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Paper Citation Record · LEDGER

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting

As of 7 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:2505.22768.

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

pith.paper-citation-record.v1
2505.22768 v3

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:04:59.766375Z

measured 14 of 14 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T06:16:38.822507Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 187fd7a7-ee52-4648-96fd-ac048a0084f8 · outbound

This paper cites Foundational Models Defining a New Era in Vision: A Survey and Outlook.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting Foundational Models Defining a New Era in Vision: A Survey and Outlook

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T13:04:58.391697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:04:58.391697Z digest=sha256:67b79b5810d277f1f1365cf764f1922a039388fc0f20ce8dc5c366a5d0e3d048

Observation 7cba5ac0-73f8-44d1-8093-4e909729106e · outbound

This paper cites an unresolved cited work.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:05:01.628850Z

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=2026-08-07T13:04:59.540623Z digest=sha256:aac9d3c4f6cefd8c6a04115909c21db19cc00892cb5efc44ac02c23bf6c46ef5

Observation c73687fe-d3f2-49db-8d70-4573e89fb97a · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T13:04:59.014129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:04:59.014129Z digest=sha256:dffe5afe94107c39546f43f86612903761b2e5cbc75adf8d6af9ab35f46d65b3

Observation bf72b687-7371-407a-a690-d4a2143e33ec · outbound

This paper cites A Survey of Large Language Models.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting A Survey of Large Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T13:04:59.293692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:04:59.293692Z digest=sha256:fe3767780ba8925a49be624f80a6febeee553b777b8f64b6348b7c4ffb6ce18a

Observation 3736cb47-c7ef-43c8-8909-48a0463f0be3 · outbound

This paper cites 5 Submission and Formatting Instructions for ICML 2025 A.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting 5 Submission and Formatting Instructions for ICML 2025 A

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:05:01.782365Z

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=2026-08-07T13:04:59.384129Z digest=sha256:010d076fb170773681abd90abc74e5c31e5ae3277f380b0370aea0998e5755de

Observation 4b6fa8db-3c51-4c1f-a6be-14ec4d3f20d5 · outbound

This paper cites All experiments are conducted on a single NVIDIA A100 GPU with 42 GB of memory.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting All experiments are conducted on a single NVIDIA A100 GPU with 42 GB of memory

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:05:01.028149Z

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=2026-08-07T13:04:59.766375Z digest=sha256:721cdb3f7d30b86f2214963ce6ac215fb085485c95799f54f0f45b8e28c0d104

Observation 280c4b1a-9460-4517-a1ce-4e4f730358cf · outbound

This paper cites The graph embedding dimension G is consistently set equal to the model channel size C.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting The graph embedding dimension G is consistently set equal to the model channel size C

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:05:01.417317Z

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=2026-08-07T13:04:59.682593Z digest=sha256:a9256e641c8eb4d35806572c07ee5d2d83960fc412fed472ac715b8f63df483f

Observation 640e8035-07b6-4752-8231-fd85c23229d2 · outbound

This paper cites Tsmixer: An all-mlp architecture for time se- ries forecasting.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting Tsmixer: An all-mlp architecture for time se- ries forecasting

Reference 1946

Resolution
unresolved
no resolver link, observed 2026-08-07T13:04:58.567068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:04:58.567068Z digest=sha256:c4f9b91315486a028ba68b7c03d58948bef79e82898472b92513b8fe5eee3619

Observation 261a64f0-aee9-4829-af4b-196072a01f11 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting Fast Graph Representation Learning with PyTorch Geometric

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T13:04:58.682013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:04:58.682013Z digest=sha256:c5607512c90aa61722818943b60a3432f8e4b8b48ee72f375de82678aad76666

Observation 30dffe4a-aa86-4e18-a8b5-712290ff4d26 · outbound

This paper cites TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-07T13:04:59.162184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:04:59.162184Z digest=sha256:fead0d7d86679bad445fb901c915a2e1c87be2bb64b51b5a0d2be55a89e1faae

Observation 2d409401-9dbc-4ef9-87b5-f4f52c7d0ab4 · outbound

This paper cites Diffusion Improves Graph Learning.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting Diffusion Improves Graph Learning

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-07T13:04:58.792361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:04:58.792361Z digest=sha256:08b42916c1ed95052c97ee468a29c5fbd301d0b4c91842e0f31755d0fc930675

Observation 1dc2b27a-1d0a-49c7-bf13-a787ab21be29 · outbound

This paper cites O., Kurban, H., Aljihmani, L., Qaraqe, K., Petrovski, G., and Dalkilic, M.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting O., Kurban, H., Aljihmani, L., Qaraqe, K., Petrovski, G., and Dalkilic, M

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T13:04:58.502250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:04:58.502250Z digest=sha256:93982f5e3ed8abd131235c3bdafc37c51a5c8a0683772b6c97201f2e8c5826ab

Observation 8e460b09-7d85-49d3-a6b8-d779d44aa2b3 · outbound

This paper cites TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables.

Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T13:04:58.905036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:04:58.905036Z digest=sha256:ba5dafd01d7bc1dcfd67629705c1bfecc93b8e234f0b80dd735e2a1a7fc27611

Pith citing papers

Observation 751ef215-0ec7-45f8-8b51-bf20cac37554 · inbound

The Spectrum Is Not Enough: When Context Helps Time-Series Forecasting cites this paper.

The Spectrum Is Not Enough: When Context Helps Time-Series Forecasting Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-02T06:16:38.822507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T06:16:38.822507Z digest=sha256:c4b909a554276e074c0c076a882fcc36d65d480617d0250506f926fb721979e4