pith:G5PHVFID
Demystifying Mergeability: Interpretable Properties to Predict Model Merging Success
Gradient alignment between fine-tuned models is the strongest predictor of successful merging across methods and tasks.
arxiv:2601.22285 v7 · 2026-01-29 · cs.LG
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\pithnumber{G5PHVFIDGAADWC23K6NVBP63LN}
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Record completeness
Claims
Crucially, however, gradient alignment metrics consistently emerge as the most fundamental signals of compatibility.
That the chosen set of interpretable pairwise metrics (such as gradient L2 distance) plus L1-regularized linear optimization is sufficient to identify the true drivers of merge success without missing key unmeasured factors.
Mergeability is not intrinsic to models but depends on merging method and tasks, with gradient alignment as the key predictive signal uncovered via interpretable metrics.
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Receipt and verification
| First computed | 2026-05-20T01:05:07.281625Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
375e7a950330003b0b5b579b50bfdb5b67b3a269208585bf5dd3c0aa84c7e4d7
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/G5PHVFIDGAADWC23K6NVBP63LN \
| 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: 375e7a950330003b0b5b579b50bfdb5b67b3a269208585bf5dd3c0aa84c7e4d7
Canonical record JSON
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