Pith Number

pith:QVJRKQ34

pith:2026:QVJRKQ347MVGPYRGNS3FHQXURD

not attested not anchored not stored refs pending

Phantom: Physics-Infused Video Generation via Joint Modeling of Visual and Latent Physical Dynamics

Ismini Lourentzou, Jerry Xiong, Tianjiao Yu, Ying Shen

Phantom generates videos that are both visually realistic and physically consistent by jointly modeling visuals and latent physical dynamics.

arxiv:2604.08503 v3 · 2026-04-09 · cs.CV

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Record completeness

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3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

By integrating the inference of physical-aware video representation directly into the video generation process, Phantom produces video sequences that are both visually realistic and physically consistent.

C2weakest assumption

That a physics-aware video representation can serve as an abstract yet informative embedding of the underlying physics, facilitating joint prediction without requiring explicit specification of complex physical dynamics and properties.

C3one line summary

Phantom generates visually realistic and physically consistent videos by jointly modeling visual content and latent physical dynamics via an abstract physics-aware representation.

Formal links

2 machine-checked theorem links

Cited by

1 paper in Pith

NEWTON: Agentic Planning for Physically Grounded Video Generation

Receipt and verification

First computed	2026-05-20T01:05:12.819365Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

855315437cfb2a67e2266cb653c2f488f0cc060a9b72dd2f9639b4540f2cd197

Aliases

arxiv: 2604.08503 · arxiv_version: 2604.08503v3 · doi: 10.48550/arxiv.2604.08503 · pith_short_12: QVJRKQ347MVG · pith_short_16: QVJRKQ347MVGPYRG · pith_short_8: QVJRKQ34

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/QVJRKQ347MVGPYRGNS3FHQXURD \
  | 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: 855315437cfb2a67e2266cb653c2f488f0cc060a9b72dd2f9639b4540f2cd197

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "a975afc61d433232bc6a7d3a2fa8f57c94145e99f83df3e6d928490501f272c8",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-04-09T17:48:46Z",
    "title_canon_sha256": "205769136e09089fc222600ce289fae2ad9300698be9fa3f03c1c72bb9193c9f"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.08503",
    "kind": "arxiv",
    "version": 3
  }
}