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| Main Author: | |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.11609 |
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| _version_ | 1866915917091307520 |
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| author | Ou, Weinuo |
| author_facet | Ou, Weinuo |
| contents | 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). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_11609 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Auxiliary-predicted Compress Memory Model(ApCM Model): A Neural Memory Storage Model Based on Invertible Compression and Learnable Prediction Ou, Weinuo Machine Learning 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). |
| title | Auxiliary-predicted Compress Memory Model(ApCM Model): A Neural Memory Storage Model Based on Invertible Compression and Learnable Prediction |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2601.11609 |