Paper Citation Record · LEDGER

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection

As of 22 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2506.03654.

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

pith.paper-citation-record.v1
2506.03654 v3

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:04:17.852724Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact0
verified fuzzy11
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ec55c58c-f418-4c1d-a15b-54efeffb85da · outbound

This paper cites YOLOv4: Optimal Speed and Accuracy of Object Detection.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.728352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4232a40c-d2e3-4906-ad8a-3a4498dc6a0a · outbound

This paper cites an unresolved cited work.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.734115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f128446d-edec-40b1-b992-61ee39ad3a01 · outbound

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

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.739011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80526ffa-5b97-467c-9bf5-f24269081e98 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection Efficiently Modeling Long Sequences with Structured State Spaces

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.743989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b4e5bf1-b96a-4be6-9d7f-45976df3dca4 · outbound

This paper cites LocalMamba: Visual State Space Model with Windowed Selective Scan.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection LocalMamba: Visual State Space Model with Windowed Selective Scan

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.748844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3816412f-c613-4898-bbc1-bc202479e027 · outbound

This paper cites https://doi.org/10.5281/zenodo.3908559, https://github.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection https://doi.org/10.5281/zenodo.3908559, https://github

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.753772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b1f2e61-f73c-42b2-858b-f339ff4fde3a · outbound

This paper cites an unresolved cited work.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:04:18.281744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c46d7890-2129-41c7-8095-5b7d6f58b147 · outbound

This paper cites YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.763273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6e4f5ae-7c56-456f-95ad-0189bab3769b · outbound

This paper cites Advances in Neural Information Processing Sys- tems 35, 12934–12949 (2022).

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection Advances in Neural Information Processing Sys- tems 35, 12934–12949 (2022)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:04:18.266460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 69185b98-fd77-4c6b-9320-6dba3b576817 · outbound

This paper cites VMamba: Visual State Space Model.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection VMamba: Visual State Space Model

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.772287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c628613-9ada-4dc9-aa48-26400233384d · outbound

This paper cites MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.777123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3545f1b-3fb9-4a1c-9ed6-6509b075e926 · outbound

This paper cites In: Eu- ropean conference on computer vision.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection In: Eu- ropean conference on computer vision

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:04:18.250129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 20734bb3-2a26-42d7-a24c-8a44730803e0 · outbound

This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recog- nition (CVPR) (June 2016).

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recog- nition (CVPR) (June 2016)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:04:18.234572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fa5fee16-2d44-4a18-8f1f-2f010171e191 · outbound

This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (July 2017).

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (July 2017)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:04:18.218695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 67905de7-3273-4ad9-bf20-4dc482ee243f · outbound

This paper cites YOLOv3: An Incremental Improvement.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection YOLOv3: An Incremental Improvement

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.795226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9f156e7-10db-4a67-be95-3eae2d7aac3b · outbound

This paper cites YOLOv12: Attention-Centric Real-Time Object Detectors.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection YOLOv12: Attention-Centric Real-Time Object Detectors

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.800278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfc5ccd8-69e8-4fa2-a73b-cf0ea74d8422 · outbound

This paper cites Advances in neural information processing systems 30 (2017).

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection Advances in neural information processing systems 30 (2017)

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.805064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e76903c-0322-4480-8e2d-817a6143c265 · outbound

This paper cites Advances in Neural Information Processing Systems 37, 107984–108011 (2024).

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection Advances in Neural Information Processing Systems 37, 107984–108011 (2024)

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.809446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25430b9a-5ba2-4dec-9554-2749db40b902 · outbound

This paper cites In: Proceedings of the IEEE /CVF conference on com- puter vision and pattern recognition.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection In: Proceedings of the IEEE /CVF conference on com- puter vision and pattern recognition

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:04:18.182124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7e0f2ec5-ae8e-4dd1-8ab1-2ddbf32b4db9 · outbound

This paper cites In: European conference on computer vision.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection In: European conference on computer vision

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:04:18.167121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8668d7b9-904f-4a16-956e-09a16aefbde5 · outbound

This paper cites Mamba YOLO: A Simple Baseline for Object Detection with State Space Model.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection Mamba YOLO: A Simple Baseline for Object Detection with State Space Model

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:17.824285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 692562f0-935d-4491-9c66-c37b06f4a391 · outbound

This paper cites In: The IEEE Conference on Com- puter Vision and Pattern Recognition (CVPR) (June 2018).

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection In: The IEEE Conference on Com- puter Vision and Pattern Recognition (CVPR) (June 2018)

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:04:18.150075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3f78f963-97bc-4e39-953d-b7be59cf15d5 · outbound

This paper cites CAAI transactions on intelligence technology 8(2), 319–330 (2023).

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection CAAI transactions on intelligence technology 8(2), 319–330 (2023)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:04:18.134605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 477870ff-4ce1-4870-8c21-7f5e1a9cb8b9 · outbound

This paper cites IEEE Transactions on Vehicular Technology 73(4), 5647–5658 (2023).

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection IEEE Transactions on Vehicular Technology 73(4), 5647–5658 (2023)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:04:18.119123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7c465aef-01ba-4d25-a6de-9dc1e784fd6c · outbound

This paper cites IEEE Sensors Journal (2024).

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection IEEE Sensors Journal (2024)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:04:18.103749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 61d04967-4edf-4ded-8b69-acf5d2d4fe85 · outbound

This paper cites MHAF-YOLO: Multi-Branch Heterogeneous Auxiliary Fusion YOLO for accurate object detection.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection MHAF-YOLO: Multi-Branch Heterogeneous Auxiliary Fusion YOLO for accurate object detection

Reference 26

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T11:04:17.917412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 637e8442-2eb6-4ade-a84e-ca12f17bf147 · outbound

This paper cites In: Forty-first International Confer- ence on Machine Learning (2024) 7.

MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection In: Forty-first International Confer- ence on Machine Learning (2024) 7

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:04:18.088962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.