pith:6TOAJNEL
CAMEO: A Conditional and Quality-Aware Multi-Agent Image Editing Orchestrator
CAMEO turns conditional image editing into a feedback-driven multi-agent process that raises win rates by 20 percent over single-step models.
arxiv:2604.03156 v2 · 2026-04-03 · cs.CV
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Record completeness
Claims
CAMEO consistently achieves 20% more win rate on average compared to multiple state-of-the-art models, demonstrating improved robustness, controllability, and structural reliability in conditional image editing.
That the multi-agent decomposition with embedded evaluation will reliably detect and correct structural and contextual inconsistencies without introducing new artifacts or requiring impractical computation, and that comparisons against independent evaluation models are unbiased and comprehensive.
CAMEO uses coordinated agents for planning, prompting, generation, and quality feedback to achieve higher structural reliability in conditional image editing than single-step models.
Receipt and verification
| First computed | 2026-06-19T16:11:22.777263Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
f4dc04b48b49e04f19860c765f64daf7991dc664d542d6b7b095ab04913b2bcb
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/6TOAJNELJHQE6GMGBR3F6ZG266 \
| 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: f4dc04b48b49e04f19860c765f64daf7991dc664d542d6b7b095ab04913b2bcb
Canonical record JSON
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