Pith. sign in

Paper Citation Record · LEDGER

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling

As of 19 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2506.07920.

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

pith.paper-citation-record.v1
2506.07920 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:29:06.139982Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

27 of 27 outbound references displayed

  • verified exact2
  • verified fuzzy12
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 73451ac4-e726-4be3-b4bc-548344c5ad83 · outbound

This paper cites Transformers in Time Series: A Survey.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Transformers in Time Series: A Survey

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:02.815557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:02.815557Z digest=sha256:17b844d7ca25ba347132a37b6341157ccd48bd0a83392b7a108d0729318edd8c

Observation 5cca748e-1438-410b-b262-b13366819bfb · outbound

This paper cites Cheung, Ahmed Imtiaz Hu- mayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, and Richard G.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Cheung, Ahmed Imtiaz Hu- mayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, and Richard G

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:10.626297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:02.946373Z digest=sha256:597931babf739d8946633c0aa41c41ded77ea0c745ce0f217f17f357b6d3fb47

Observation 44146254-065d-487e-b936-4d676983e19f · outbound

This paper cites Machine learning advances for time series forecasting.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Machine learning advances for time series forecasting

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:10.426528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:03.084731Z digest=sha256:c6a2bd0e2652129d32d323d60e7ff4ead06a04c4b17f519329620fd99b057c65

Observation 159d277e-a623-4d34-a6ed-f80b97040761 · outbound

This paper cites Scinet: Time series modeling and forecasting with sample convolution and interaction.Advances in Neural Information Processing Systems , 35:5816–5828, 2022.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Scinet: Time series modeling and forecasting with sample convolution and interaction.Advances in Neural Information Processing Systems , 35:5816–5828, 2022

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:10.163628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:03.203423Z digest=sha256:b8e41bd2fc227b8e821204086236141bdaa5ee7fc869c78f8c344d373ce5f6dc

Observation b39d13e4-dfd0-43ec-9dd8-167e23237df8 · outbound

This paper cites Time series forecasting using a hybrid arima and neural network model.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Time series forecasting using a hybrid arima and neural network model

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:09.889824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:03.358435Z digest=sha256:4da65e6b88833f50d38a3086463c61c90bc701f8f8c9d0cf2bba7ec97ace91e3

Observation 6f63de68-2003-4aff-b604-1df42af538dd · outbound

This paper cites TSMixer: An All-MLP Architecture for Time Series Forecasting.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling TSMixer: An All-MLP Architecture for Time Series Forecasting

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:03.484104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:03.484104Z digest=sha256:1e6a5bcb0d49260b63f5b55d7d733e9f4616d29e66f3c1a6cec6afa46954a153

Observation af28f762-865a-4859-b634-71276eabe8a3 · outbound

This paper cites Rethinking Full Connectivity in Recurrent Neural Networks.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Rethinking Full Connectivity in Recurrent Neural Networks

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:03.582703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:03.582703Z digest=sha256:58f6ae44f6ee94c21756e3030e0a4fe81100f6129139e2993ca0b85796e1ea4d

Observation 10ebe32c-60a1-43be-9841-b0298eb1ea7a · outbound

This paper cites On the difficulty of training recurrent neural networks.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling On the difficulty of training recurrent neural networks

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:03.681138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:03.681138Z digest=sha256:029ad201839d1f51f7e097c9ada559f2c42bad01ad8c0c43c1a583f5589e7aaa

Observation 816f41ae-81f4-4afa-80e4-e07d5eb2fa80 · outbound

This paper cites Understanding the effective receptive field in deep convolutional neural networks.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Understanding the effective receptive field in deep convolutional neural networks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:03.803056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:03.803056Z digest=sha256:f35d94d6486da53f87625a247046ff3d775bb872797f241ecd64225c2c98049d

Observation 8cca54a2-94bc-4663-bef2-a7beaf690fbd · outbound

This paper cites HiPPO: Recurrent memory with optimal polynomial projections.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling HiPPO: Recurrent memory with optimal polynomial projections

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:09.648736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:03.958065Z digest=sha256:c1d8923024708d5fa7f2df6ee1e17d3bc81c40fa1e0a550541e674891d095bae

Observation 64ef644c-66bd-4c8f-a344-c09027d069e1 · outbound

This paper cites Efficiently modeling long sequences with structured state spaces.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Efficiently modeling long sequences with structured state spaces

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:09.503346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:04.052264Z digest=sha256:2095d180947a49846f4e48801c7c87c568fdd59c7854f68f474d04093e9da258

Observation 62832694-603e-412f-8e77-374935423949 · outbound

This paper cites SaFARi: State-Space Models for Frame-Agnostic Representation.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling SaFARi: State-Space Models for Frame-Agnostic Representation

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:29:06.843955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:04.205525Z digest=sha256:66918a6938695ccb5f3189d17dd16f2f4382b8d9ffea27584e7a4ea767980e9b

