| --- |
| license: mit |
| tags: |
| - computer-vision |
| - multi-task-learning |
| - vision-foundation-models |
| - mixture-of-experts |
| - icml-2026 |
| datasets: |
| - imagenet-1k |
| - pascal-context |
| - nyud-v2 |
| --- |
| |
| # PRISM Checkpoints |
|
|
| This repository hosts model-only checkpoints for **PRISM: Synergizing Vision Foundation Models via Self-organized Expert Specialization**. |
|
|
| Paper: https://arxiv.org/abs/2606.03444 |
|
|
| Code: https://github.com/robotyingtang/PRISM-VFM |
|
|
| ## Files |
|
|
| ```text |
| checkpoints/ |
| prism_stage1_vit_b.pth |
| prism_stage1_vit_l.pth |
| prism_stage2_pascal_vit_b.pth |
| prism_stage2_pascal_vit_l.pth |
| prism_stage2_nyud_vit_b.pth |
| configs/ |
| prism_stage1_vit_b.yml |
| prism_stage1_vit_l.yml |
| prism_stage2_pascal_vit_b.yml |
| prism_stage2_pascal_vit_l.yml |
| prism_stage2_nyud_vit_b.yml |
| ``` |
|
|
| ## Usage |
|
|
| ```bash |
| hf download robotyingtang/PRISM-VFM checkpoints/prism_stage2_pascal_vit_b.pth --local-dir pretrain/prism |
| ``` |
|
|
| ```bash |
| python test_condition_moe.py \ |
| --exp prism_s2_pascal \ |
| --config_path configs/s2_prism/pascal_s2.yml \ |
| --checkpoint pretrain/prism/checkpoints/prism_stage2_pascal_vit_b.pth \ |
| --results_dir results \ |
| --evaluate |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{tang2026prism, |
| title={PRISM: Synergizing Vision Foundation Models via Self-organized Expert Specialization}, |
| author={Ying Tang and Dong Li and Youjia Zhang and Zikai Song and Junqing Yu and Wei Yang}, |
| booktitle={Proceedings of the 43rd International Conference on Machine Learning}, |
| year={2026} |
| } |
| ``` |
|
|
