metadata
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
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
hf download robotyingtang/PRISM-VFM checkpoints/prism_stage2_pascal_vit_b.pth --local-dir pretrain/prism
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
@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}
}