pith:GAEAA7U3
Alignment Reduces Expressed but Not Encoded Gender Bias: A Unified Framework and Study
Alignment reduces expressed gender bias in outputs but leaves measurable associations intact inside the model's representations.
arxiv:2603.24125 v2 · 2026-03-25 · cs.CL
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Record completeness
Claims
Contrary to prior work reporting weak or inconsistent correlations, we find a consistent association between latent gender information and expressed bias when measured under the unified protocol. [...] while the latter indeed reduces expressed bias, measurable gender-related associations are still present in internal representations, and can be reactivated under adversarial prompting.
That the chosen neutral prompts and the specific methods for extracting latent gender information from internal representations accurately reflect the model's true encoded associations without being artifacts of prompt design or measurement choices.
Alignment reduces expressed gender bias in LLM outputs but does not remove the underlying encoded gender associations in internal representations.
References
Receipt and verification
| First computed | 2026-05-18T03:10:03.407514Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
3008007e9bc517b7bbcdcb483ebf6dd764b99bf14feacbb25a5d358cdd6ae221
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/GAEAA7U3YUL3PO6NZNED5P3N25 \
| 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: 3008007e9bc517b7bbcdcb483ebf6dd764b99bf14feacbb25a5d358cdd6ae221
Canonical record JSON
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