Paper Citation Record · LEDGER

Self-Gating Attention for Efficient Time Series Forecasting

As of 4 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2607.02344.

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

pith.paper-citation-record.v1
2607.02344 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-03T16:33:19.870207Z

measured 40 of 40 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 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

40 of 40 outbound references displayed

verified exact2
verified fuzzy38
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0354e726-ee75-4641-9392-ec705eb9959a · outbound

This paper cites The capacity and robustness trade-off: Revisiting the channel independent strategy for multivariate time series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting The capacity and robustness trade-off: Revisiting the channel independent strategy for multivariate time series forecasting,

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-03T16:38:39.700358Z

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.

Observation f56d1872-fc4d-4592-b03b-78be91de96bc · outbound

This paper cites A survey on graph neural networks for time series: Forecasting, classification, imputation, and anomaly detec- tion,.

Self-Gating Attention for Efficient Time Series Forecasting A survey on graph neural networks for time series: Forecasting, classification, imputation, and anomaly detec- tion,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.522750Z

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.

Observation b3abde3d-941e-46bd-ba94-93a061b911d4 · outbound

This paper cites Spatio-temporal transformer network for weather forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting Spatio-temporal transformer network for weather forecasting,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.527204Z

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.

Observation db37f122-35f0-4c21-b997-9b52e2916952 · outbound

This paper cites Long short-term financial time series forecasting based on residual multiscale TCN sparse expert network and Informer,.

Self-Gating Attention for Efficient Time Series Forecasting Long short-term financial time series forecasting based on residual multiscale TCN sparse expert network and Informer,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.515836Z

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.

Observation 6e97ba7d-343b-4d8d-b569-6b7933079648 · outbound

This paper cites TimeMixer: Decomposable multiscale mixing for time series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting TimeMixer: Decomposable multiscale mixing for time series forecasting,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.470619Z

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.

Observation 279118a0-994d-4d8e-ab26-99b0c4da21ae · outbound

This paper cites A multi-task end-to-end multivariate long-sequence time series prediction model for load forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting A multi-task end-to-end multivariate long-sequence time series prediction model for load forecasting,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.531638Z

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.

Observation bf94c196-27d8-4f97-b397-8ce27859cedb · outbound

This paper cites Investigating pattern neurons in urban time series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting Investigating pattern neurons in urban time series forecasting,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.500842Z

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.

Observation ab6bfa24-45c4-4ee4-973f-ff549d904244 · outbound

This paper cites Informer: Beyond efficient trans- former for long sequence time-series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting Informer: Beyond efficient trans- former for long sequence time-series forecasting,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.541731Z

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.

Observation 85cf7b0d-7945-453e-b837-5428ba934b63 · outbound

This paper cites Simultaneous bearing fault recognition and remaining useful life prediction using joint-loss convo- lutional neural network,.

Self-Gating Attention for Efficient Time Series Forecasting Simultaneous bearing fault recognition and remaining useful life prediction using joint-loss convo- lutional neural network,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.513183Z

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.

Observation 6280fc86-23b1-4a20-bd58-26804771d4e1 · outbound

This paper cites Attention is all you need,.

Self-Gating Attention for Efficient Time Series Forecasting Attention is all you need,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.529371Z

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.

Observation 5937448b-f0cc-49c7-8f1c-f63a5914bf61 · outbound

This paper cites TimeXer: Empowering transformers for time series forecasting with exogenous variables,.

Self-Gating Attention for Efficient Time Series Forecasting TimeXer: Empowering transformers for time series forecasting with exogenous variables,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.551291Z

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.

Observation b601ddf2-2668-43b8-96c5-0391aa36dde9 · outbound

This paper cites an unresolved cited work.

Self-Gating Attention for Efficient Time Series Forecasting Unresolved cited work

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-03T16:38:39.697178Z

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.

Observation 3e2fde6a-3d38-4092-a3de-d298c53abddc · outbound

This paper cites iTransformer: Inverted transformers are effective for time series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting iTransformer: Inverted transformers are effective for time series forecasting,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.518648Z

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.

Observation 8d7df93e-c302-4c7c-b6b9-cf0f5647a0e9 · outbound

This paper cites Efficient attention: Attention with linear complexities,.

