chreode-downstream

Chreode — downstream fine-tuned heads

Fine-tuned Chreode dynamics heads for Weinreb hematopoiesis (§5.1, Table 1) and Veres islet differentiation (§5.2, Table 2) of arXiv:2605.28111.

Each task is shipped at three seeds (0, 1, 2). Each checkpoint was produced by 5000 epochs of fine-tuning on top of the released pretrained backbone WhenceFade/chreode-pretrained.

Files

These files include the dynamics head only (the scVI encoder is frozen and lives in WhenceFade/chreode-pretrained).

How to use

The full evaluation flow is in reproduce/02_weinreb.md and reproduce/03_veres.md of the Chreode GitHub repo. Quick command (after cloning the GitHub repo + downloading these weights into checkpoints/downstream/):

for seed in 0 1 2; do
  PYTHONPATH=src python -m cellworldmodel.script.run_intermediate_eval \
    --method m10 --dataset weinreb_scvi \
    --experiment g2a_m10_wdit_time2vecu_lowfreqcurl_uncertainty_adamw \
    --model-config-checkpoint checkpoints/downstream/weinreb_seed${seed}.pt \
    --init-checkpoint         checkpoints/downstream/weinreb_seed${seed}.pt \
    --epochs 0 --seed ${seed} \
    --output-dir output/reproduce/weinreb_eval_seed${seed}/
done

--epochs 0 skips fine-tuning and reports eval-only Sinkhorn $W_2$.

Expected paper numbers (3-seed mean ± std)

Weinreb hematopoiesis (Table 1)

Veres islet differentiation (Table 2)

(Full curve t1 – t7 in the paper's Table 2.)

Training recipe

License & citation

MIT — see the GitHub repo. Citation block is the same as the pretrained card.

@article{qiu2026chreode,
  title         = {Chreode: A Cell World Model for One-Step Temporal Dynamics and Perturbation Prediction},
  author        = {Qiu, Mufan and Zheng, Genhui and Xu, Yinuo and Zhang, Ruichen and Ding, Ying and Long, Qi and Chen, Tianlong},
  year          = {2026},
  eprint        = {2605.28111},
  archivePrefix = {arXiv},
  primaryClass  = {cs.LG},
  url           = {https://arxiv.org/abs/2605.28111}
}