Pith. sign in

Paper Citation Record · LEDGER

Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2402.05956.

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

pith.paper-citation-record.v1
2402.05956 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 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 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T20:06:12.547071Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

36
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0323324f-c509-45bd-945b-1202e2e309e5 · inbound

AttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset cites this paper.

AttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T20:06:12.547071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:06:12.547071Z digest=sha256:64197b5dd1f998a3b2db1b7afde01a74c8c16c3c797208987d0e3808d25fe77a

Observation fc58d632-4880-42fe-840a-0e500829f085 · inbound

Logo-LLM: Local and Global Modeling with Large Language Models for Time Series Forecasting cites this paper.

Logo-LLM: Local and Global Modeling with Large Language Models for Time Series Forecasting Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-22T15:21:45.122779Z

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=2026-05-22T15:17:13.583856Z digest=sha256:70ecb2158b72ae2aa287033ea94ec174641025e225d00f6f98fe5a9e972cd59e

Observation 6e445a28-20c2-4320-a718-dc55d88d5c63 · inbound

MSDformer: Multi-scale Discrete Transformer For Time Series Generation cites this paper.

MSDformer: Multi-scale Discrete Transformer For Time Series Generation Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 59

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T13:44:52.875917Z

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=2026-05-22T13:44:08.891339Z digest=sha256:91a64a978cd25c1f08ce2ffa7b04c448ed23cd7b28d0c2bdd68aaa22e4a2e7cb

Observation 2be0397c-8d7e-4ea8-9499-146358f45988 · inbound

PIPE: Physics-Informed Position Encoding for Alignment of Satellite Images and Time Series cites this paper.

PIPE: Physics-Informed Position Encoding for Alignment of Satellite Images and Time Series Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T13:54:29.336070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:54:29.336070Z digest=sha256:cfdb2f4a9b58d36129a2eee16faad08987a58db21adb030efead1743b83b57c4

Observation 99bba139-6013-4e28-836f-292d134b2c3b · inbound

DisMS-TS: Eliminating Redundant Multi-Scale Features for Time Series Classification cites this paper.

DisMS-TS: Eliminating Redundant Multi-Scale Features for Time Series Classification Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T19:52:19.031613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:52:19.031613Z digest=sha256:8460dc72d635b5878cb8c7d1a41c6e3e05a92cde207f342b43236503175af7d1

Observation 2567d205-9f03-4178-89ad-52be162d99c0 · 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 Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T18:01:26.634168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:01:26.634168Z digest=sha256:6a380353c13af81f3e3e60028293e1a0121b9ad6735652cb1c390b86fc43166e

Observation a9b10124-3a0c-46e2-968a-74e06bc6fc36 · inbound

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting cites this paper.

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T16:35:25.298249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:35:25.298249Z digest=sha256:e547745fdbfa1c52d3f70a97eccc1e91ded733a2e6e2d2a7014ed69094111d8e

Observation d4d5efbe-c686-4464-8baf-bccc8270dfbf · inbound

MSGM: A Multi-Scale Spatiotemporal Graph Mamba for EEG Emotion Recognition cites this paper.

MSGM: A Multi-Scale Spatiotemporal Graph Mamba for EEG Emotion Recognition Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T15:26:55.571356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:26:55.571356Z digest=sha256:7dba495846fab38ae969685660ef29f1427819a945252bf23f2516aac6c15588

Observation b093dd96-8f8d-4438-a337-23a3b483c57d · inbound

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

Foundation Models for Demand Forecasting via Dual-Strategy Ensembling Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.443027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:09:39.443027Z digest=sha256:53b73872e2b7fb44f54f9f4ec3e9b012096f27324daf1be9fec208137f5a391c

Observation 803ebed0-ff83-4501-b74d-5aa22ad763e3 · inbound

Towards Measuring and Modeling Geometric Structures in Time Series Forecasting via Image Modality cites this paper.

Towards Measuring and Modeling Geometric Structures in Time Series Forecasting via Image Modality Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T10:58:02.346598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:58:02.346598Z digest=sha256:04da50faac02f82e1e8eb3bbcb6ab30950d602da7634e1ddfda9bc1565a2da50

Observation bcc1159f-83a5-44bd-ad81-2d1203fd80c9 · inbound

Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models cites this paper.

Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T13:21:23.771218Z

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=2026-05-18T13:21:02.738561Z digest=sha256:6bd3e379e49c6bb4e41b985564c91cd1e88ab5e1aebad877136c4379878a21de

Observation bcc6b566-d37a-4124-9d38-a3f4cd86b34c · inbound

SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting cites this paper.

SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-02T22:40:03.195176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T22:40:03.195176Z digest=sha256:f135a07e4de92458a4130fe0f7f90010bc0a68021af2eea8878313b54459aecf

Observation 6bf1cb38-b163-4d8a-b196-b8e6d5980f6c · inbound

On What We Can Learn from Low-Resolution Data cites this paper.

On What We Can Learn from Low-Resolution Data Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:32:19.030780Z

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=arxiv_source observed=2026-05-13T05:28:50.993737Z digest=sha256:e9497745b5aa9208639dacdb37db6b9925cd164ba57da703a5a7e2028f80bd2e

Observation 1a094079-06ba-438a-a394-3ba52dc6c3cb · inbound

SeesawNet: Towards Non-stationary Time Series Forecasting with Balanced Modeling of Common and Specific Dependencies cites this paper.

SeesawNet: Towards Non-stationary Time Series Forecasting with Balanced Modeling of Common and Specific Dependencies Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T01:58:29.227260Z

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=2026-05-15T01:54:32.493922Z digest=sha256:50b9a700088e014b663aa0506fc56a67337ad3bc6876412fedbd1afc3861bed7

Observation 00607754-0035-4476-b24a-2cc9f9b17f77 · inbound

CASE-NET: Deep Spatio-Temporal Representation Learning via Causal Attention and Channel Recalibration for Multivariate Time Series Classification cites this paper.

CASE-NET: Deep Spatio-Temporal Representation Learning via Causal Attention and Channel Recalibration for Multivariate Time Series Classification Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T08:31:16.758150Z

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=2026-05-22T08:30:12.447896Z digest=sha256:88be5917fd822f2ea39a7749bf812fa3b03264d43dc9f6e842add70ea4c0f53b

Observation 87de82d4-f753-40cd-8c11-19363f3df6c2 · inbound

PMDformer: Patch-Mean Decoupling Information Transformer for Long-term Forecasting cites this paper.

PMDformer: Patch-Mean Decoupling Information Transformer for Long-term Forecasting Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T13:19:50.456226Z

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=2026-06-26T05:22:10.800685Z digest=sha256:6c1766a8eae548a1fe8d851f4357b386290e89d84c5dfdc454b423f4a34018ac

Observation 0a5443b7-ad4e-437f-8e59-f41d45210d59 · inbound

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition cites this paper.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T16:47:08.989098Z

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=2026-07-02T16:45:46.207051Z digest=sha256:d6ed89b4ab97dbdfa8c4029d5185d6f164d09fad3e4a4d62f070afe871c89aa8

Observation 893632d9-d664-4795-a4dd-ba29db1788c0 · inbound

Regime-Aware Physics-Guided Early Warning of Lithium-Ion Battery Thermal Runaway Using Thermo-Mechanical Signals cites this paper.

Regime-Aware Physics-Guided Early Warning of Lithium-Ion Battery Thermal Runaway Using Thermo-Mechanical Signals Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-01T14:10:00.307077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:10:00.307077Z digest=sha256:925664bce2731b84710ffe76eef228b9fddf28a0177c6dbc5880c99cd5bec6c6

Observation 3ab483af-6b9b-48b0-a44f-de5e45deda73 · inbound

Differencing the Diffusion Trajectory toward Uncertain Components for Time Series Forecasting cites this paper.

Differencing the Diffusion Trajectory toward Uncertain Components for Time Series Forecasting Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-02T11:33:56.982834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:33:56.982834Z digest=sha256:2c406db77252aad116309ed8b840e235da9253910f43fc04aa2215ad6112656a