Self-Gating Attention for Efficient Time Series Forecasting Efficient attention: Attention with linear complexities,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.520549Z

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.

Observation 478509c1-0575-4ab7-bbed-748e25f4f425 · outbound

This paper cites Adversarial self-attention for language understanding,.

Self-Gating Attention for Efficient Time Series Forecasting Adversarial self-attention for language understanding,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.524750Z

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.

Observation 32fc0153-28f9-425b-b9cf-5e398d585645 · outbound

This paper cites Token statistics transformer: Linear-time attention via variational rate reduction,.

Self-Gating Attention for Efficient Time Series Forecasting Token statistics transformer: Linear-time attention via variational rate reduction,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.533714Z

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.

Observation 6b360859-177a-43fe-9df5-20d84e8e68b4 · outbound

This paper cites Long sequence multivariate time- series forecasting for industrial processes using SASGNN,.

Self-Gating Attention for Efficient Time Series Forecasting Long sequence multivariate time- series forecasting for industrial processes using SASGNN,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.546157Z

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.

Observation 6d08f641-f29d-40b1-8d3b-74d5da83ca3d · outbound

This paper cites MC-ANN: A mixture clustering-based attention neural network for time series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting MC-ANN: A mixture clustering-based attention neural network for time series forecasting,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.465609Z

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.

Observation f183cde0-45a4-4b23-80de-ab0a2f5837cd · outbound

This paper cites HDT: Hierarchical discrete transformer for multivariate time series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting HDT: Hierarchical discrete transformer for multivariate time series forecasting,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.536085Z

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.

Observation 6ae09b77-b05d-45c9-857f-6dbd44f88111 · outbound

This paper cites Short-term forecasting of heat demand of buildings for efficient and optimal energy management based on integrated machine learning models,.

Self-Gating Attention for Efficient Time Series Forecasting Short-term forecasting of heat demand of buildings for efficient and optimal energy management based on integrated machine learning models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.538346Z

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.

Observation 94bbfb37-9f35-489b-a894-bf7ddd82e60c · outbound

This paper cites Irregular multivariate time series fore- casting: A transformable patching graph neural networks approach,.

Self-Gating Attention for Efficient Time Series Forecasting Irregular multivariate time series fore- casting: A transformable patching graph neural networks approach,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.513680Z

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.

Observation bc74a497-d67e-45b0-bcba-e1e169a24477 · outbound

This paper cites UniMATS: A unified time series forecasting model with multi-dimensional attention structure for power systems,.

Self-Gating Attention for Efficient Time Series Forecasting UniMATS: A unified time series forecasting model with multi-dimensional attention structure for power systems,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.532571Z

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.

Observation 5862e6b4-0fa4-49c8-9149-1f6db9bae2dc · outbound

This paper cites Temporal re-attention LSTM for multivariate prediction in industrial heating process with large time delays,.

Self-Gating Attention for Efficient Time Series Forecasting Temporal re-attention LSTM for multivariate prediction in industrial heating process with large time delays,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.548888Z

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.

Observation a90eb0c7-d4ae-43ec-beaf-842cb7372ae8 · outbound

This paper cites A difference metric attention with position distance-based weighting for transformer in data sequence modeling of industrial processes,.

Self-Gating Attention for Efficient Time Series Forecasting A difference metric attention with position distance-based weighting for transformer in data sequence modeling of industrial processes,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.510150Z

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.

Observation 2b99f06f-8925-4a71-82c0-d17398070627 · outbound

This paper cites Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.486225Z

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.

Observation 287903e6-5f56-46d3-b02a-6e033b0ddb7e · outbound

This paper cites Crossformer: Transformer utilizing cross- dimension dependency for multivariate time series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting Crossformer: Transformer utilizing cross- dimension dependency for multivariate time series forecasting,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.481874Z

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.

Observation f109c1d8-cea6-4402-b85c-01e37def8021 · outbound

This paper cites CAST: An innovative framework for cross-dimensional attention structure in transformers,.

Self-Gating Attention for Efficient Time Series Forecasting CAST: An innovative framework for cross-dimensional attention structure in transformers,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.483773Z

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.

