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Paper Citation Record · LEDGER

TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2405.14616.

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

pith.paper-citation-record.v1
2405.14616 v1

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 2026-08-04T06:34:03.388597+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T06:57:07.191355Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:30:07.267907Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation fae110e6-c1f1-467c-9a74-33618c3d5b6e · inbound

Time Series Forecasting Through the Lens of Dynamics cites this paper.

Time Series Forecasting Through the Lens of Dynamics TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-19T03:32:01.236519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-19T03:31:48.513830Z digest=sha256:49e0ecf3fc707719c5b099c4279a89e2087433654b44dca234e752c69245cf8d

Observation b9ba5df5-2d08-4291-8cb9-5f34de1641a3 · inbound

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

Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-18T13:21:23.786710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-18T13:21:02.738561Z digest=sha256:15beffcb492551a33299a856600461c72ddb4438f7c939eebde26adaae687935

Observation 8b9c5139-96ac-4857-b6c6-b9783869912d · inbound

DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting cites this paper.

DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-03T06:57:07.191355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:57:07.191355Z digest=sha256:2247b34ef65224d45c84b48ffefeb11a35a11180f10c5b92cc04cadf3b91ec1e

Observation ab6b78ef-2811-476e-a665-1fe48ecf2eb8 · inbound

CollideNet: Hierarchical Multi-scale Video Representation Learning with Disentanglement for Time-To-Collision Forecasting cites this paper.

CollideNet: Hierarchical Multi-scale Video Representation Learning with Disentanglement for Time-To-Collision Forecasting TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 55

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T08:53:04.952538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T08:33:49.539335Z digest=sha256:c3de2938cdeb2d4539367c8bb223a5612f54d11d6583b587673fcdbe422a4ff5

Observation 686af168-1f56-44fa-830b-ccae5b152458 · inbound

CombinationTS: A Modular Framework for Understanding Time-Series Forecasting Models cites this paper.

CombinationTS: A Modular Framework for Understanding Time-Series Forecasting Models TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:41:17.166361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-09T15:21:38.405970Z digest=sha256:1969d5ccd755b463a58689eb8c6f2a68bfffa17ab40aca35d65ec412cc51f808

Observation 9038647e-7753-4bbe-92e1-1e9e7a98ab8e · inbound

PRISM-CTG: A Foundation Model for Cardiotocography Analysis with Multi-View SSL cites this paper.

PRISM-CTG: A Foundation Model for Cardiotocography Analysis with Multi-View SSL TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:01:08.634050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T17:20:00.793919Z digest=sha256:8eaab73121a72d4e70836ae2cc5734339d934d11c2ae8643ad14a59e2ac07777

Observation e0f50dc0-23bc-4e12-a7f0-c30d82e34c21 · inbound

Perceive, Route and Modulate: Dynamic Pattern Recalibration for Time Series Forecasting cites this paper.

Perceive, Route and Modulate: Dynamic Pattern Recalibration for Time Series Forecasting TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:01:16.667360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-08T12:59:50.701441Z digest=sha256:f48ed30ab3366057bad1d550073ff12d162ab42357ede97b35d3a648921a3cfb

Observation a4010411-a66b-4c20-b7e8-e23b3bca8601 · inbound

What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies cites this paper.

What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 79

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:31:26.989794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-12T02:36:18.686443Z digest=sha256:4011200e7024ec527fd0880e3cf5a12a363945869cfe5e3ecff0b5e2e5c57b01

Observation 51b0225c-4b66-40d7-94a3-3c082bbb66dc · inbound

Reviving Error Correction in Modern Deep Time-Series Forecasting cites this paper.

Reviving Error Correction in Modern Deep Time-Series Forecasting TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:29:39.707931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-21T05:25:34.356205Z digest=sha256:78eee1a01b807e693a692faab9bb656b6eabff28f4817273603eebd2a63e1d09

Observation b1d2b88a-d476-4b72-b27d-9297db27615f · 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 TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-22T08:31:16.784996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T08:30:12.447896Z digest=sha256:828be1ab9a005d4244ea63ecb6a2e95420e09c1d1af5835d14f1a3ad16eb9fe6

Observation d2dffd1a-bfa2-4301-8421-b1417ca22624 · inbound

Stationarity-Aware Retrieval-Augmented Time Series Forecasting cites this paper.

Stationarity-Aware Retrieval-Augmented Time Series Forecasting TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:06:26.502718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T11:17:45.288201Z digest=sha256:0a603295338935d709281ddd73ce002f250bc9db1fb6dc7ffd921ad9ae50afad

Observation 40ed69fb-9f84-464c-9caf-49984a34d127 · inbound

CausalMoE: A Billion-Scale Multimodal Foundation Model for Granger Causal Discovery with Pattern-Routed Heterogeneous Experts cites this paper.

CausalMoE: A Billion-Scale Multimodal Foundation Model for Granger Causal Discovery with Pattern-Routed Heterogeneous Experts TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-07-03T13:38:19.502443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Observation 4f304f53-7d78-4637-988a-4bda73dc39a1 · inbound

MetaPS: Adaptive Programmatic Strategy Selection for Market Agents cites this paper.

MetaPS: Adaptive Programmatic Strategy Selection for Market Agents TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 146

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:39:42.685074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-26T11:06:28.690956Z digest=sha256:87743950e9c65972c4b440ae8a036a57364c196303b80bd70d94f31bc56cb589

Observation 318aa908-8ce7-4761-b4a2-60d8f67b0af6 · inbound

$\text{DT}^2$: Decision-Targeted Digital Twins cites this paper.

$\text{DT}^2$: Decision-Targeted Digital Twins TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-04T20:30:07.269895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-25T20:08:13.039445Z digest=sha256:da29f8afdb0806def4222c04ad29337ac1474d4589231fddcccda17f8f5af0f5

Observation 5472cf81-d477-4c8d-a296-442fbad687ce · inbound

How Good Can Linear Models Be for Time-Series Forecasting? cites this paper.

How Good Can Linear Models Be for Time-Series Forecasting? TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:19:51.307266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Observation e3f8dd8f-c351-4cf8-a28c-ef86c4707538 · inbound

How Good Can Linear Models Be for Time-Series Forecasting? cites this paper.

How Good Can Linear Models Be for Time-Series Forecasting? TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-06-30T09:34:34.412885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-30T09:33:16.718840Z digest=sha256:ba8d8fd5ce60fe6ae584372553f943d936774dc838fe58edc7eebb290637a30e

Observation 9513409e-cf77-40d2-9236-ae22243d8a0f · inbound

QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting cites this paper.

QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 1191

Resolution
unresolved
no resolver link, observed 2026-08-02T09:05:36.574036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T09:05:36.574036Z digest=sha256:0c9b91813fc572755573e857069497c9ce12d9593f858cae0a6746a87de386e1

Observation b0c6f19b-94e1-4de3-8f60-0617f969fdf7 · inbound

Multi-Scale Convolution with Optimal Transport Attention Effect on Multivariate Time Series cites this paper.

Multi-Scale Convolution with Optimal Transport Attention Effect on Multivariate Time Series TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 24

Resolution
unresolved
no resolver link, observed 2026-07-14T09:36:39.436015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T09:36:39.436015Z digest=sha256:bf39a4f6df09cf02a917ac28e573cf310d9700c2a93c4386c4d55a3b004410ac

Observation f7f79445-b9b0-4d66-9069-e64221060bdf · inbound

PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling cites this paper.

PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-01T10:29:15.474242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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