Paper Citation Record · LEDGER

Efficient Long Sequence Modeling via State Space Augmented Transformer

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2212.08136.

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

pith.paper-citation-record.v1
2212.08136 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:52:42.700496Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T22:12:11.701219Z

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 ac8671b1-8181-42e3-932b-17d7c116681e · inbound

Mamba: Linear-Time Sequence Modeling with Selective State Spaces cites this paper.

Mamba: Linear-Time Sequence Modeling with Selective State Spaces Efficient Long Sequence Modeling via State Space Augmented Transformer

Reference 116

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:53:06.708476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9373747f-f9f7-4541-a473-c7d32fed6ec3 · inbound

Jamba: A Hybrid Transformer-Mamba Language Model cites this paper.

Jamba: A Hybrid Transformer-Mamba Language Model Efficient Long Sequence Modeling via State Space Augmented Transformer

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-13T14:11:27.229169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0176a3b0-e074-4fe7-9126-d7f8a91bb547 · inbound

Advancing Intelligent Sequence Modeling: Evolution, Trade-offs, and Applications of State-Space Architectures from S4 to Mamba cites this paper.

Advancing Intelligent Sequence Modeling: Evolution, Trade-offs, and Applications of State-Space Architectures from S4 to Mamba Efficient Long Sequence Modeling via State Space Augmented Transformer

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:12:11.704403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1c99e954-aa90-4c3d-bf08-e9a814bf49d9 · inbound

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing cites this paper.

Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing Efficient Long Sequence Modeling via State Space Augmented Transformer

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T04:52:42.700496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1609cb38-dc68-4e7d-be0c-b4819fa450ed · inbound

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding cites this paper.

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding Efficient Long Sequence Modeling via State Space Augmented Transformer

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:34.834731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5efda260-6214-46c5-b6f0-09958d84ab61 · inbound

Towards Understanding Self-Pretraining for Sequence Classification cites this paper.

Towards Understanding Self-Pretraining for Sequence Classification Efficient Long Sequence Modeling via State Space Augmented Transformer

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:33:58.941590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.