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pith:E25GRCME

pith:2026:E25GRCMEVIVYKWIEQV37DKGIBP
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Divide and Conquer: Decoupled Representation Alignment for Multimodal World Models

Bin Xia, Dingkang Liang, Guangmo Yi, Jianlou Si, Jun Huang, Junyuan Xiao, Qiang Lyu, Shurui Shi, Tongtong Su, Wenming Yang, Xin Zhou, Yixuan Ye

Decoupling modality features in a diffusion model allows each to align with a separate foundation model expert for improved multi-modal video generation.

arxiv:2605.01896 v2 · 2026-05-03 · cs.CV

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Claims

C1strongest claim

This design enables joint optimization, fully exploiting priors from multiple foundation models. Extensive experiments demonstrate that our method significantly outperforms baselines in visual quality and long-term consistency.

C2weakest assumption

Foundation models trained on different modality spaces naturally capture distinct domain-specific priors, acting as complementary experts, and that the proposed decoupling regularization will maintain this complementarity without introducing new conflicts during joint optimization.

C3one line summary

M²-REPA decouples modality-specific features inside a diffusion model and aligns each to its matching expert foundation model via an alignment loss plus a decoupling regularizer, yielding better visual quality and long-term consistency in multi-modal video generation.

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First computed 2026-07-02T01:17:32.037792Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

26ba688984aa2b8559048577f1a8c80bf6317aec6c146228e1bf54ec6a9a7857

Aliases

arxiv: 2605.01896 · arxiv_version: 2605.01896v2 · doi: 10.48550/arxiv.2605.01896 · pith_short_12: E25GRCMEVIVY · pith_short_16: E25GRCMEVIVYKWIE · pith_short_8: E25GRCME
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/E25GRCMEVIVYKWIEQV37DKGIBP \
  | 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: 26ba688984aa2b8559048577f1a8c80bf6317aec6c146228e1bf54ec6a9a7857
Canonical record JSON
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    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-03T14:22:22Z",
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