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Paper Citation Record · LEDGER

Towards Time Series Generation Conditioned on Unstructured Natural Language

As of 7 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2506.22927.

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

pith.paper-citation-record.v1
2506.22927 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:59:21.189027Z

measured 45 of 45 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

45 of 45 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved41
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cebcd597-9525-4e4f-bc86-5cc09b58a5ec · outbound

This paper cites Time-Causal VAE: Robust Financial Time Series Generator.

Towards Time Series Generation Conditioned on Unstructured Natural Language Time-Causal VAE: Robust Financial Time Series Generator

Reference 1

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Observation cf26197b-e2cb-4a75-8847-c6b7b8a62e02 · outbound

This paper cites Towards Controllable Time Series Generation.

Towards Time Series Generation Conditioned on Unstructured Natural Language Towards Controllable Time Series Generation

Reference 2

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Observation f3f25b64-bd58-4550-8d7d-7fbd02b23b52 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 3

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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 270d71fb-60a8-427c-8372-5c936db41a67 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 4

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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 5585f81c-6c55-4b11-b789-b06dbfab66f8 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 5

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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 0811971d-5dd3-4a7f-92c1-970299333e3f · outbound

This paper cites TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation.

Towards Time Series Generation Conditioned on Unstructured Natural Language TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation

Reference 6

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Source-reported events for the cited work

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Observation f280b933-ad9a-4017-98a9-0506509560b4 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Towards Time Series Generation Conditioned on Unstructured Natural Language BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 7

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Source-reported events for the cited work

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Observation 35730704-330e-49f5-8443-3f255e8b6c64 · outbound

This paper cites Can LLMs Serve As Time Series Anomaly Detectors?.

Towards Time Series Generation Conditioned on Unstructured Natural Language Can LLMs Serve As Time Series Anomaly Detectors?

Reference 8

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Observation 6671ae7c-81c3-4064-9b81-c3d8c11a1ce6 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 9

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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 8d6215ca-5c67-45f8-a727-ec7846d0db13 · outbound

This paper cites Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs.

Towards Time Series Generation Conditioned on Unstructured Natural Language Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs

Reference 10

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Observation f1b335c2-1a8b-4ba5-97b8-221bbb6c145d · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 11

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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 c16f3b36-77a0-4f66-9b3e-cabb226d798f · outbound

This paper cites TimeGPT-1.

Towards Time Series Generation Conditioned on Unstructured Natural Language TimeGPT-1

Reference 12

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Observation 5a1f65ad-44ec-4fdb-89ce-966667dcdba8 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 13

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Observation 9a863a8b-1ebd-4658-af8a-be32805c06b4 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 14

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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 04c50abc-c7a8-423e-81f5-a1431e276708 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 15

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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 76ac28cc-dd73-46e6-8e36-e7a9d7a52b3a · outbound

This paper cites Augmentation Scheme for Dealing with Imbalanced Network Traffic Classification Using Deep Learning.

Towards Time Series Generation Conditioned on Unstructured Natural Language Augmentation Scheme for Dealing with Imbalanced Network Traffic Classification Using Deep Learning

Reference 16

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Observation 8f8294df-af43-4d8b-a137-45db6283f5c0 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Towards Time Series Generation Conditioned on Unstructured Natural Language Gaussian Error Linear Units (GELUs)

Reference 17

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Observation 8530a9fa-962b-40b5-b099-671110506c47 · outbound

This paper cites Truth-Conditional Captioning of Time Series Data.

Towards Time Series Generation Conditioned on Unstructured Natural Language Truth-Conditional Captioning of Time Series Data

Reference 18

Resolution
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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 747ffe45-dd79-4c6e-926f-58cfc9f5a76a · outbound

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

Towards Time Series Generation Conditioned on Unstructured Natural Language Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 19

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Observation d454af99-f2a0-49cd-a737-f84b5bf387b8 · outbound

This paper cites ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data.

Towards Time Series Generation Conditioned on Unstructured Natural Language ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data

Reference 20

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Observation ee133ed9-2a72-4a4f-b4ec-f7b2bbc08e40 · outbound

This paper cites Hyndman, and Feng Li.

Towards Time Series Generation Conditioned on Unstructured Natural Language Hyndman, and Feng Li

Reference 21

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Observation 8887d61e-8a79-4989-ba2a-6a383bf632ce · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Towards Time Series Generation Conditioned on Unstructured Natural Language Adam: A Method for Stochastic Optimization

Reference 22

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Observation 8c180b65-e96d-4520-af0e-94d7e6f06201 · outbound

This paper cites Auto-Encoding Variational Bayes.

