Paper Citation Record · LEDGER

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations

As of 18 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2505.00307.

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

pith.paper-citation-record.v1
2505.00307 v3

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:51:20.403544Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

30 of 30 outbound references displayed

verified exact0
verified fuzzy15
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5ada1cd5-fdf1-45b3-9e16-0e27d83cedaa · outbound

This paper cites A., Martens, P.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations A., Martens, P

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.918424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 33f6cec5-7be9-4e80-ae0e-4cdb0708ab98 · outbound

This paper cites W., Gerlach, R., Lin, E.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations W., Gerlach, R., Lin, E

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.902436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a05d9fee-c3a3-4c45-9036-a3eee6d6e51b · outbound

This paper cites A decoder-only foundation model for time-series forecasting.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations A decoder-only foundation model for time-series forecasting

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.248731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62d60dc3-19fe-493e-9703-11b0bacd848c · outbound

This paper cites MOMENT: A Family of Open Time-series Foundation Models.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations MOMENT: A Family of Open Time-series Foundation Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.254039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49c17e08-bd84-4daa-9d28-27dc0d0684ab · outbound

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

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations The capacity and robustness trade-off: Revisiting the channel independent strategy for multivariate time series forecasting

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.874718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cc895793-fe3d-4acd-845b-c5a885e1dd59 · outbound

This paper cites Y., Shi, X., Chen, P.-Y., Liang, Y., Li, Y.-F., Pan, S., and Wen, Q.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Y., Shi, X., Chen, P.-Y., Liang, Y., Li, Y.-F., Pan, S., and Wen, Q

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.854961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e020246c-9a12-479b-b248-1bbcad3e2954 · outbound

This paper cites K., Dasgupta, N., Natarajan, S., Pickett, L.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations K., Dasgupta, N., Natarajan, S., Pickett, L

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.836989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 50e18bc1-c592-46b1-8df5-48f2f3434ab3 · outbound

This paper cites Reversible instance normalization for accurate time-series forecasting against distribution shift.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Reversible instance normalization for accurate time-series forecasting against distribution shift

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.278498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2451651b-2f47-4b5f-9427-0ecf81bcf9f1 · outbound

This paper cites Reformer: The efficient transformer.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Reformer: The efficient transformer

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.283993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ded740a0-d2d2-4df5-9b13-9fade23c0fdc · outbound

This paper cites Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.291202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19aeaeed-9146-4813-9be1-a478dce43a76 · outbound

This paper cites Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.297246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fcea863-f450-4939-ba41-054f9713a02e · outbound

This paper cites SCIN et: Time series modeling and forecasting with sample convolution and interaction.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations SCIN et: Time series modeling and forecasting with sample convolution and interaction

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.789628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b0056987-232e-4bdb-95e8-1d1255f9c61e · outbound

This paper cites X., and Dustdar, S.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations X., and Dustdar, S

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.763364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 41ecd46a-b204-48ad-a6e0-e9b845dcacf7 · outbound

This paper cites Unitime: A language-empowered unified model for cross-domain time series forecasting.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Unitime: A language-empowered unified model for cross-domain time series forecasting

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.747776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c5f483d9-ea31-4534-ac2f-acf1d7662aed · outbound

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

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Non-stationary transformers: Exploring the stationarity in time series forecasting

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.728710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 51d060c6-6b3a-4427-8719-d2c9e4e7ce40 · outbound

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

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations itransformer: Inverted transformers are effective for time series forecasting

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.324721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc1ca050-c7d0-4a92-9192-bfcd344e0030 · outbound

This paper cites Timer: Generative pre-trained transformers are large time series models.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Timer: Generative pre-trained transformers are large time series models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.702828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6cde489b-8446-4af7-9fd7-d8f521ece1e6 · outbound

This paper cites Traffic flow prediction with big data: A deep learning approach.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Traffic flow prediction with big data: A deep learning approach

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.677383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2387d3c9-1da9-4090-8aeb-25c2f0aeb982 · outbound

This paper cites H., Sinthong, P., and Kalagnanam, J.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations H., Sinthong, P., and Kalagnanam, J

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.342835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cd90671-ba8b-4ffd-9abd-0fa96df002f4 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Pytorch: An imperative style, high-performance deep learning library

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.347709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 857be7ac-9651-4bba-a803-1781871f2dfe · outbound

This paper cites N., Kaiser, L.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations N., Kaiser, L

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.632101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b483032b-0c2f-459b-9d42-dd6fb6f8e824 · outbound

This paper cites Transformers in Time Series: A Survey.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Transformers in Time Series: A Survey

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.355739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90e32b80-7f53-48e1-aabb-274e60ea8f06 · outbound

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

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.360182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8628f3e-d770-4c5b-9e7e-7c82aaedce87 · outbound

This paper cites Flowformer: Linearizing Transformers with Conservation Flows.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Flowformer: Linearizing Transformers with Conservation Flows

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.365128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 902da20d-81cc-42bb-aa23-ce651f6155e1 · outbound

This paper cites Timesnet: Temporal 2d-variation modeling for general time series analysis.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Timesnet: Temporal 2d-variation modeling for general time series analysis

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.371788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d589aad-0079-4265-a2e9-cda926d6091e · outbound

This paper cites Are transformers effective for time series forecasting? In Proceedings of the AAAI conference on artificial intelligence, 2023.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Are transformers effective for time series forecasting? In Proceedings of the AAAI conference on artificial intelligence, 2023

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.590616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c0ce917c-6214-4463-844f-15fd521adb4f · outbound

This paper cites and Yan, J.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations and Yan, J

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.384480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de7c3566-6abb-490c-a223-b20fc05d0340 · outbound

This paper cites FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T04:51:20.393696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef59a386-21a3-4c7d-a52d-eb503c48f7f9 · outbound

This paper cites One fits all: Power general time series analysis by pretrained LM.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations One fits all: Power general time series analysis by pretrained LM

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.567859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e0169ce9-3216-423f-b1aa-57065e893dd7 · outbound

This paper cites Energy forecasting with robust, flexible, and explainable machine learning algorithms.

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations Energy forecasting with robust, flexible, and explainable machine learning algorithms

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:51:20.551828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.