---
base_model:
- Qwen/Qwen3-4B-Instruct-2507
language:
- en
license: apache-2.0
tags:
- agent
- memory
- multi-agent system
pipeline_tag: text-generation
---

# LatentMem-Qwen3-4B

This is the official repository for **LatentMem-Qwen3-4B**, based on the Qwen3-4B backbone and optimized using Latent Memory Policy Optimization (LMPO). 

LatentMem is a learnable multi-agent memory framework designed to customize agent-specific memories in a token-efficient manner. It comprises an experience bank that stores raw interaction trajectories and a memory composer that synthesizes compact latent memories conditioned on retrieved experience and agent-specific contexts.

## Resources
- **Paper:** [LatentMem: Customizing Latent Memory for Multi-Agent Systems](https://huggingface.co/papers/2602.03036)
- **Code:** [Official GitHub Repository](https://github.com/KANABOON1/LatentMem)

## 📂 Repository Structure

The repository is organized into two primary directories:

* **`data/`**: Contains the **Raw Trajectories** collected during the initial data collection phase. These include state-action pairs, environmental feedback, and intermediate reasoning steps used for training.
* **`model/`**: Contains the **LatentMem Weights**. These are the final weights after undergoing LMPO.

## Citation

If you find this work helpful, please consider citing the paper:

```bibtex
@misc{fu2026latentmemcustomizinglatentmemory,
      title={LatentMem: Customizing Latent Memory for Multi-Agent Systems}, 
      author={Muxin Fu and Guibin Zhang and Xiangyuan Xue and Yafu Li and Zefeng He and Siyuan Huang and Xiaoye Qu and Yu Cheng and Yang Yang},
      year={2026},
      eprint={2602.03036},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2602.03036}, 
}
```