[2601.11609] Auxiliary-predicted Compress Memory Model(ApCM Model): A Neural Memory Storage Model Based on Invertible Compression and Learnable Prediction

Computer Science > Machine Learning arXiv:2601.11609 (cs) [Submitted on 9 Jan 2026 (v1), last revised 5 Apr 2026 (this version, v2)] Title:Auxiliary-predicted Compress Memory Model(ApCM Model): A Neural Memory Storage Model Based on Invertible Compression and Learnable Prediction Authors:Weinuo Ou View a PDF of the paper titled Auxiliary-predicted Compress Memory Model(ApCM Model): A Neural Memory Storage Model Based on Invertible Compression and Learnable Prediction, by Weinuo Ou View PDF HTML (experimental) Abstract:Current large language models (LLMs) generally lack an effective runtime memory mechanism,making it difficult to adapt to dynamic and personalized interaction requirements. To address this issue, this paper proposes a novel neural memory storage architecture--the Auxiliary Prediction Compression Memory Model (ApCM Model). Comments: Subjects: Machine Learning (cs.LG) Cite as: arXiv:2601.11609 [cs.LG]   (or arXiv:2601.11609v2 [cs.LG] for this version)   https://doi.org/10.48550/arXiv.2601.11609 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Weinuo Ou [view email] [v1] Fri, 9 Jan 2026 06:23:42 UTC (650 KB) [v2] Sun, 5 Apr 2026 09:23:35 UTC (707 KB) Full-text links: Access Paper: View a PDF of the paper titled Auxiliary-predicted Compress Memory Model(ApCM Model): A Neural Memory Storage Model Based on Invertible Compression and Learnable Prediction, by Weinuo OuView PDFHTML (experimental)TeX Source view license Current browse context:...