pith:BPZB3OHI
Improving Classifier-Free Guidance of Flow Matching via Manifold Projection
Reformulating classifier-free guidance in flow matching as manifold-constrained homotopy optimization reduces sensitivity to guidance scales.
arxiv:2601.21892 v2 · 2026-01-29 · cs.CV · cs.AI
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Claims
We reformulate the CFG sampling as a homotopy optimization with a manifold constraint. This formulation necessitates a manifold projection step, which we implement via an incremental gradient descent scheme during sampling.
That the velocity field in flow matching exactly corresponds to the gradient of a sequence of smoothed distance functions guiding latent variables toward the scaled target image set, making standard CFG merely an approximation whose gap controls sensitivity.
Reformulates CFG sampling in flow matching as homotopy optimization with manifold projection via incremental gradient descent and Anderson acceleration, yielding better fidelity and robustness without retraining.
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Receipt and verification
| First computed | 2026-05-18T03:09:24.099324Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
0bf21db8e851918bb1263dff0284056554661e20552fa154f622207d8516802a
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/BPZB3OHIKGIYXMJGHX7QFBAFMV \
| 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: 0bf21db8e851918bb1263dff0284056554661e20552fa154f622207d8516802a
Canonical record JSON
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