Pith Number

pith:2ABKKND4

pith:2026:2ABKKND4I7HSUQCCNWDUNIKA34

not attested not anchored not stored refs resolved

CAST: Causal Anchored Simplex Transport for Distribution-Valued Time Series

Jiecheng Lu, Jieqi Di, Runhua Wu, Yuwei Zhou

CAST uses causal context to retrieve non-aliased successors then anchors and transports them on the simplex to forecast distribution time series.

arxiv:2605.16919 v1 · 2026-05-16 · stat.ML · cs.LG

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{2ABKKND4I7HSUQCCNWDUNIKA34}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

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

CAST attains the best average rank on both one-step KL (1.27) and autoregressive rollout JSD (1.91), winning 8/11 sections on each metric against a broad statistical, compositional, recurrent, convolutional, and Transformer baseline set, and top-2 on all 11 sections for offline KL.

C2weakest assumption

The assumption that causal context can be used to retrieve non-aliased empirical successors and that supports are ordered so that the additional Pinsker separation holds when the transported successor lies outside the no-transport anchor hull.

C3one line summary

CAST is a successor-local operator for causal forecasting of simplex-valued time series that retrieves empirical successors from causal context, stabilizes them with a persistence anchor, and applies bounded local stochastic transport while preserving the simplex by construction.

References

72 extracted · 72 resolved · 0 Pith anchors

[1] Queueing, predictions, and large language models: Challenges and open problems.Stochastic Systems, 15(3):195–219, 2025 2025 · doi:10.1287/stsy.2025.0106

[2] TLC Trip Record Data 2025

[3] Journal of the Royal Statistical Society: Series B (Methodological) , author = 1982 · doi:10.1111/j.2517-6161.1982.tb01195.x

[4] Chapman and Hall, London, 1986 1986

[5] Ralph D. Snyder, J. Keith Ord, Anne B. Koehler, Keith R. McLaren, and Adrian Beaumont. Forecasting compositional time series: A state space approach. Working Paper 11/15, Department of Econometrics an 2015

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:03:30.455212Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d002a5347c47cf2a40426d8746a140df0a6d7354133a44a06baeee1e07f1546b

Aliases

arxiv: 2605.16919 · arxiv_version: 2605.16919v1 · doi: 10.48550/arxiv.2605.16919 · pith_short_12: 2ABKKND4I7HS · pith_short_16: 2ABKKND4I7HSUQCC · pith_short_8: 2ABKKND4

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/2ABKKND4I7HSUQCCNWDUNIKA34 \
  | 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: d002a5347c47cf2a40426d8746a140df0a6d7354133a44a06baeee1e07f1546b

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "7b4e208ee69a5b8a62f7f432f430fc59f831aee7084e70f97de1ff1233bfd74e",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "stat.ML",
    "submitted_at": "2026-05-16T10:23:09Z",
    "title_canon_sha256": "aa07ae6bd0c36c4def2073a97816fdfe9c13565f5d0b974ffad000ef2b7edd3e"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.16919",
    "kind": "arxiv",
    "version": 1
  }
}