Paper Citation Record · LEDGER

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting

As of 8 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2506.02389.

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

pith.paper-citation-record.v1
2506.02389 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:30:15.260931Z

measured 36 of 36 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

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verified fuzzy26
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c1c2a987-fe09-4fa0-b9fa-e17584e200cc · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 1

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Observation 10235192-a290-4fd8-9fb4-20aeb46bb1e5 · outbound

This paper cites Llama 3.2: Multilingual large language models.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Llama 3.2: Multilingual large language models

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.512676Z

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Observation 55dd5304-3b8e-49ce-91ea-bb89f2ea8970 · outbound

This paper cites Comparative study on th e effect of order and cut off frequency of butterworth low pass ﬁlter for removal of noise in ecg signal.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Comparative study on th e effect of order and cut off frequency of butterworth low pass ﬁlter for removal of noise in ecg signal

Reference 3

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Observation e0640f7f-98cc-4c1d-b607-e7e723d54972 · outbound

This paper cites Selection of the most suit able decomposition ﬁlter for the mea- surement of ﬂuctuating harmonics.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Selection of the most suit able decomposition ﬁlter for the mea- surement of ﬂuctuating harmonics

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.500263Z

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Observation 194439d7-a13d-49ff-a37d-c7d662b9dadf · outbound

This paper cites LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters

Reference 5

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Observation 8dafa29a-793c-4ac8-9df0-767ddcee701a · outbound

This paper cites Sd- former: Similarity-driven discrete transformer for time s eries generation.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Sd- former: Similarity-driven discrete transformer for time s eries generation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.493979Z

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Observation 6d39dbfb-84c1-4737-ab04-1db9ba0130b2 · outbound

This paper cites How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs

Reference 7

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Observation 8be00f32-8693-4622-8976-830c56afdbfd · outbound

This paper cites Deep learning wi th long short-term memory net- works for ﬁnancial market predictions.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Deep learning wi th long short-term memory net- works for ﬁnancial market predictions

Reference 8

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Observation 01e384a0-752d-481e-9870-33083a9f156b · outbound

This paper cites Large language models are zero- shot time series forecasters.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Large language models are zero- shot time series forecasters

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.481280Z

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Observation 41c9c930-1c47-4bab-8c13-1ca231323021 · outbound

This paper cites SOF TS: Efﬁcient multivariate time series forecasting with series-core fusion.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting SOF TS: Efﬁcient multivariate time series forecasting with series-core fusion

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.475147Z

Source-reported events for the cited work

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Observation 14f1aeb6-1be8-4470-96dd-d124560118ca · outbound

This paper cites An intelligent network t rafﬁc prediction method based on butterworth ﬁlter and cnn–lstm.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting An intelligent network t rafﬁc prediction method based on butterworth ﬁlter and cnn–lstm

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.469153Z

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Observation 80f712e8-a49b-463b-b92f-300234d7c75c · outbound

This paper cites Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 12

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Observation 1c3cadb6-4ff4-4316-9c50-602d3e67c3e2 · outbound

This paper cites Back to basics: The power of the multilayer perceptron in ﬁnancial time series foreca sting.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Back to basics: The power of the multilayer perceptron in ﬁnancial time series foreca sting

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.462450Z

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Observation 64e8aaa9-4a5a-4baf-afca-5997a953ad61 · outbound

This paper cites Autotimes: Au- toregressive time series forecasters via large language models.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Autotimes: Au- toregressive time series forecasters via large language models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.456216Z

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Observation d3b3e32e-6ecf-48eb-9360-abb6f03e5cba · outbound

This paper cites Trafﬁc ﬂow predic- tion with big data: A deep learning approach.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Trafﬁc ﬂow predic- tion with big data: A deep learning approach

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.448994Z

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Observation 5082bf9e-d801-4151-8dce-bb5aa92b7c91 · outbound

This paper cites Videotrain++: Gan-based adap tive framework for synthetic video trafﬁc generation.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Videotrain++: Gan-based adap tive framework for synthetic video trafﬁc generation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.442845Z

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Observation 8aa33e96-a780-419d-ad64-c472b15d469a · outbound

This paper cites Gpt-4o mini: Advancing cost-efﬁcient intelli gence.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Gpt-4o mini: Advancing cost-efﬁcient intelli gence

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.436466Z

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Observation ea455261-450a-44b1-af3f-80d1b4c0117e · outbound

This paper cites Fred- former: Frequency debiased transformer for time series for ecasting.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Fred- former: Frequency debiased transformer for time series for ecasting

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.424131Z

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Observation 5ce26483-1d62-431a-a6cc-bc28123290ae · outbound

This paper cites Large Language Models in Numberland: A Quick Test of Their Numerical Reasoning Abilities.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Large Language Models in Numberland: A Quick Test of Their Numerical Reasoning Abilities

Reference 19

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Observation fa4ba504-c079-43dd-b016-3ecb43a4703a · outbound

This paper cites Weatherbench: a benchmark data set for dat a-driven weather forecasting.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Weatherbench: a benchmark data set for dat a-driven weather forecasting

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.417664Z

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.

