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Paper Citation Record · LEDGER

One Fits All:Power General Time Series Analysis by Pretrained LM

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2302.11939.

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

pith.paper-citation-record.v1
2302.11939 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:25:19.314174Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

118
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 383cb456-2619-4829-8a91-948114cbf7a5 · inbound

A decoder-only foundation model for time-series forecasting cites this paper.

A decoder-only foundation model for time-series forecasting One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 20

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verified exact
arxiv_id, observed 2026-05-16T18:07:21.290471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation de710018-9898-403d-836a-2eb15dc4c49b · inbound

Universal Time-Series Representation Learning: A Survey cites this paper.

Universal Time-Series Representation Learning: A Survey One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 244

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verified exact
arxiv_id, observed 2026-05-24T04:28:53.317429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-24T04:26:45.527625Z digest=sha256:d6ec0578e1cd2c85a842e2754d21c96c20773f9145ed490ea272caf87d8ef923

Observation e3e0451a-6edd-456a-bf4a-b6ccc6715e10 · inbound

Evaluation of a Foundational Model and Stochastic Models for Forecasting Sporadic or Spiky Production Outages of High-Performance Machine Learning Services cites this paper.

Evaluation of a Foundational Model and Stochastic Models for Forecasting Sporadic or Spiky Production Outages of High-Performance Machine Learning Services One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 28

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unresolved
no resolver link, observed 2026-08-06T21:25:19.314174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 85b12086-4710-46c2-8e2b-72dadff2d83f · inbound

LLM4Delay: Flight Delay Prediction via Cross-Modality Adaptation of Large Language Models and Aircraft Trajectory Representation cites this paper.

LLM4Delay: Flight Delay Prediction via Cross-Modality Adaptation of Large Language Models and Aircraft Trajectory Representation One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-18T04:30:53.675481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T04:26:15.232765Z digest=sha256:075f1d04191ca9786d86c8bd667aa7dd34868dd2e25ccbbb90810b38f40b59c4

Observation 1a08a9f1-3375-4ea2-b8b3-b4014e747785 · inbound

LLM4Delay: Flight Delay Prediction via Cross-Modality Adaptation of Large Language Models and Aircraft Trajectory Representation cites this paper.

LLM4Delay: Flight Delay Prediction via Cross-Modality Adaptation of Large Language Models and Aircraft Trajectory Representation One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-04T08:21:32.361506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:21:32.361506Z digest=sha256:64e23f99c4696ea18aa18bbd274cc5cbc36b5eef251ddc0661a9b4303f692614

Observation 68b375c2-2dc5-418a-ad08-c473c677b72b · inbound

TSVer: A Benchmark for Fact Verification Against Time-Series Evidence cites this paper.

TSVer: A Benchmark for Fact Verification Against Time-Series Evidence One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:00:34.119189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 557e2368-9381-4f0a-ac35-57cb56cec323 · inbound

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis cites this paper.

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-17T04:39:03.445411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T04:34:43.406156Z digest=sha256:d8918a8656ec1889a2018a7627efb19f02d50f9b84dce7cce15c3d80e4811e72

Observation d3c30017-aea7-494b-b6e9-002cbdfe12ba · inbound

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis cites this paper.

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 26

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verified exact
arxiv_id, observed 2026-05-21T18:20:29.046609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T18:18:33.265640Z digest=sha256:10741f9610014529338a3b618c2d3821e4a167b5b1c71076071d7a770659eb10

Observation 7d4e6eed-28ee-4767-8ffe-308a9b24d787 · inbound

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis cites this paper.

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-03T20:16:43.483347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:16:43.483347Z digest=sha256:63bdda48a6ce30d86e8f5abb776f3755b0f010ffb168cb98c67b0c1505569f41

Observation 9e79aa33-cf4f-4e7a-b2f5-b34c9013e5ff · inbound

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection cites this paper.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 37

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unresolved
no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T22:02:51.907844Z digest=sha256:82e128ee3d1b68fe62371798daff9f2fd8fc841c49b23461f67d833aa14e9d78

Observation e577e84a-cc8c-4ca6-982d-594b2dcda526 · inbound

ADAPTive Input Training for Many-to-One Pre-Training on Time-Series Classification cites this paper.

ADAPTive Input Training for Many-to-One Pre-Training on Time-Series Classification One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 16

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verified exact
arxiv_id, observed 2026-05-11T07:25:59.994446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation f5e9f26a-3a65-42dc-9cd5-dca01cba25f5 · inbound

From Index to Equity: Pre-Training Transformers for Stock Return Prediction cites this paper.

From Index to Equity: Pre-Training Transformers for Stock Return Prediction One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:15:46.389515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 4b14ab01-9159-4da8-a2e8-c82708e2d095 · inbound

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

Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 13

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metadata mismatch
arxiv_id, observed 2026-07-03T17:38:43.374221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3025a45b-3d36-44b1-9168-eb44ecb41895 · inbound

Probabilistic Low-Voltage Peak Load Forecasting with Time Series Foundation Models Evaluated on Application-Oriented Metrics cites this paper.

Probabilistic Low-Voltage Peak Load Forecasting with Time Series Foundation Models Evaluated on Application-Oriented Metrics One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 71

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metadata mismatch
arxiv_id, observed 2026-07-03T17:28:44.051622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 95a907fd-e4e1-46cd-ab3b-a10bf3a1eb15 · inbound

Modular Foundation Models for Time-Series Perception in Digital Twins cites this paper.

Modular Foundation Models for Time-Series Perception in Digital Twins One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 126

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unresolved
no resolver link, observed 2026-07-12T01:22:51.284207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T01:22:51.284207Z digest=sha256:aba8b0cd64897200bc77ba2005188686ce67f76a62f3c5513bcd1493f614eb5c

Observation 4c6572ff-addc-4fe5-8ee8-3bca73a8771e · inbound

LLM-Guided Task-Semantic Field Factorization for Industrial Process Forecasting cites this paper.

LLM-Guided Task-Semantic Field Factorization for Industrial Process Forecasting One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 11

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verified exact
local_arxiv, observed 2026-07-11T01:17:44.740849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 48b4a5be-d486-4ecd-9277-f0264db58ff3 · inbound

A Cost-Effective Multimodal LLM Reasoning Framework for Question Answering over Irregular Clinical Time Series cites this paper.

A Cost-Effective Multimodal LLM Reasoning Framework for Question Answering over Irregular Clinical Time Series One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 32

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unresolved
no resolver link, observed 2026-08-01T01:06:50.058404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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