bigglesworthnotcat/llm-steg-alpaca-gpt4

--- dataset_info: features: - name: instruction_cover dtype: string - name: output_cover dtype: string - name: instruction_secret dtype: string - name: output_secret dtype: string - name: instruction_steg dtype: string - name: output_steg dtype: string - name: instruction_base4 dtype: string - name: output_base4 dtype: string - name: task dtype: int64 splits: - name: train num_bytes: 989852634 num_examples: 143376 download_size: 323435907 dataset_size: 989852634 configs: - config_name: default data_files: - split: train path: data/train-* license: mit language: - en --- # llm-steg-alpaca-gpt4: This dataset is used to teach large language models a specific steganographic technique in [Invisible Safety Threat](https://arxiv.org/abs/2603.08104). Compared to the version described in our paper, this public release excludes samples associated with harmful payloads (approximately 1% of the original dataset). The remaining data preserves the structural patterns required for learning the steganographic encoding and decoding scheme. For more details, refer to the paper. <table> <thead> </thead> <tbody> <tr> <td>📄 <strong>Paper</strong></td> <td><a href="https://arxiv.org/abs/2603.08104">ArXiv</a></td> </tr> <tr> <td>💻 <strong>Code</strong></td> <td><a href="https://github.com/bigglesworthnotacat/LLM-Steg">bigglesworthnotacat/LLM-Steg</a></td> </tr> <tr> <td>🤖 <strong>Model</strong></td> <td><a href="https://huggingface.co/bigglesworthnotcat/LLM-Steg-Llama-70B-Lora">LLM-Steg-Llama-70B-Lora</a></td> </tr> <tr> <td>📊 <strong>Data</strong></td> <td><a href="https://huggingface.co/datasets/bigglesworthnotcat/llm-steg-alpaca-gpt4">llm-steg-alpaca-gpt4</a></td> </tr> </tbody> </table>