Paper Citation Record · LEDGER

MambaOut: Do We Really Need Mamba for Vision?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2405.07992.

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

pith.paper-citation-record.v1
2405.07992 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:48:15.479776Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T19:32:35.269755Z

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 0e25cfe6-802a-4f97-9597-597565d8db20 · inbound

Is Long Range Sequential Modeling Necessary For Colorectal Tumor Segmentation? cites this paper.

Is Long Range Sequential Modeling Necessary For Colorectal Tumor Segmentation? MambaOut: Do We Really Need Mamba for Vision?

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T13:48:15.479776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a11be1c-b64c-45e5-8208-416f3ce61645 · inbound

Selective Structured State Space for Multispectral-fused Small Target Detection cites this paper.

Selective Structured State Space for Multispectral-fused Small Target Detection MambaOut: Do We Really Need Mamba for Vision?

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:33.835548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f40fd105-aebe-4dc3-8ca8-9da666e14f36 · inbound

Semi-Supervised State-Space Model with Dynamic Stacking Filter for Real-World Video Deraining cites this paper.

Semi-Supervised State-Space Model with Dynamic Stacking Filter for Real-World Video Deraining MambaOut: Do We Really Need Mamba for Vision?

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T15:00:28.184655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 987129fe-8c62-467b-aaa3-be2f25752a07 · inbound

Hypergraph Mamba for Efficient Whole Slide Image Understanding cites this paper.

Hypergraph Mamba for Efficient Whole Slide Image Understanding MambaOut: Do We Really Need Mamba for Vision?

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T14:50:32.893114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0056d22-3937-477f-ad7a-ead5d5a038fc · inbound

MambaHash: Visual State Space Deep Hashing Model for Large-Scale Image Retrieval cites this paper.

MambaHash: Visual State Space Deep Hashing Model for Large-Scale Image Retrieval MambaOut: Do We Really Need Mamba for Vision?

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T23:49:00.062568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06bd437f-7cc6-46d0-a3a3-716001d12c22 · inbound

StableCodec: Taming One-Step Diffusion for Extreme Image Compression cites this paper.

StableCodec: Taming One-Step Diffusion for Extreme Image Compression MambaOut: Do We Really Need Mamba for Vision?

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-06T22:21:15.808158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b6998f6-0317-4d24-b6c9-93447fb321da · inbound

MUG: Pseudo Labeling Augmented Audio-Visual Mamba Network for Audio-Visual Video Parsing cites this paper.

MUG: Pseudo Labeling Augmented Audio-Visual Mamba Network for Audio-Visual Video Parsing MambaOut: Do We Really Need Mamba for Vision?

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T20:58:06.156919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2bb8ba9-3e39-4754-b0e4-609d63525771 · inbound

Modernizing CNN-based Weather Forecast Model towards Higher Computational Efficiency cites this paper.

Modernizing CNN-based Weather Forecast Model towards Higher Computational Efficiency MambaOut: Do We Really Need Mamba for Vision?

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T17:29:30.302115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be7eadfe-98db-4b23-a419-4a146f604fa8 · inbound

UAVScenes: A Multi-Modal Dataset for UAVs cites this paper.

UAVScenes: A Multi-Modal Dataset for UAVs MambaOut: Do We Really Need Mamba for Vision?

Reference 115

Resolution: unresolved; no resolver link, observed 2026-08-06T11:47:49.859178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f3e454b-fad5-49ee-ae71-1266485d221e · inbound

After the Party: Navigating the Mapping From Color to Ambient Lighting cites this paper.

After the Party: Navigating the Mapping From Color to Ambient Lighting MambaOut: Do We Really Need Mamba for Vision?

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-06T05:11:44.441901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36052a3a-3299-4037-9ca8-988c60a224be · inbound

VCMamba: Bridging Convolutions with Multi-Directional Mamba for Efficient Visual Representation cites this paper.

VCMamba: Bridging Convolutions with Multi-Directional Mamba for Efficient Visual Representation MambaOut: Do We Really Need Mamba for Vision?

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-05T05:58:39.217128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9633b02c-845d-436e-8661-afa4636cd430 · inbound

Balanced Diffusion-Guided Fusion for Multimodal Remote Sensing Classification cites this paper.

Balanced Diffusion-Guided Fusion for Multimodal Remote Sensing Classification MambaOut: Do We Really Need Mamba for Vision?

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-18T12:42:36.922655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 71e7a2ca-14c4-4bd7-a2b7-b599fb168fd9 · inbound

A Spatial-Spectral-Frequency Interactive Network for Multimodal Remote Sensing Classification cites this paper.

A Spatial-Spectral-Frequency Interactive Network for Multimodal Remote Sensing Classification MambaOut: Do We Really Need Mamba for Vision?

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-18T09:56:13.039109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c1e458a9-9a74-4252-abb7-6da621ba364f · inbound

A Spatial-Spectral-Frequency Interactive Network for Multimodal Remote Sensing Classification cites this paper.

A Spatial-Spectral-Frequency Interactive Network for Multimodal Remote Sensing Classification MambaOut: Do We Really Need Mamba for Vision?

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:01.166789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 655e29c4-2c41-4d24-b82d-f4827604d4b6 · inbound

DFIR-DETR: Frequency-Domain Iterative Refinement and Dynamic Feature Aggregation for Small Object Detection cites this paper.

DFIR-DETR: Frequency-Domain Iterative Refinement and Dynamic Feature Aggregation for Small Object Detection MambaOut: Do We Really Need Mamba for Vision?

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-25T07:45:29.658882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d5384f3f-5e71-4ccf-97f9-11fa873a058a · inbound

HAMSA: Scanning-Free Vision State Space Models via SpectralPulseNet cites this paper.

HAMSA: Scanning-Free Vision State Space Models via SpectralPulseNet MambaOut: Do We Really Need Mamba for Vision?

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:40:18.950847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8331ff79-4295-4681-a557-461553f693fc · inbound

Deep neural networks with Fisher vector encoding for medical image classification cites this paper.

Deep neural networks with Fisher vector encoding for medical image classification MambaOut: Do We Really Need Mamba for Vision?

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:00:58.910972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 89683f0b-acd2-4f99-8517-684754b91802 · inbound

Edge-Efficient Image Restoration: Transformer Distillation into State-Space Models cites this paper.

Edge-Efficient Image Restoration: Transformer Distillation into State-Space Models MambaOut: Do We Really Need Mamba for Vision?

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:40:40.268500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation daddd1c3-64fe-41ab-9fc0-1f5ee364d0ad · inbound

STAR: Semantic-Temporal Adaptive Representation Learning for Few-Shot Action Recognition cites this paper.

STAR: Semantic-Temporal Adaptive Representation Learning for Few-Shot Action Recognition MambaOut: Do We Really Need Mamba for Vision?

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:19:27.159180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ed0cc818-8fa0-4035-8176-2325a940742c · inbound

Scaling Parallel Sequence Models to Foundation-Scale Vision Encoders cites this paper.

Scaling Parallel Sequence Models to Foundation-Scale Vision Encoders MambaOut: Do We Really Need Mamba for Vision?

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T19:32:35.271250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.