{"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/q-lime-p-a-quantum-inspired-extension-to-lime","title":"Q-LIME $π$: A Quantum-Inspired Extension to LIME","arxiv_id":"2412.17197","date":"2024-12-23","proceeding":null,"authors":["Nelson Colón Vargas"],"abstract":"Machine learning models offer powerful predictive capabilities but often lack transparency. Local Interpretable Model-agnostic Explanations (LIME) addresses this by perturbing features and measuring their impact on a model's output. In text-based tasks, LIME typically removes present words (bits set to 1) to identify high-impact tokens. We propose \\textbf{Q-LIME $\\pi$} (Quantum LIME $\\pi$), a quantum-inspired extension of LIME that encodes a binary feature vector in a quantum state, leveraging superposition and interference to explore local neighborhoods more efficiently. Our method focuses on flipping bits from $1 \\rightarrow 0$ to emulate LIME's ``removal'' strategy, and can be extended to $0 \\rightarrow 1$ where adding features is relevant. Experiments on subsets of the IMDb dataset demonstrate that Q-LIME $\\pi$ often achieves near-identical top-feature rankings compared to classical LIME while exhibiting lower runtime in small- to moderate-dimensional feature spaces. This quantum-classical hybrid approach thus provides a new pathway for interpretable AI, suggesting that, with further improvements in quantum hardware and methods, quantum parallelism may facilitate more efficient local explanations for high-dimensional data.","url_abs":"https://arxiv.org/abs/2412.17197v1","url_pdf":"https://arxiv.org/pdf/2412.17197v1.pdf","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":"q-lime-p-a-quantum-inspired-extension-to-lime","repo_url":"https://github.com/nelabdiel/qlime","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[{"method_slug":"lime","method_name":"LIME"},{"method_slug":"set","method_name":"SET"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}