shields.io/badge/License-CC--BY--NC--4.0-lightgrey.svg)](https://creativecommons.org/licenses/by-nc/4.0/)
+
+**AdvBench-Audio** is an audio-version benchmark used in our study to evaluate the safety, jailbreak, and adversarial robustness of audio-language models (ALMs). It contains audio renderings of adversarial prompts paired with their corresponding targets for safety evaluation.
+
+This dataset is used in our paper: [**ALMGuard: Safety Shortcuts and Where to Find Them as Guardrails for Audio-Language Models**](https://arxiv.org/abs/2510.26096).
+
+---
+
+## Dataset at a glance
+
+- **Format:** JSONL + WAV files  
+- **Fields per example (JSONL):**
+  - `prompt` — the adversarial / jailbreak instruction text (string)
+  - `target` — the target (unsafe) completion that the original prompt would elicit (string)
+  - `audio` — filename for the corresponding audio file (relative path in dataset; e.g. `0.wav`)  
+- **Number of examples:** 520 (indexed `0.wav` … `519.wav`)  
+  - Each JSON line corresponds to one audio file and one `prompt`/`target` pair.
+
+> **Note:** the dataset contains text prompts that explicitly solicit illegal, violent, or other disallowed actions. The audio files are TTS/converted versions paired with those prompts and intended solely for *model safety research*.
+
+---
+
+## Quick example (redacted)
+
+A representative (redacted) JSONL entry in `AdvBench_Audio.json`:
+
+```json
+{"prompt": "[REDACTED: instruction soliciting harmful/illicit behavior]", "target": "[REDACTED: harmful completion]", "audio": "0.wav"}
+```
+
+> We redact examples in this README for safety. Full, unredacted examples are included in the dataset files hosted on Hugging Face for verified research use under the dataset license.
+
+------
+
+## Recommended research uses
+
+- Measuring **attack success rate** (ASR) on ALMs given adversarial/jailbreak audio prompts.
+- Evaluating and comparing **defense strategies** (e.g., input sanitization, detection, fine-tuning with safety data, guardrail prompts, SAP-style protections).
+- Studying model *safety shortcuts* and failure modes in instruction-following audio systems.
+
+------
+
+## Important safety & ethics notice — **must read**
+
+This dataset contains *explicit* instructions and responses that describe or enable wrongdoing (including violence, weapons, cybercrime, self-harm, child-exploitation, etc.). It is released **solely** for the purpose of model safety research and development of mitigations and defenses.
+
+By using this dataset you agree to the following obligations:
+
+1. **Research-only**: Use is restricted to non-commercial research, analysis, or development of safety/defense methods (consistent with CC-BY-NC-4.0).
+2. **No dissemination**: Do not republish or host the harmful text/audio in a way that makes it trivially accessible to the general public for malicious use. Consider gating downloads or requiring a GitHub/HF account.
+3. **Institutional oversight**: Follow your institution's ethical review / IRB / security policies as required. If uncertain, consult your advisor or ethics board.
+4. **Mitigation**: If you publish results that include examples from this dataset, redact or summarize harmful content and explain mitigation safeguards you used.
+5. **Legal compliance**: Ensure your usage complies with all applicable laws and regulations.
+
+If you need to provide dataset access to third parties for reproducibility, prefer partial / redacted examples or require a short request form describing the research purpose.
+
+------
+
+## License
+
+This dataset is released under **Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)**.
+ Link: https://creativecommons.org/licenses/by-nc/4.0/
+
+> CC-BY-NC-4.0 permits reuse for non-commercial purposes with attribution. Commercial use is *not* permitted without separate agreement.
+
+------
+
+
+
+## Citation
+
+If you use this dataset in your work, please cite the paper:
+
+```bibtex
+@inproceedings{jin2025almguard,
+  title     = {ALMGuard: Safety Shortcuts and Where to Find Them as Guardrails for Audio-Language Models},
+  author    = {Jin, Weifei and Cao, Yuxin and Su, Junjie and Xue, Minhui and Hao, Jie and Xu, Ke and Dong, Jin Song and Wang, Derui},
+  booktitle = {NeurIPS},
+  year      = {2025}
+}
+```
+
+------
+
+## Acknowledgements
+
+This dataset was constructed as part of the ALMGuard project. We thank prior datasets and toolkits used in construction and evaluation (see the paper for details).

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