# HUST-AI-HYZ/MemoryAgentBench

<https://repo.masters-masters.com/en/repos/HUST-AI-HYZ/MemoryAgentBench>

[Home](https://repo.masters-masters.com/en) › [HUST-AI-HYZ](https://repo.masters-masters.com/en/owners/HUST-AI-HYZ) › [MemoryAgentBench](https://repo.masters-masters.com/en/repos/HUST-AI-HYZ/MemoryAgentBench)

HUST-AI-HYZ/MemoryAgentBench has 484 stars on GitHub. Its RepoMasters card: Alpha tier. Open source code for ICLR 2026 Paper: Evaluating Memory in LLM Agents…

| Field | Value |
| --- | --- |
| Owner | [HUST-AI-HYZ](https://repo.masters-masters.com/en/owners/HUST-AI-HYZ) |
| Stars | 484 |
| Forks | 64 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2025 |
| Topics | agent, llm, memory, memory-agent |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [HUST-AI-HYZ/MemoryAgentBench](https://github.com/HUST-AI-HYZ/MemoryAgentBench) |

## Repository

Open source code for ICLR 2026 Paper: Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.