Paper Citation Record · LEDGER

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting

As of 10 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.08234.

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

pith.paper-citation-record.v1
2607.08234 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T11:50:26.030339Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

18 of 18 outbound references displayed

verified exact7
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch11

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c3c00975-435b-4613-9d6b-67548ea80f30 · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-10T10:57:05.497436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1bebcde8-cf4c-4d51-b916-7b0c3e4f0f5e · outbound

This paper cites Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:57:05.485274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fb536bad-0366-4a71-8c77-af0ccd4e629b · outbound

This paper cites IEEE Access 12, 191162–191198.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting IEEE Access 12, 191162–191198

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-10T10:57:05.381903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 27658bcc-1b01-4d68-959c-f642da140ec8 · outbound

This paper cites SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-07-10T10:57:05.378167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7a8b6659-e253-48f7-9243-717bb97c81d5 · outbound

This paper cites Long short -term memory.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting Long short -term memory

Reference 5

Resolution: metadata mismatch; doi, observed 2026-07-10T10:57:05.369848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4e352b29-7294-4757-b9ba-f2cfb7ac9fea · outbound

This paper cites Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:57:05.510725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5342934f-0607-48cb-a124-f49439afa358 · outbound

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

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:57:05.476406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4419b2a2-5008-427a-987f-dd2e6b745fc1 · outbound

This paper cites Philo- sophical Transactions of the Royal Society A379(2194), 20200209 (2021).https: //doi.org/10.1098/rsta.2020.0209.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting Philo- sophical Transactions of the Royal Society A379(2194), 20200209 (2021).https: //doi.org/10.1098/rsta.2020.0209

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-10T10:57:05.374402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 541c96a2-fef8-428f-a874-b8d9cd705578 · outbound

This paper cites CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-07-10T10:57:05.473528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dae4bfae-aad7-4a88-a9e3-769da431cae7 · outbound

This paper cites SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction

Reference 10

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:57:05.482509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d3e4aa96-1857-43e1-afcf-4cd271e639d9 · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 11

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:57:05.494444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 905a2ef9-fe19-42c3-aec7-49882c874f61 · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 12

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:57:05.488576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6f4a2072-a8d1-4ab4-b301-058cf39b9bfe · outbound

This paper cites 37 Qiu, X., Cheng, H., Wu, X., Hu, J., Guo, C., Yang, B.,.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting 37 Qiu, X., Cheng, H., Wu, X., Hu, J., Guo, C., Yang, B.,

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-10T10:57:05.479520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4861ee0c-e2c6-4963-8e55-24777439661d · outbound

This paper cites Attention Is All You Need.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting Attention Is All You Need

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:57:05.499838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4d76e44e-acc3-48b6-881e-fc3a5753b4e0 · outbound

This paper cites TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

Reference 15

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:57:05.502857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 29550a86-7c29-4f48-9532-e4430c7a87fa · outbound

This paper cites Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:57:05.505450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c7291e82-ebc1-456f-8812-9535f5d63a39 · outbound

This paper cites Are Transformers Effective for Time Series Forecasting?.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting Are Transformers Effective for Time Series Forecasting?

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:57:05.491156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fb283eec-eb64-49f4-b9f1-ebe8484fec62 · outbound

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

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-07-10T10:57:05.508075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.