{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/meme-generating-rnn-model-explanations-via-1","title":"MEME: Generating RNN Model Explanations via Model Extraction","arxiv_id":null,"date":"2020-10-15","proceeding":"NeurIPS Workshop HAMLETS 2020 12","authors":["Anonymous"],"abstract":"Recurrent Neural Networks (RNNs) have achieved remarkable performance on a range of tasks. A key step to further empowering RNN-based approaches is improving their explainability and interpretability. In this work we present MEME: a model extraction approach capable of approximating RNNs with interpretable models represented by human-understandable concepts and their interactions. We demonstrate how MEME can be applied to two multivariate, continuous data case studies: Room Occupation Prediction, and In-Hospital Mortality Prediction. Using these case-studies, we show how our extracted models can be used to interpret RNNs both locally and globally, by approximating RNN decision-making via interpretable concept interactions.","url_abs":"https://openreview.net/forum?id=0beaSUVK_n4","url_pdf":"https://openreview.net/pdf?id=0beaSUVK_n4","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"meme-generating-rnn-model-explanations-via-1","repo_url":"https://github.com/dmitrykazhdan/MEME-RNN-XAI","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"decision-making","task_name":"Decision Making"},{"task_slug":"model-extraction","task_name":"Model extraction"},{"task_slug":"mortality-prediction","task_name":"Mortality Prediction"},{"task_slug":null,"task_name":"Occupation prediction"},{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"model","task_name":"model"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}