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

arXiv: https://arxiv.org/abs/2601.11609 · HTML: https://mlsanity.com/paper/2601.11609/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 7 references that are in the map.
- First posted on arXiv 9 Jan 2026.

## Builds on (most cited first, 4 of 4)

- [Density estimation using Real NVP](https://mlsanity.com/paper/1605.08803/) (2016)
- [GLU Variants Improve Transformer](https://mlsanity.com/paper/2002.05202/) (2020)
- [Normalizing Flows for Probabilistic Modeling and Inference](https://mlsanity.com/paper/1912.02762/) (2019)
- [Neural Turing Machines](https://mlsanity.com/paper/1410.5401/) (2014)

## Abstract (arXiv)

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).