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Paper Citation Record · LEDGER

Autoregressive Pretraining with Mamba in Vision

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.07537.

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

pith.paper-citation-record.v1
2406.07537 v1

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 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:58:40.338323Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T14:25:47.196263Z

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 a062b888-e48c-4729-aee8-daffbc6e273a · inbound

A Survey of Mamba cites this paper.

A Survey of Mamba Autoregressive Pretraining with Mamba in Vision

Reference 157

Resolution
verified exact
arxiv_id, observed 2026-05-23T22:13:30.645172Z

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.

source=pdf_text observed=2026-05-23T22:09:19.917854Z digest=sha256:0c39e2891de7cf9bb636f9cdab6a0d365962f4b40c06af42666460c546391b0e

Observation a2265e88-f7f1-41bf-af59-847173c0ab45 · inbound

Surface Vision Mamba: Leveraging Bidirectional State Space Model for Efficient Spherical Manifold Representation cites this paper.

Surface Vision Mamba: Leveraging Bidirectional State Space Model for Efficient Spherical Manifold Representation Autoregressive Pretraining with Mamba in Vision

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-10T14:58:40.338323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:58:40.338323Z digest=sha256:05ef2b2c997a90146634eb65f74a74a622f738cd8a961795529c1baf42b8fb5b

Observation 9c461ef3-cc6e-4b92-8c8a-3db74e1e26ab · inbound

Fast Vision Mamba: Pooling Spatial Dimensions for Accelerated Processing cites this paper.

Fast Vision Mamba: Pooling Spatial Dimensions for Accelerated Processing Autoregressive Pretraining with Mamba in Vision

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-09T18:28:48.358953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:28:48.358953Z digest=sha256:1a63523f6ea6a235f250455d100a35c631d18d167727cbbaa792be04ee5e50f7

Observation 0d82f474-7078-40b1-906b-af6c12e11440 · inbound

Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation cites this paper.

Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation Autoregressive Pretraining with Mamba in Vision

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:25:47.198011Z

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.

source=pdf_text observed=2026-06-30T21:17:16.489486Z digest=sha256:81cfd8c37a3bf819c2497f0066c211d0397aafc457aaaacc760a5c6e70c28dbc