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Paper Citation Record · LEDGER

TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:2310.04948.

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

pith.paper-citation-record.v1
2310.04948 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:26:54.471141Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:30:07.231037Z

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f37eb6df-cda2-4e00-911f-bceea0b3811c · inbound

Deep Time Series Models: A Comprehensive Survey and Benchmark cites this paper.

Deep Time Series Models: A Comprehensive Survey and Benchmark TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 55

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arxiv_id, observed 2026-05-23T23:05:51.467777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T23:03:45.096751Z digest=sha256:2d7f186012fb39d2c0ddb0c26b6c1bbb380911218080beda156c45d951cc646f

Observation fb4a7b4a-08ae-4b91-92d2-b5abd470b8f2 · inbound

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis cites this paper.

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 35

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arxiv_id, observed 2026-05-23T19:45:47.124040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T19:45:39.130509Z digest=sha256:9586d473be8252b5fb8af953ede7f8005d15ef7e99abe26bf95047361f6e9304

Observation 7a02a285-51cc-4b15-a390-cf430340fcc4 · inbound

Large Language models for Time Series Analysis: Techniques, Applications, and Challenges cites this paper.

Large Language models for Time Series Analysis: Techniques, Applications, and Challenges TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 49

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source=pdf_text observed=2026-08-07T15:26:54.471141Z digest=sha256:f90afbd681543e1c841858fc4b26354b9a56b380c340a40fe1e363f62c9754fc

Observation dca585c9-0c93-45da-89b6-ae6114c79f4a · inbound

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection cites this paper.

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 27

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no resolver link, observed 2026-08-07T10:28:42.267258Z

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source=pdf_text observed=2026-08-07T10:28:42.267258Z digest=sha256:880f0dbfef0fa3bbb205da64ae5ee6457ed47b8ba08db849aa37c47960367965

Observation 6a9f81e4-710a-4225-88e1-6fb4db85126c · inbound

Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting cites this paper.

Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 33

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no resolver link, observed 2026-08-06T18:01:26.539715Z

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source=pdf_text observed=2026-08-06T18:01:26.539715Z digest=sha256:3291c7c9dd459e4a5624ffbe707b84b861a7cb5c6d7f04f9cc79e4834307e1f1

Observation 5c2df10b-0997-45c6-a123-fb8e6477820e · inbound

Fusing Large Language Models with Temporal Transformers for Time Series Forecasting cites this paper.

Fusing Large Language Models with Temporal Transformers for Time Series Forecasting TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 2023

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no resolver link, observed 2026-08-06T17:43:36.297956Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:43:36.297956Z digest=sha256:c01653c618dfdf606061f124dc8380f56b8cca2c902bbda248cdce50e2365461

Observation c88630ce-e66e-4718-be14-4e2ecd7e5649 · inbound

Reprogramming Vision Foundation Models for Spatio-Temporal Forecasting cites this paper.

Reprogramming Vision Foundation Models for Spatio-Temporal Forecasting TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 5

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no resolver link, observed 2026-08-06T17:46:42.029777Z

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source=arxiv_source observed=2026-08-06T17:46:42.029777Z digest=sha256:7cea7fb08b0d4a14ce09dbd23ee617b147480a3f5366781f8c8149834ef6b70d

Observation 1c1804c7-6a27-4281-b914-3a2ca9111ab9 · inbound

Causal Graph Fuzzy LLMs: A First Introduction and Applications in Time Series Forecasting cites this paper.

Causal Graph Fuzzy LLMs: A First Introduction and Applications in Time Series Forecasting TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 8

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no resolver link, observed 2026-08-06T15:04:11.137189Z

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source=pdf_text observed=2026-08-06T15:04:11.137189Z digest=sha256:a70ffa29a00b58541a6237e0755c5935dd34071f80011a1ad71bc26336704f40

Observation 0a1e5efe-ee16-46f1-b5b1-ae1ef6b27901 · inbound

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction cites this paper.

LSDM: LLM-Enhanced Spatio-temporal Diffusion Model for Service-Level Mobile Traffic Prediction TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 62

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no resolver link, observed 2026-08-06T14:52:30.402593Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:30.402593Z digest=sha256:7a3fd8a5cb1b19879d72727f9243ad3a5138976c7fa7d2064a3a59ff331f08b4

Observation 1ea95ebc-01cc-42aa-8e9d-c9c5f53f4c41 · inbound

Foundation Models for Demand Forecasting via Dual-Strategy Ensembling cites this paper.

Foundation Models for Demand Forecasting via Dual-Strategy Ensembling TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 3

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no resolver link, observed 2026-08-06T12:09:39.411328Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:09:39.411328Z digest=sha256:37dca29535060c81a08ca2ac9cf7098e234d94220afcdd2d3334b9217359896a

Observation 94b5f497-58bb-4c6d-9d0d-ed106294dbb6 · inbound

On Identifying Why and When Foundation Models Perform Well on Time-Series Forecasting Using Automated Explanations and Rating cites this paper.

On Identifying Why and When Foundation Models Perform Well on Time-Series Forecasting Using Automated Explanations and Rating TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 12

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no resolver link, observed 2026-08-05T15:10:28.304185Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:10:28.304185Z digest=sha256:d2b4cbcaccb85ac03f43fee92b3ec15fca2a77495bc4e9f3445bb7defd7d558d

Observation 1645107e-eabe-4401-b9f8-e7fe40ce0e16 · inbound

BALM-TSF: Balanced Multimodal Alignment for LLM-Based Time Series Forecasting cites this paper.

