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Paper Citation Record · LEDGER

Diagonal State Spaces are as Effective as Structured State Spaces

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2203.14343.

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

pith.paper-citation-record.v1
2203.14343 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T22:12:59.435414Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 78785bab-5c36-422e-9ead-b514a7e8c1c2 · inbound

Gated Linear Attention Transformers with Hardware-Efficient Training cites this paper.

Gated Linear Attention Transformers with Hardware-Efficient Training Diagonal State Spaces are as Effective as Structured State Spaces

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-15T01:15:14.047422Z

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.

source=arxiv_source observed=2026-05-15T01:15:13.991219Z digest=sha256:0ec48e58ce697e847d32e374709bd55a89eb22e107cc76e7c31cacd0be689219

Observation 0309458f-4098-44d8-9f0a-7a670198c7af · inbound

Deep Learning for Virtual Reality User Identification: A Benchmark cites this paper.

Deep Learning for Virtual Reality User Identification: A Benchmark Diagonal State Spaces are as Effective as Structured State Spaces

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-15T11:29:58.785079Z

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.

source=pdf_text observed=2026-05-15T11:27:36.130684Z digest=sha256:b401fb411b1f9b653a01e2093b7bcb54012277f3c935bb56ae751bdd83938c27

Observation 091ed3c8-2f0b-48ec-ade3-99ae92d538c5 · inbound

Beyond Similarity: Temporal Operator Attention for Time Series Analysis cites this paper.

Beyond Similarity: Temporal Operator Attention for Time Series Analysis Diagonal State Spaces are as Effective as Structured State Spaces

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-13T02:47:07.761989Z

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.

source=pdf_text observed=2026-05-13T02:46:08.480763Z digest=sha256:2cb79f40d45672b7825298be9dab94aebe3c6558fffd927b92e8c428d6f2ab5f

Observation 27db99be-09a7-43a2-a507-4a315053646d · inbound

Beyond Similarity: Temporal Operator Attention for Time Series Analysis cites this paper.

Beyond Similarity: Temporal Operator Attention for Time Series Analysis Diagonal State Spaces are as Effective as Structured State Spaces

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:15:46.523561Z

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.

source=pdf_text observed=2026-06-30T22:12:59.435414Z digest=sha256:78e35a9d6eecb13463b2dcd1e8d40cc2be478c92f76df976275bfd23e1c4daae

Observation d04d6f25-a4c7-47d9-a93e-853a43bee6cd · inbound

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement cites this paper.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Diagonal State Spaces are as Effective as Structured State Spaces

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-07-04T12:29:51.715827Z

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.

source=pdf_text observed=2026-06-26T06:49:46.425849Z digest=sha256:ccf8d3efa535cdc1d614dff57085ae21a91447bf805c7e5f0ca691e622aa0893