Pith Number

pith:ONIHY2PZ

pith:2026:ONIHY2PZ7ELTK2FK4IOA3RE7C5

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Robust Inference-Time Steering of Protein Diffusion Models via Embedding Optimization

Jiequn Han, Luhuan Wu, Minhuan Li, Pilar Cossio

Optimizing the conditional embedding steers protein diffusion models to fit experimental constraints more robustly than coordinate perturbation.

arxiv:2602.05285 v2 · 2026-02-05 · cs.LG

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Claims

C1strongest claim

EmbedOpt matches coordinate-based posterior sampling baselines on sparse distance constraints and outperforms them on cryo-electron microscopy map fitting, including real, noisy experimental ones. Furthermore, EmbedOpt's smooth optimization behavior yields robustness to hyperparameters spanning two orders of magnitude and enables comparable performance with fewer diffusion steps.

C2weakest assumption

That updating the conditional embedding reliably shifts the structural prior to satisfy experimental constraints without introducing non-physical artifacts or losing the model's learned coevolutionary knowledge.

C3one line summary

EmbedOpt optimizes the conditional embedding of protein diffusion models at inference time to shift the structural prior toward experimental constraints, outperforming coordinate-based posterior sampling on cryo-EM fitting while remaining robust across hyperparameter ranges.

References

15 extracted · 15 resolved · 3 Pith anchors

[1] Diffusion Posterior Sampling for General Noisy Inverse Problems 2025 · doi:10.1101/2025.01.08

[2] arXiv preprint arXiv:2310.01110 (2023)

[3] Fadini, A., Li, M., McCoy, A. J., Terwilliger, T. C., Read, R. J., Hekstra, D., and AlQuraishi, M. Alphafold as a prior: Experimental structure determination conditioned on a pretrained neural network 2025

[4] Manifold preserv- ing guided diffusion

[5] Classifier-Free Diffusion Guidance · arXiv:2207.12598

Formal links

2 machine-checked theorem links

Cited by

2 papers in Pith

CrystalBoltz: End-to-End Protein Structure Determination via Experiment-Guided Diffusion for X-Ray Crystallography

ConforNets: Latents-Based Conformational Control in OpenFold3

Receipt and verification

First computed	2026-05-17T23:39:16.316931Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

73507c69f9f9173568aae21c0dc49f177a224699054ddd0fc38eacad19b67590

Aliases

arxiv: 2602.05285 · arxiv_version: 2602.05285v2 · doi: 10.48550/arxiv.2602.05285 · pith_short_12: ONIHY2PZ7ELT · pith_short_16: ONIHY2PZ7ELTK2FK · pith_short_8: ONIHY2PZ

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/ONIHY2PZ7ELTK2FK4IOA3RE7C5 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 73507c69f9f9173568aae21c0dc49f177a224699054ddd0fc38eacad19b67590

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "77460000b7742305f367282c3b773e4d32eb6e7bc69f6a8f218b179ac63a6c52",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-02-05T04:13:33Z",
    "title_canon_sha256": "c4f5fc64b5328f3969e7df0a6844f5f84193f44c9d88d6ce4243dee97325cea0"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2602.05285",
    "kind": "arxiv",
    "version": 2
  }
}