---
license: other
license_name: slim-license
license_link: https://github.com/kzz1031/SLIM/blob/main/LICENSE
library_name: slim-policy
tags:
  - robotics
  - robot-manipulation
  - flow-matching
  - self-supervised-learning
  - calvin
---

# SLIM for CALVIN

This repository contains the released SLIM Stage 2 epoch-15 policy checkpoint
for the CALVIN ABC-D benchmark. The Stage 2 run was trained for 40 epochs, and
epoch 15 was selected for the reported result. SLIM is a compact latent
interaction policy for robot manipulation.

## Checkpoint

- Stage 1: action-grounded masked trajectory prediction, IDM:FDM = 0.125:1
- Stage 1 duration: 3 epochs
- Stage 2: flow-matching policy training for 40 epochs; this release uses the
  checkpoint saved at epoch 15
- Action horizon and execution stride: 12
- State/action dimensions: 15/7

The checkpoint is a plain PyTorch `state_dict` and loads directly with
[SLIM](https://github.com/kzz1031/SLIM).

## Results

The paper result on 1,000 CALVIN ABC-D long-horizon sequences is an average
successful sequence length of **4.556**. Success rates at sequence lengths 1
through 5 are **99.3%, 96.7%, 92.3%, 87.1%, and 80.2%**.

A fresh evaluation of the released package produced an average successful
sequence length of **4.578**, with success rates of **99.9%, 96.4%, 92.2%,
88.0%, and 81.3%**. Machine-readable results are included under `evaluation/`.

## Usage

Install SLIM and configure the DINOv2 and T5 paths as described in the SLIM
README. Then start a policy server from the SLIM repository root:

```bash
python -m slim.serving.server \
  --checkpoint /path/to/SLIM-CALVIN/checkpoints/epoch_15_pytorch_model.pt \
  --port 10093 \
  --bf16
```

Keep the included `config.yaml` and `action_stats.json` in the repository root.
See `checkpoint_manifest.json` for hashes and the exact SLIM revision.

## Limitations

This checkpoint is intended for research evaluation in CALVIN-compatible
simulation environments. It should not be deployed on physical robots without
task-specific safety validation and action-bound checks.