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Paper Citation Record · LEDGER

Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2310.05063.

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

pith.paper-citation-record.v1
2310.05063 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:10:55.697934Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation dd06aaa8-7e7d-435a-a161-d977d3addff7 · inbound

Out-of-Distribution Generalization in Time Series: A Survey cites this paper.

Out-of-Distribution Generalization in Time Series: A Survey Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain

Reference 162

Resolution
verified exact
arxiv_id, observed 2026-05-23T00:22:18.621743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-23T00:17:25.925774Z digest=sha256:bf95f657f311f6926e6afb4814152d78f69cad3c7ad2abb0c7cfc542e801f82a

Observation 8059cdac-a328-4c2c-b198-87b43f934f7d · inbound

Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics cites this paper.

Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-16T10:10:55.697934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:10:55.697934Z digest=sha256:c12992293af33375318c66ce1d551b7e7af70563897859532f7c28f0d2a348e5

Observation 260b3ae7-7fe2-49d4-a8a5-2dd60930ea18 · inbound

DELPHYNE: A Pre-Trained Model for General and Financial Time Series cites this paper.

DELPHYNE: A Pre-Trained Model for General and Financial Time Series Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-15T22:15:53.477817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:15:53.477817Z digest=sha256:51eec9724c2036afc80364bd8ddeaaaffe7777933a51dc980d0ee2757785abce

Observation dc959aa5-139a-4efe-bffc-25dc8914b89f · inbound

Feature to Dynamics: Feature-space to Autoregression strategy for Zero-shot Time Series Forecasting cites this paper.

Feature to Dynamics: Feature-space to Autoregression strategy for Zero-shot Time Series Forecasting Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-28T17:22:24.550861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-28T17:20:32.648181Z digest=sha256:fc2aa34e3cfb5d943bc7ccb673d327908e50a0a16b3f6755a15bd38e2ca8e181

Observation b8f89a30-9fb4-4297-8c70-9d38e8da2395 · inbound

REGEN: Reference-Guided Synthetic Multivariate Time Series Generation for Forecasting cites this paper.

REGEN: Reference-Guided Synthetic Multivariate Time Series Generation for Forecasting Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain

Reference 50

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T06:06:41.707715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-28T07:31:08.371696Z digest=sha256:51a0c84a203a0e7c6fc82f76de108bd377452716da01220da0939cd2cebee345

Observation 56e08f50-89f1-4362-b5a4-40adae3f607e · inbound

CloudCons: A Comprehensive End-to-End Benchmark for Cloud Resource Consolidation cites this paper.

CloudCons: A Comprehensive End-to-End Benchmark for Cloud Resource Consolidation Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-07-03T14:28:31.508900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-27T07:03:29.070834Z digest=sha256:6c4f6b66c1f15cf5849a79dd0dd6fb5462bc7977ea1351b2f15da83863d3fb48

Observation 53251c1e-52cc-450f-8a76-8a2a02f54ac5 · inbound

Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis cites this paper.

Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T17:38:43.381766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-07-03T17:34:37.552706Z digest=sha256:0374ba3137dff1070bdd9d6f0a853569b381dc78608c32b99d0a01dde955197e