Paper Citation Record · LEDGER

Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences

As of 12 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2501.02735.

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

pith.paper-citation-record.v1
2501.02735 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:12:06.569508Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

46 of 46 outbound references displayed

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External citation measurements

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Outbound references

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences , " * write output.state after.block = add.period write newline

Reference 1

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences write newline

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Reference 3

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences Leveraging redundancy in attention with Reuse Transformers

Reference 4

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Observation 2c3b6955-57d1-4ec3-9591-dbde4e231288 · outbound

This paper cites R.; Chen, M.; Rodrigues, M.

Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences R.; Chen, M.; Rodrigues, M

Reference 5

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences O.; Yoder, N

Reference 6

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Reference 7

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This paper cites an unresolved cited work.

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Reference 8

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This paper cites Analyzing Redundancy in Pretrained Transformer Models.

Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences Analyzing Redundancy in Pretrained Transformer Models

Reference 11

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Reference 12

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Reference 13

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Observation c2f98fdf-1207-46bf-8391-a9b09efbb617 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 14

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Reference 15

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This paper cites Adam: A Method for Stochastic Optimization.

Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences Adam: A Method for Stochastic Optimization

Reference 16

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences Unresolved cited work

Reference 17

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Observation 3e52f15b-e240-4c42-9bcb-011848fe8f98 · outbound

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Reference 18

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences Unresolved cited work

Reference 19

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Observation cfc053a2-c16d-435b-af57-60893b94dce1 · outbound

This paper cites Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping.

Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping

Reference 20

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters

Reference 21

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Reference 22

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences X.; and Dustdar, S

Reference 23

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Reference 24

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Reference 25

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Reference 26

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Reference 27

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Observation 439c6d0f-cd71-48bb-9350-ffc75dd0e999 · outbound

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences H.; Sinthong, P.; and Kalagnanam, J

Reference 28

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time series

Reference 30

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences Certain Relations between Mutual Information and Fidelity of Statistical Estimation

Reference 32

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Reference 33

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Reference 34

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences N.; Kaiser, .; and Polosukhin, I

Reference 35

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences Y.; and ZHOU, J

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This paper cites Deep Time Series Models: A Comprehensive Survey and Benchmark.

Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences Deep Time Series Models: A Comprehensive Survey and Benchmark

Reference 37

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Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences Unresolved cited work

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Pith citing papers

No inbound Pith citation observations are available.