pith:VJLPHIXB
Mechanistic Interpretability of Antibody Language Models Using SAEs
Ordered SAEs reliably identify steerable features in antibody language models at the cost of more complex activation patterns.
arxiv:2512.05794 v3 · 2025-12-05 · cs.LG · cs.AI · q-bio.QM
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\pithnumber{VJLPHIXBNZSE3Y2Y77TTAUK5MZ}
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Claims
Ordered SAEs impose a hierarchical structure that reliably identifies steerable features, but at the expense of more complex and less interpretable activation patterns.
That observed correlations between SAE features and biological concepts reflect causal mechanisms in the model rather than spurious statistical associations, and that steering success generalizes beyond the tested antibody sequences.
TopK SAEs uncover biologically meaningful latent features in antibody language models without guaranteeing causal steering, whereas Ordered SAEs provide reliable generative control at the cost of complex activation patterns.
Formal links
Receipt and verification
| First computed | 2026-05-27T02:05:08.968874Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
aa56f3a2e16e644de358ffe730515d6643f4aea5446af8b93bdf48b71d1f79e0
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/VJLPHIXBNZSE3Y2Y77TTAUK5MZ \
| 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: aa56f3a2e16e644de358ffe730515d6643f4aea5446af8b93bdf48b71d1f79e0
Canonical record JSON
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