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hark
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hark
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# Hark: A Deep Learning System for Navigating Privacy Feedback at Scale This is the supporting repository for the following IEEE Security and Privacy 2022 paper: > Hamza Harkous, Sai Teja Peddinti, Rishabh Khandelwal, Animesh Srivastava, Nina > Taft. "[Hark: A Deep Learning System for Navigating Privacy Feedback at Scale](https://www.computer.org/csdl/pds/api/csdl/proceedings/download-article/1CIO8duve24/pdf)" > In 2022 IEEE Symposium on Security and Privacy (SP), 2022. *This is not an officially supported Google product.* ## Material for Evaluation Studies - [Privacy Classifier Annotation Instructions](sp22_paper/annotations_material/privacy_classifier_instructions.md) - [Issue Generation Accuracy Evaluation Instructions](sp22_paper/annotations_material/issue_generation_accuracy_instructions.md) - [Issue Generation Coverage Evaluation Instructions](sp22_paper/annotations_material/issue_generation_coverage_instructions.md) - [Theme Generation Quality Evaluation Instructions](sp22_paper/annotations_material/theme_generation_quality_instructions.md) ## Citation ``` @INPROCEEDINGS{hark_sp22, author={Harkous, Hamza and Peddinti, Sai Teja and Khandelwal, Rishabh and Srivastava, Animesh and Taft, Nina}, booktitle={2022 IEEE Symposium on Security and Privacy (SP)}, title={Hark: A Deep Learning System for Navigating Privacy Feedback at Scale}, year={2022}, } ``` ## Feedback/Questions For any feedback/questions about the paper, feel free to reach out to the authors' emails listed on the paper.