Observation dcd02e5b-2b65-415a-981f-3d75eb23d113 · outbound

This paper cites WaLRUS: Wavelets for Long-range Representation Using SSMs.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling WaLRUS: Wavelets for Long-range Representation Using SSMs

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:29:06.590546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:04.334308Z digest=sha256:d9a2abd4d77212357c020ae9096dc377ff2aa7663c6dbb00682f388e31849142

Observation cce4ee04-6a7e-4af2-9f29-15d8108fcaf8 · outbound

This paper cites Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:04.477213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:04.477213Z digest=sha256:0f7d6b90804b60f01450bffef838cc41caac9a68f78213de70c71ebdd2094803

Observation d75095a5-4f35-4aad-96c6-9e5ca0c50602 · outbound

This paper cites Combining recurrent, convolutional, and continuous-time models with linear state space layers.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Combining recurrent, convolutional, and continuous-time models with linear state space layers

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:09.339296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:04.638530Z digest=sha256:ada89e2a3eab3f2929f3690cf74fd94cb9567d213d4841a192329426d13e27dd

Observation 51f1b94e-dbf7-471c-b45e-ccad60cf1397 · outbound

This paper cites On the parameterization and initialization of diagonal state space models.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling On the parameterization and initialization of diagonal state space models

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:09.193065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:04.746996Z digest=sha256:3ebd02cb1d26dbf5d0c0682c0cce571ec838879bc39faaee634790eab34a212a

Observation c3070e2f-7df1-4deb-bc57-a698f5c316b0 · outbound

This paper cites How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:04.893078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:04.893078Z digest=sha256:dca1c5db39fbffa24d1706503ca391ac1e8cb2bf7685d8b95163d747b65b033f

Observation d588022c-0c82-4f8f-aee9-d9d5af5499af · outbound

This paper cites Long Range Arena: A Benchmark for Efficient Transformers.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Long Range Arena: A Benchmark for Efficient Transformers

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:05.003723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:05.003723Z digest=sha256:7eea68ed0493ea1ccdddd433f9f406eb71a3f7dc36dc773762bb9a3498b44376

Observation ffdc31d9-8281-40b8-9052-96be82be4acd · outbound

This paper cites Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:05.194785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:05.194785Z digest=sha256:9c38dda7d350db56391ee70dd9fc07f436952be15819cdd13c494b2f867ec2dc

Observation 2deaa9e8-e281-4199-94f2-a21cc1346d06 · outbound

This paper cites Learning multiple layers of features from tiny images.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Learning multiple layers of features from tiny images

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:09.025267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:05.350978Z digest=sha256:4dd2b5800de0b185045c89899595dbfa8aecdbee7272dedb02212805247930f4

Observation d5bbed68-73e9-43c2-8427-929f1f1783c2 · outbound

This paper cites Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T05:29:05.437094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:29:05.437094Z digest=sha256:96e56b16a00a39facb7427e4c5c118259851363a04e881146be27b3b59e2ea75

Observation c4e45eda-f36c-45dc-bd74-9394bad8ed0a · outbound

This paper cites Toward a robust estimation of respiratory rate from pulse oximeters.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Toward a robust estimation of respiratory rate from pulse oximeters

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:08.878461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:05.523567Z digest=sha256:b7bda2d35f6cabfcb41a4e15fd1c971304221457b6d187fedcf5aa5669a541d8

Observation 1c97ed6c-0b70-4c8c-9398-31e662bdc837 · outbound

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

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Autoformer: Decomposition trans- formers with auto-correlation for long-term series forecasting

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:08.631741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:05.633438Z digest=sha256:ac79afb203d42db28adf16ee1b790a38bd52d18d43e0e9b1ac9eb560fa29565c

Observation 68b682ed-b026-47b5-81a9-f12133b5824f · outbound

This paper cites Modeling long-and short-term temporal patterns with deep neural networks.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Modeling long-and short-term temporal patterns with deep neural networks

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:29:08.256677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:05.711572Z digest=sha256:ea813804c7ae3cf346f0ec1e87a480856c4f26bf3f8a2860c8f4eb0008b402ff

Observation edc643e7-aff3-4e59-8ee1-3a77ac48984c · outbound

This paper cites an unresolved cited work.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:29:07.867773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:05.796937Z digest=sha256:02ddc9745bbe989dc4c37882e7b9aa73f48f1f9e1b378cdef79065ece515aed9

Observation dc137711-3df9-4cc8-ac59-baf1ba6607e8 · outbound

This paper cites an unresolved cited work.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:29:07.573189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:06.020371Z digest=sha256:877e574b6284333d958fcdf49a6cca41264a2a74b4d4658f1aa3386a966a7f35

Observation f5d7b7ff-5f33-43ae-a9bc-ce4a36bff11e · outbound

This paper cites an unresolved cited work.

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:29:07.211662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T05:29:06.139982Z digest=sha256:d50177d4d2b90a4a2f6cbdfceb8c67937aa8ec7b27bd3e57099a4e2d59204735

Pith citing papers

No inbound Pith citation observations are available.