Observation 9a636586-5572-4016-9991-394ce589464b · outbound

This paper cites Llm processes: Numerical predictive distributions condition ed on natural language.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Llm processes: Numerical predictive distributions condition ed on natural language

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.411441Z

Source-reported events for the cited work

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Observation ab1834bf-2240-426e-b9a6-a7bd3b07919e · outbound

This paper cites Netdiffus : Network trafﬁc generation by diffusion models through time-series imaging.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Netdiffus : Network trafﬁc generation by diffusion models through time-series imaging

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.405001Z

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.

Observation f2cb7e60-5392-4377-9ee9-7f14a4c89090 · outbound

This paper cites A survey of transformer enabled time series synthesis.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting A survey of transformer enabled time series synthesis

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.398262Z

Source-reported events for the cited work

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Observation e3b28d00-8ef0-4695-808d-0d3dfe8c0488 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 24

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Observation 8c4f52b1-5f99-40aa-aaf5-d56b088c7904 · outbound

This paper cites From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples

Reference 25

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Observation 579c98db-0217-48b0-98ad-408a842f382c · outbound

This paper cites Learning latent seasonal-trend representations for time s eries forecasting.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Learning latent seasonal-trend representations for time s eries forecasting

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.392060Z

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.

Observation 8d0c3e50-47d0-46fa-89c8-0286ff4f0d79 · outbound

This paper cites A utoformer: Decomposition transformers with auto-correlation for long-term series f orecasting.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting A utoformer: Decomposition transformers with auto-correlation for long-term series f orecasting

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.385644Z

Source-reported events for the cited work

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Observation 46c6448f-6980-48b5-9cce-847ee92df9f9 · outbound

This paper cites Adversarial sparse transformer for time series forecasting.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Adversarial sparse transformer for time series forecasting

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.378435Z

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

Observation 6386c2ff-fc60-4a9c-a8f0-54ad80989866 · outbound

This paper cites Promptcast: A new prompt-base d learning paradigm for time series forecasting.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Promptcast: A new prompt-base d learning paradigm for time series forecasting

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.371286Z

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.

Observation 25613631-35db-4f93-8bce-9a14e13fae19 · outbound

This paper cites Fouriergnn: Rethinking multivariate time se ries forecasting from a pure graph perspective.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Fouriergnn: Rethinking multivariate time se ries forecasting from a pure graph perspective

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.363588Z

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.

Observation c8562229-e391-4569-b79d-1db43e8cc5c8 · outbound

This paper cites Frequency-domain MLPs are m ore effective learners in time series forecasting.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Frequency-domain MLPs are m ore effective learners in time series forecasting

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.356466Z

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.

Observation 225e818e-b400-4fdc-8ad1-79c58a9d286d · outbound

This paper cites Multivariate Probabilistic Time Series Forecasting with Correlated Errors.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Multivariate Probabilistic Time Series Forecasting with Correlated Errors

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:30:15.285875Z

Source-reported events for the cited work

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Observation 9786f002-d10d-4f32-bd4a-0ac3f22377cd · outbound

This paper cites Informer: Beyond efﬁcient transformer for long s equence time-series forecasting.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Informer: Beyond efﬁcient transformer for long s equence time-series forecasting

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.350036Z

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.

Observation a5dfe175-05ec-41ce-8909-0d775eae2e7d · outbound

This paper cites Fedformer: Frequency enhanced decomposed transformer for long-term s eries forecasting.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Fedformer: Frequency enhanced decomposed transformer for long-term s eries forecasting

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.343358Z

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.

Observation 5c7eb9b3-9cbd-4e53-ad28-a01eed6ab1ba · outbound

This paper cites Consider the distribution. Predict the next few lines. INT EGER component of the value SHOULD be SAME as the train data. ONLY provide numerica l values.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Consider the distribution. Predict the next few lines. INT EGER component of the value SHOULD be SAME as the train data. ONLY provide numerica l values

Reference 35

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T11:30:15.336248Z

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.

Observation 3fdd9d8f-75ae-42b7-b1d8-98d384b8e354 · outbound

This paper cites an unresolved cited work.

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting Unresolved cited work

Reference 2024

Resolution: parse uncertain; raw_fallback, observed 2026-08-07T11:30:15.430377Z

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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