Pith. sign in

Paper Citation Record · LEDGER

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

As of 8 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 2026-08-08T06:32:00.761636+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=sha256:5b955f3ecd41b2f61637914cfacd05b38897d6d836e793fe8aef0a087d69b196

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:04:59.540623Z digest=sha256:23e845c7bcbeac58819f6a1221bd6466bbc1e39c54d0ed8e676e4bed05b130ce

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:ce367e7229ff39c24348d6ea84451df7d586f81e8f2b42294194d65259899f63

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=sha256:52e3bf5d6f4997a26c888f64e4769b60757a658dc65f591a761918d3cc163de0

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:04:59.384129Z digest=sha256:748239dd0a97dd02c15a424b844ae1cb1ac19d5f1a037dbc0baf870b22b4be1d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:04:59.766375Z digest=sha256:4d74a8fa1e117ba84c0b15e3234bc2ae31481c4259ba945a13390fe7c2008c46

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:04:59.682593Z digest=sha256:8806837adcd525f8f8e0a64d136dfb6b4d34b70c29f1da3ea66cb728aaa70613

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=sha256:12f44fe30136fe2b0b19551f6782556d59d1c9dbd840a92e60d152969fa9be30

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:e352cf0d70b69b162e94fe89bbaff5f346d12d5b2340168030fe552f2528e3ea

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=sha256:91a82230124625cc5a61d2beb8f7458c3cb874d72728a9c7b941a15de12f7f9f

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=sha256:47bd0f5ec9c7a07c85a8b94fc6378a6d9e3dd35c49aae23e9a81d36a89b69427

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=sha256:58e4eb00b6e177e129d28018eecf25f2a2bca164b31dda87e092b9be9057c1f4

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=sha256:78458e50362a1055c8da725f1ae78957f7fa3834b6f36065746aef22c403d748

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=sha256:009d37c3a53a1d2ae777ce06734431bc3ee0d4bc5c7bbba91ce5270a385ef9a8