Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
S7: Selective and Simplified State Space Layers for Sequence Modeling
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.03464.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:23:53.224284Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T11:46:33.439351Z
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 b2698bb6-dadd-49d7-be8a-98265c695b3f · inbound
ControlMambaIR: Conditional Controls with State-Space Model for Image Restoration cites this paper.
ControlMambaIR: Conditional Controls with State-Space Model for Image Restoration S7: Selective and Simplified State Space Layers for Sequence Modeling
Reference 74
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:23:53.224284Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90e3b0cb-98a9-45f9-a99f-47e01534f5ac · inbound
Quantizing Small-Scale State-Space Models for Edge AI cites this paper.
Quantizing Small-Scale State-Space Models for Edge AI S7: Selective and Simplified State Space Layers for Sequence Modeling
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:54:51.820447Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 20e4640c-822e-4e12-92fb-1c774e6c89a9 · inbound
Cortical-SSM: A Deep State Space Model for Motor Imagery Decoding from EEG Signals cites this paper.
Cortical-SSM: A Deep State Space Model for Motor Imagery Decoding from EEG Signals S7: Selective and Simplified State Space Layers for Sequence Modeling
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T09:27:11.096389Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 12fb3861-878a-4c54-b5d8-60b6a0a1e4ca · inbound
Three factor delay learning rules for spiking neural networks cites this paper.
Three factor delay learning rules for spiking neural networks S7: Selective and Simplified State Space Layers for Sequence Modeling
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T13:05:05.137445Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00f178ac-6d81-40b4-a185-d05ce159386b · inbound
Low-latency Event-based Object Detection with Spatially-Sparse Linear Attention cites this paper.
Low-latency Event-based Object Detection with Spatially-Sparse Linear Attention S7: Selective and Simplified State Space Layers for Sequence Modeling
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:46:02.054673Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 10795200-c2d5-45b8-b578-929f0f5f2cdb · inbound
On the Expressive Power and Limitations of Multi-Layer SSMs cites this paper.
On the Expressive Power and Limitations of Multi-Layer SSMs S7: Selective and Simplified State Space Layers for Sequence Modeling
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T11:46:33.464353Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.