Observation 050450f2-8036-442c-b3a3-6d6e4d46b6be · outbound

This paper cites Probabilistic multienergy load forecasting based on hybrid attention-enabled transformer network and Gaussian process-aided residual learning,.

Self-Gating Attention for Efficient Time Series Forecasting Probabilistic multienergy load forecasting based on hybrid attention-enabled transformer network and Gaussian process-aided residual learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.496520Z

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.

Observation 4a25e8f1-da35-4278-b030-c78ba306ad2c · outbound

This paper cites Multi-criteria token fusion with one- step-ahead attention for efficient vision transformers,.

Self-Gating Attention for Efficient Time Series Forecasting Multi-criteria token fusion with one- step-ahead attention for efficient vision transformers,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.526158Z

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.

Observation f6850eab-7de2-4b09-8a50-a5e45a208923 · outbound

This paper cites Hierarchical self-attention network for industrial data series modeling with different sampling rates between the input and output sequences,.

Self-Gating Attention for Efficient Time Series Forecasting Hierarchical self-attention network for industrial data series modeling with different sampling rates between the input and output sequences,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.493721Z

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.

Observation e65bbea4-938f-4238-9e30-5b567968f8ce · outbound

This paper cites Reversible instance normalization for ac- curate time-series forecasting against distribution shift,.

Self-Gating Attention for Efficient Time Series Forecasting Reversible instance normalization for ac- curate time-series forecasting against distribution shift,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.519095Z

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.

Observation 01124c03-970e-4664-8915-00ad88408347 · outbound

This paper cites Non-stationary transformers: Exploring the stationarity in time series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting Non-stationary transformers: Exploring the stationarity in time series forecasting,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.510264Z

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.

Observation ccba4fe4-0b48-4096-854c-07312082287a · outbound

This paper cites Occlusion-aware transformer with second-order attention for person re-identification,.

Self-Gating Attention for Efficient Time Series Forecasting Occlusion-aware transformer with second-order attention for person re-identification,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.507942Z

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.

Observation 32e80df6-90af-4726-93e1-60a9ab8e8e96 · outbound

This paper cites TAMT: Temporal-aware model tuning for cross-domain few-shot action recognition,.

Self-Gating Attention for Efficient Time Series Forecasting TAMT: Temporal-aware model tuning for cross-domain few-shot action recognition,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.475731Z

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.

Observation c26d48f4-7a6b-4c55-ba15-79ae6d3fa915 · outbound

This paper cites Are self-attentions effective for time series forecasting?.

Self-Gating Attention for Efficient Time Series Forecasting Are self-attentions effective for time series forecasting?

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.479850Z

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.

Observation 0d2dcf35-516e-45bb-afd9-52d7ca0cb4ea · outbound

This paper cites CARD: Channel aligned robust blend transformer for time series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting CARD: Channel aligned robust blend transformer for time series forecasting,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.488993Z

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.

Observation e44eeb95-5928-440c-90c0-50217640b49b · outbound

This paper cites Fedformer: Frequency enhanced decom- posed transformer for long-term series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting Fedformer: Frequency enhanced decom- posed transformer for long-term series forecasting,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.505655Z

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.

Observation fa847ecc-1d40-4670-b296-f8c663b57af7 · outbound

This paper cites Are language models actually useful for time series forecasting?.

Self-Gating Attention for Efficient Time Series Forecasting Are language models actually useful for time series forecasting?

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.490934Z

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.

Observation 020536d9-b556-415e-92f3-0b89732c286d · outbound

This paper cites A multiscale model for multivariate time series forecasting,.

Self-Gating Attention for Efficient Time Series Forecasting A multiscale model for multivariate time series forecasting,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.523481Z

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.

Observation 9c6a4d80-63d7-4a96-a3b3-51860b3ad593 · outbound

This paper cites A time series is worth 64 words: Long-term forecasting with transformers,.

Self-Gating Attention for Efficient Time Series Forecasting A time series is worth 64 words: Long-term forecasting with transformers,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T05:30:43.497245Z

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.

Pith citing papers

No inbound Pith citation observations are available.