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Paper Citation Record · LEDGER

DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2403.00818.

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

pith.paper-citation-record.v1
2403.00818 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:56:23.602903Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T22:13:30.617531Z

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 609d396a-a287-4980-a702-5c208ba4e654 · inbound

A Survey on Efficient Inference for Large Language Models cites this paper.

A Survey on Efficient Inference for Large Language Models DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models

Reference 106

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:39:33.324378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T02:39:33.007894Z digest=sha256:49247b482045528b0650347cd96a31cbcfd109863ce4d4b8d37d4c9df96215f9

Observation 36bbc029-917f-45d5-af0d-830c0b0120a2 · inbound

A Survey of Mamba cites this paper.

A Survey of Mamba DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-05-23T22:13:30.619580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T22:09:19.917854Z digest=sha256:f63a9a6e03789b1fe978e57295eadde5f5f3a4c932ef220361432f1dc81bc5ef

Observation 00194f5a-2229-4562-823f-d60c38b5155b · inbound

A Survey of Retentive Network cites this paper.

A Survey of Retentive Network DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T05:56:23.602903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:56:23.602903Z digest=sha256:024ce830206062065a73dc97e3b4388a9363db8139d623329c5687469221693d

Observation aca3df03-ee8f-49af-8f0a-c4023f099d45 · inbound

DeMo++: Motion Decoupling for Autonomous Driving cites this paper.

DeMo++: Motion Decoupling for Autonomous Driving DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-06T14:55:03.012691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:55:03.012691Z digest=sha256:a82df571da53ca9a36bfdafe3e0e7c94619aabdc5c58b6fe8cd9eabb4961b1b8