Towards Time Series Generation Conditioned on Unstructured Natural Language Auto-Encoding Variational Bayes

Reference 23

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Observation bfbd00dd-3bb6-42fd-8ccd-0a0c87ac35ef · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 24

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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 fb4580a1-0e44-408c-90aa-8e51d71c693c · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 25

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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 48645ae9-1dcf-4e8d-8c8a-bc1038773c09 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 26

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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 7726f8fd-3c93-464f-95b1-c1037d7fb120 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 27

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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 80425add-e6f5-44e2-9cd0-6e731b139fc9 · outbound

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Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 28

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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 2e3aec57-f5a6-48d6-9351-ff9cf177a902 · outbound

This paper cites an unresolved cited work.

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Reference 29

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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 ecdb0372-4f94-4cb1-9c69-aa7674e6a354 · outbound

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Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 30

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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 decee556-64f6-46e9-9b59-ef8dcb99b4e8 · outbound

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Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 31

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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 878cfa7a-d00a-4b98-9260-85cd47b4e31c · outbound

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Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 32

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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 0839129c-8872-4157-b201-b811acfc92a1 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 33

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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 d1b942b9-4e77-437f-87c2-c5f36695ca78 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 34

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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 b62c06bb-01d0-446a-b6cf-1bc104fe1ba2 · outbound

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Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 35

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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 b8698587-a401-4f96-a8ad-ab82ae2911d9 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 36

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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 aafb1bfe-d56c-44a1-a79c-4bb943527a61 · outbound

This paper cites Denoising Diffusion Implicit Models.

Towards Time Series Generation Conditioned on Unstructured Natural Language Denoising Diffusion Implicit Models

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3b960851-68a0-481d-b73f-2e1f765f9b06 · outbound

This paper cites Tanner and Wing Hung Wong.

Towards Time Series Generation Conditioned on Unstructured Natural Language Tanner and Wing Hung Wong

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f5b0f936-2b18-4fd1-8baf-5beb6fc839a6 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:59:23.357739Z

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=arxiv_source observed=2026-08-06T21:59:20.727734Z digest=sha256:b04a2b38d520cc6ddc4ea54c9614f8a595ce700b1b42cf2f4db9bca614aaf7e9

Observation 8db23257-c622-46f9-ab09-a7b6ac13f30e · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:59:23.201494Z

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=arxiv_source observed=2026-08-06T21:59:20.788061Z digest=sha256:54c8c054996050d30ae3a370d6d48dcf151de0ec9e3b6883965b7afe6fa5e5f6

Observation 48b51b1c-103d-40a8-bfc5-750eea43f76e · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:59:22.983460Z

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 3465919c-4c8e-4d35-9708-91fc00ae9691 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:59:22.855923Z

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=arxiv_source observed=2026-08-06T21:59:20.906358Z digest=sha256:d9e1a8a3a79d4a841ff2c7c933f829bb2dedc303298dc7264826cd1df86a050b

Observation d9ec9957-28f8-4e55-9ae9-02e7a05d28dc · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T21:59:20.972437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:59:20.972437Z digest=sha256:db109d3b28ec147488eb056c51b2d9e89a661bf6edaa45a0afd88f3eaac8effd

Observation d218c082-bf65-4735-9fcf-49a5be33ded4 · outbound

This paper cites an unresolved cited work.

Towards Time Series Generation Conditioned on Unstructured Natural Language Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:59:22.747908Z

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=arxiv_source observed=2026-08-06T21:59:21.099101Z digest=sha256:4d97e9929c697a9f8a663bda161e11b74d051a0882f4dbf20dead6316f90d500

Observation 7c01ff6d-43a2-4376-832c-f46677e4aa72 · outbound

This paper cites Understanding Why Large Language Models Can Be Ineffective in Time Series Analysis: The Impact of Modality Alignment.

Towards Time Series Generation Conditioned on Unstructured Natural Language Understanding Why Large Language Models Can Be Ineffective in Time Series Analysis: The Impact of Modality Alignment

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T21:59:21.189027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:59:21.189027Z digest=sha256:515c6907dd27ab07b9f0f529d8537629e57112e0260f80e0e2cfb0dca31618c8

Pith citing papers

No inbound Pith citation observations are available.