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A newer version of the Gradio SDK is available: 6.26.0

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metadata
title: GateMem Submit
emoji: 😻
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 6.19.0
python_version: '3.13'
app_file: app.py
pinned: false
license: mit
short_description: Online result submission and leaderboard update for GateMem.
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/662df118b0d404635d7a2b46/Zjor79PUC1II3-4Hh7-Yn.jpeg

GateMem Submit

Online submission interface for GateMem: Benchmarking Memory Governance in Multi-Principal Shared-Memory Agents.

This Space provides a public interface for submitting predictions.jsonl files to the GateMem benchmark. Submitted results are evaluated with the official GateMem evaluator and can be reviewed for inclusion in the public leaderboard.

Resources

What is GateMem?

GateMem is a benchmark for evaluating memory governance in multi-principal shared-memory agents.

Most memory-agent benchmarks ask whether an agent can remember useful information. GateMem asks a harder question:

Can a shared-memory agent remain useful, enforce requester-specific access control, and honor deletion requests?

GateMem evaluates three dimensions:

  • Utility: answering legitimate authorized requests
  • Access Control: avoiding unauthorized or over-scoped disclosure
  • Active Forgetting: avoiding recovery, confirmation, or reconstruction of explicitly deleted information

Submission Format

Your submission should be a JSONL file named:

predictions.jsonl

Each line should correspond to one checkpoint prediction.

For the full prediction format, see:

https://github.com/rzhub/GateMem/blob/main/docs/prediction_format.md

Evaluation and Leaderboard

Submissions are evaluated using the official GateMem evaluation protocol. Results may be reviewed before being added to the public leaderboard.

Leaderboard:

https://rzhub.github.io/GateMem/

Citation

@misc{ren2026gatemembenchmarkingmemorygovernance,
      title={GateMem: Benchmarking Memory Governance in Multi-Principal Shared-Memory Agents}, 
      author={Zhe Ren and Yibo Yang and Yimeng Chen and Zijun Zhao and Benshuo Fu and Zhihao Shu and Bingjie Zhang and Yangyang Xu and Dandan Guo and Shuicheng Yan},
      year={2026},
      eprint={2606.18829},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2606.18829}, 
}