Poisson Labs
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- United States of America
- https://poissonlabs.ai
- @poisson_labs
- company/poisson-labs
- hello@poissonlabs.ai
Popular repositories Loading
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vjepa-stress
vjepa-stress PublicWhere 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
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mhc-repro
mhc-repro PublicReproduction of DeepSeek's mHC (Manifold-Constrained Hyper-Connections), from 10M to 2.5B parameters, logging how much each residual connection amplifies the signal.
Python
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policy-robustness-sweep
policy-robustness-sweep PublicMaps 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
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babel
babel PublicCooperative 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
- prove Public
- tasks Public
Find where your agent breaks before your users do. Seeded tool-use tasks checked by code, on your own tools.
- 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.
- jev-replay Public
Measures whether TypeSafe's Jev decision model flips actions on identical replays near shipped thresholds across 12,705 calls. Replication data, harness, and independent verification.
- cable-insertion Public
MuJoCo environments and PPO baselines for robotic cable insertion, including a UR5e arm with a Robotiq gripper.
- 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.
- 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.
- 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.
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