BALM-TSF: Balanced Multimodal Alignment for LLM-Based Time Series Forecasting TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 4

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source=pdf_text observed=2026-08-05T13:29:00.791648Z digest=sha256:26361b130d9c261da656ba8eb1dd45fc9433a68bf2a1e9958e49857d77642da3

Observation a4d736a0-0452-486d-a5aa-85c5f31d376f · inbound

Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting cites this paper.

Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 6

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verified exact
arxiv_id, observed 2026-05-25T08:25:34.155340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 11f089b3-86bc-4e12-8093-03ad70f608d8 · inbound

Taming Text-to-Sounding Video Generation via Advanced Modality Condition and Interaction cites this paper.

Taming Text-to-Sounding Video Generation via Advanced Modality Condition and Interaction TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 2024

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no resolver link, observed 2026-08-04T12:38:56.312366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:38:56.312366Z digest=sha256:57c25906d121e77f940bebe390654f3d6ade3ae8e136d2603f5b78fecafd85b9

Observation 7cb01dd6-19f5-4597-9867-9583270727ba · inbound

MAP4TS: A Multi-Aspect Prompting Framework for Time-Series Forecasting with Large Language Models cites this paper.

MAP4TS: A Multi-Aspect Prompting Framework for Time-Series Forecasting with Large Language Models TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 2

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verified exact
arxiv_id, observed 2026-05-22T12:36:32.511386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4b2a3109-09d0-4f7a-af06-a22400cdc804 · inbound

AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Interactive Time Series Forecasting cites this paper.

AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Interactive Time Series Forecasting TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 4

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verified exact
arxiv_id, observed 2026-05-17T23:10:26.178196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T23:07:55.891663Z digest=sha256:0218bd41edea0b8d616bb2d7309a1e688a267c44a7ee6a596fceb994d931dc4c

Observation 16a61787-7cee-4c6c-8b88-df90f1660120 · inbound

Discrete Prototypical Memories for Federated Time Series Foundation Models cites this paper.

Discrete Prototypical Memories for Federated Time Series Foundation Models TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 4

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verified exact
arxiv_id, observed 2026-05-10T23:35:52.028972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T18:59:18.819953Z digest=sha256:5c0d1d60f7b0baf89a92313fd1c2f68d629f0522c042f6528108a69190e1c49c

Observation c6f35693-62b5-468c-9965-13efab01ad94 · inbound

TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale cites this paper.

TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 8

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arxiv_id, observed 2026-05-11T10:36:04.345350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T15:25:02.732205Z digest=sha256:507cb4f561413d9556d7428fcc691672e803f1e0a1c0b2cc643bfa605f503caf

Observation f5906bd9-77a5-4dfb-81a5-6de4cc45eed0 · inbound

Conditional Imputation for Within-Modality Missingness in Multi-Modal Federated Learning cites this paper.

Conditional Imputation for Within-Modality Missingness in Multi-Modal Federated Learning TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 3

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arxiv_id, observed 2026-05-11T20:36:09.707554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ba5c7cc4-386d-4f40-be46-a72ebd7dab36 · inbound

MILM: Large Language Models for Multimodal Irregular Time Series with Informative Sampling cites this paper.

MILM: Large Language Models for Multimodal Irregular Time Series with Informative Sampling TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 32

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arxiv_id, observed 2026-05-14T20:19:27.819666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-14T20:16:47.340541Z digest=sha256:f24b529eba94e27fce73e9dc7f9af8e57092ba9ebeacb82baeb74bfe7176de61

Observation 3c785689-a48d-46af-bd12-85eeca7e563d · inbound

TRACE: A Temporal Conditional Estimation for Multimodal Time Series Foundation Models cites this paper.

TRACE: A Temporal Conditional Estimation for Multimodal Time Series Foundation Models TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 4

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verified exact
arxiv_id, observed 2026-07-02T12:46:57.002897Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 234a9197-0779-4544-b390-d3e072665460 · inbound

$\text{DT}^2$: Decision-Targeted Digital Twins cites this paper.

$\text{DT}^2$: Decision-Targeted Digital Twins TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 28

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arxiv_id, observed 2026-07-04T20:30:07.232671Z

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Observation 2abf6c67-add8-4ce4-986b-aa6e9ab09d16 · inbound

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

Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 28

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arxiv_id, observed 2026-07-03T17:38:43.411552Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 678a0003-5bf1-4545-b755-ff2a71d59e80 · inbound

TSRouter: Dynamic Modality-Model Selection for Time Series Reasoning cites this paper.

TSRouter: Dynamic Modality-Model Selection for Time Series Reasoning TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 5

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Observation bf7f08f0-f680-4a02-b9ac-cf8563d664c9 · inbound

TSRouter: Dynamic Modality-Model Selection for Time Series Reasoning cites this paper.

TSRouter: Dynamic Modality-Model Selection for Time Series Reasoning TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 5

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Observation 59b67d14-94d3-4e78-9a4e-8cb9d0a79f3a · inbound

Hopformer: Homogeneity-Pursuit Transformer for Time Series Forecasting cites this paper.

Hopformer: Homogeneity-Pursuit Transformer for Time Series Forecasting TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 3

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source=pdf_text observed=2026-08-01T05:16:38.160646Z digest=sha256:159bc297d7190feb82dc743bfc6371b9bc718ef62875ff30a7bcc327a7b16682

Observation 08c1f456-385a-4784-bc24-f87f0f068ec8 · 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 TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 1

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no resolver link, observed 2026-08-01T01:06:47.359737Z

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