Pith Number

pith:IMLN6CJR

pith:2026:IMLN6CJRIAUFAZNULT4ENI5DQS

not attested not anchored not stored refs pending

Autoregressive One-Step Generative Modeling for Dynamical System Forecasting

Tianyue Yang, Xiao Xue

MeLISA delivers one-step blockwise generative forecasting for dynamical systems that improves short-term accuracy and long-horizon statistical fidelity over neural operators while matching or exceeding their inference speed.

arxiv:2605.05540 v2 · 2026-05-07 · cs.LG · physics.flu-dyn

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\usepackage{pith}
\pithnumber{IMLN6CJRIAUFAZNULT4ENI5DQS}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

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

MeLISA outperforms neural-operator baselines on short-term forecasting accuracy and long-horizon statistical metrics, including energy spectra, turbulent kinetic energy, and mixing-rate-related dynamics, while achieving inference speeds comparable to, and in some cases faster than, neural operators.

C2weakest assumption

That the Window-Consistency MeanFlow objective combined with the Time Increment Consistency loss will stabilize long-horizon rollouts and preserve statistical structure without introducing artifacts or requiring additional post-hoc corrections.

C3one line summary

Receipt and verification

First computed	2026-07-28T02:23:32.096967Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

4316df093140285065b45cf846a3a384b888813392130da0eb269a83c405c863

Aliases

arxiv: 2605.05540 · arxiv_version: 2605.05540v2 · doi: 10.48550/arxiv.2605.05540 · pith_short_12: IMLN6CJRIAUF · pith_short_16: IMLN6CJRIAUFAZNU · pith_short_8: IMLN6CJR

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/IMLN6CJRIAUFAZNULT4ENI5DQS \
  | 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: 4316df093140285065b45cf846a3a384b888813392130da0eb269a83c405c863

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "2f6a418b0e469850555349606e8328c08aa9a251b6f6c5fcb6bdc36f8e6b54c0",
    "cross_cats_sorted": [
      "physics.flu-dyn"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-07T00:41:47Z",
    "title_canon_sha256": "ecd340cccd0642893ab85be5612af305bc910bd69c266ffc229f3f8638a02da0"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.05540",
    "kind": "arxiv",
    "version": 2
  }
}