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Paper Citation Record · LEDGER

Towards Stability of Autoregressive Neural Operators

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2306.10619.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2306.10619 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:05:35.478484Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-01T18:45:58.242614Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 602729c0-ff59-47f1-889c-b8f341dc30a2 · inbound

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for time-dependent PDEs cites this paper.

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for time-dependent PDEs Towards Stability of Autoregressive Neural Operators

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T20:05:35.478484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:05:35.478484Z digest=sha256:12487e15dcd28f008211b2dcbaa4c608beb72f4923fe334a6c8ec28e028a1cdb

Observation c0b9dd94-1895-43fb-8a48-850f0fe0dc3f · inbound

Bubbleformer: Forecasting Boiling with Transformers cites this paper.

Bubbleformer: Forecasting Boiling with Transformers Towards Stability of Autoregressive Neural Operators

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T13:02:55.355899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:02:55.355899Z digest=sha256:36ead29e926f85ae6662ab5d1c83ccafbd94046959dba2cc862772a1aed1550e

Observation 84ea3fcc-b171-4c5e-9d78-5af716e2ba8f · inbound

Diffeomorphic Neural Operator Learning cites this paper.

Diffeomorphic Neural Operator Learning Towards Stability of Autoregressive Neural Operators

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T22:39:54.647322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:39:54.647322Z digest=sha256:321161d911658eea86f6a1951aa37ecc24035bdfc0751e174d6202f22b8b542d

Observation 06934b9d-72e3-407c-835c-c99b419d5266 · inbound

MoWE : A Mixture of Weather Experts cites this paper.

MoWE : A Mixture of Weather Experts Towards Stability of Autoregressive Neural Operators

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-04T19:49:23.361042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:49:23.361042Z digest=sha256:3386d2e0a9f4b73ec360bf09d17fc62cbc90052a5b32e93983c9bde2dcfca27a

Observation 7b46450b-d414-4976-b23e-a3a73c15e750 · inbound

Autoregressive One-Step Generative Modeling for Dynamical System Forecasting cites this paper.

Autoregressive One-Step Generative Modeling for Dynamical System Forecasting Towards Stability of Autoregressive Neural Operators

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-02T14:48:33.075304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:48:33.075304Z digest=sha256:a9a41cbb61c51db66bb4985128cd33a4a8b5031e49964dcfb94df99a9196b4ef

Observation 5fed43e4-077f-4e16-b467-570e7b196039 · inbound

Mechanism Learning: Prototype-Anchored Mechanism Inference for Scientific Forecasting cites this paper.

Mechanism Learning: Prototype-Anchored Mechanism Inference for Scientific Forecasting Towards Stability of Autoregressive Neural Operators

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-20T15:28:25.577077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T15:24:37.958002Z digest=sha256:09b87590ae8371f9f8b607f503691f84b87268208ad95e9acdf91bde5a3fe98c

Observation 4115dcff-4912-428b-a0fd-7f2e4c345ba0 · inbound

Higher-Order Fourier Neural Operator: Explicit Mode Mixer for Nonlinear PDEs cites this paper.

Higher-Order Fourier Neural Operator: Explicit Mode Mixer for Nonlinear PDEs Towards Stability of Autoregressive Neural Operators

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T18:45:58.244313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-29T01:49:08.216819Z digest=sha256:1c2a0ccd94e7b4beb945ab817454136dc9198eca5272e65198d990e1224cb317

Observation 00cfe53c-840f-4cfa-a204-d941bc488a1e · inbound

A Physics-Regulated Neural Framework for Learning 3D Grain Growth Dynamics cites this paper.

A Physics-Regulated Neural Framework for Learning 3D Grain Growth Dynamics Towards Stability of Autoregressive Neural Operators

Reference 29

Resolution
unresolved
no resolver link, observed 2026-07-11T15:18:46.219931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T15:18:46.219931Z digest=sha256:0ce08cb41c5fc72c7b7b41382b43a81e392adc2f9e32e962d3e491b40c66479a

Observation 2af65bbe-f740-4b56-99cd-e2f9f6cf3be6 · inbound

Explainable quantum-compressed machine learning for complex fluid flows cites this paper.

Explainable quantum-compressed machine learning for complex fluid flows Towards Stability of Autoregressive Neural Operators

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-01T07:36:54.397788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T07:36:54.397788Z digest=sha256:b6123173e543f9b150e49b51ec0d9dc579f61b1531fa79c9593a3e2cea67675b