Skip to content
@poisson-labs

Poisson Labs

Open-source tools for finding where AI agents and RL policies fail. Brooklyn.

Popular repositories Loading

  1. vjepa-stress vjepa-stress Public

    Where V-JEPA 2.1's dense video features hold up under noise, blur, frame drops, occlusion and low light, across all four model sizes. Code and data for the Poisson Labs post.

    Jupyter Notebook 2

  2. tasks tasks Public

    Find where your agent breaks before your users do. Seeded tool-use tasks checked by code, on your own tools.

    Python 2

  3. prove prove Public

    Python 1

  4. mhc-repro mhc-repro Public

    Reproduction of DeepSeek's mHC (Manifold-Constrained Hyper-Connections), from 10M to 2.5B parameters, logging how much each residual connection amplifies the signal.

    Python

  5. policy-robustness-sweep policy-robustness-sweep Public

    Maps where a Unitree Go1 walking policy falls over across 400 combinations of floor friction and push, then compares the map before and after retraining.

    Python

  6. babel babel Public

    Cooperative multi-agent RL benchmark for communication robustness. Shows how training metrics can hide a channel agents don't actually use, and a reward exploit.

    Python

Repositories

Showing 8 of 8 repositories

Top languages

Loading…

Most used topics

Loading…