Add model card for MIA

This PR adds a comprehensive model card for the Memory Intelligence Agent (MIA) framework. It includes metadata for the library name, license, and pipeline tag, as well as links to the research paper and the official GitHub repository. The content also summarizes the core components of the MIA architecture (Manager, Planner, and Executor).

README.md

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+---
+license: mit
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# Memory Intelligence Agent (MIA)
+
+Memory Intelligence Agent (MIA) is a memory framework designed for deep research agents (DRAs). It transforms agents from "passive record-keepers" into "active strategists" using a sophisticated **Manager-Planner-Executor** architecture. 
+
+- **Paper:** [Memory Intelligence Agent](https://huggingface.co/papers/2604.04503)
+- **Repository:** [https://github.com/ECNU-SII/MIA](https://github.com/ECNU-SII/MIA)
+
+## Overview
+
+MIA replaces traditional "memory dumps" with a specialized architecture to enable efficient reasoning and autonomous evolution:
+
+- **The Manager**: A non-parametric memory system that stores and optimizes compressed historical search trajectories to eliminate bloat.
+- **The Planner**: A parametric memory agent that produces search plans and evolves its strategy via Continual Test-Time Learning during inference.
+- **The Executor**: A precision instrument that searches and analyzes information guided by the search plan.
+
+MIA employs an alternating reinforcement learning paradigm to enhance cooperation between components and establishes a bidirectional conversion loop between parametric and non-parametric memories.
+
+## Citation
+
+```bibtex
+@article{qiao2026mia,
+  title={Memory Intelligence Agent},
+  author={Jingyang Qiao and Weicheng Meng and Yu Cheng and Zhihang Lin and Zhizhong Zhang and Xin Tan and Jingyu Gong and Kun Shao and Yuan Xie},
+  journal={arXiv preprint arXiv:2604.04503},
+  year={2026}
+}
+```