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Paper Citation Record · LEDGER

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds

As of 19 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2505.10601.

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

pith.paper-citation-record.v1
2505.10601 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:14:35.739462Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

53 of 53 outbound references displayed

  • verified exact1
  • verified fuzzy43
  • unresolved9
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5d3a35d6-b427-406c-b86f-c1ca7cb4d4bb · outbound

This paper cites Rangeldm: Fast realistic lidar point cloud generation,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Rangeldm: Fast realistic lidar point cloud generation,

Reference 1

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Source-reported events for the cited work

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Observation 095f82b5-796c-4625-afd1-83884acbf41a · outbound

This paper cites Hvnet: Hybrid voxel network for lidar based 3d object detection,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Hvnet: Hybrid voxel network for lidar based 3d object detection,

Reference 2

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation afdf1e3e-d7f4-4992-bf5c-df85503fb715 · outbound

This paper cites Panoptic-polarnet: Proposal-free lidar point cloud panoptic segmentation,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Panoptic-polarnet: Proposal-free lidar point cloud panoptic segmentation,

Reference 3

Resolution
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Source-reported events for the cited work

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Observation 00a09def-3b17-44ce-9d66-1c80d0398bd6 · outbound

This paper cites Deepmapping2: Self-supervised large-scale lidar map optimization,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Deepmapping2: Self-supervised large-scale lidar map optimization,

Reference 4

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f8c75f96-4eac-4f31-836e-95fe0908a553 · outbound

This paper cites Fast-lio2: Fast direct lidar-inertial odometry,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Fast-lio2: Fast direct lidar-inertial odometry,

Reference 5

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 84000522-e919-46c6-9f61-cc97b6ff0f5a · outbound

This paper cites Vpl-slam: a vertical line supported point line monocular slam system,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Vpl-slam: a vertical line supported point line monocular slam system,

Reference 6

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f55c2a4c-a7ef-455d-b4c8-fc074bdee1b7 · outbound

This paper cites 3d point clouds data super resolution-aided lidar odometry for vehicular positioning in urban canyons,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds 3d point clouds data super resolution-aided lidar odometry for vehicular positioning in urban canyons,

Reference 7

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3c190e66-9cb1-40e9-bac9-ba9c402ea5c7 · outbound

This paper cites Pugeo-net: A geometry-centric network for 3d point cloud upsampling,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Pugeo-net: A geometry-centric network for 3d point cloud upsampling,

Reference 8

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 267618bd-5c77-4d83-8060-1531f28d4c18 · outbound

This paper cites Pu-net: Point cloud upsampling network,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Pu-net: Point cloud upsampling network,

Reference 9

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 556be995-3355-415f-a709-d29f1e8c0ae8 · outbound

This paper cites Patch-based progressive 3d point set upsampling,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Patch-based progressive 3d point set upsampling,

Reference 10

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 730a4cfc-cede-4b22-b76c-91b92694fd6d · outbound

This paper cites Edge-aware point set resampling,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Edge-aware point set resampling,

Reference 11

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 1f77f687-87f0-4764-af6d-377f818dcf76 · outbound

This paper cites Point cloud upsampling via disentangled refinement,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Point cloud upsampling via disentangled refinement,

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 43141d7a-f6a8-4b2e-91a2-29d692468f03 · outbound

This paper cites Simulation-based lidar super-resolution for ground vehicles,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Simulation-based lidar super-resolution for ground vehicles,

Reference 13

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 68208cf8-3f11-40c0-ad22-b26154006fec · outbound

This paper cites Analysis of Deep Learning-Based Colorization and Super-Resolution Techniques for Lidar Imagery.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Analysis of Deep Learning-Based Colorization and Super-Resolution Techniques for Lidar Imagery

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a4aedf33-1ce0-4c0c-900e-faffc4f6d96f · outbound

This paper cites Single image super-resolution via a holistic attention network,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Single image super-resolution via a holistic attention network,

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 34cf2d4b-ed65-4247-b40f-0840704ace79 · outbound

This paper cites Image super-resolution using very deep residual channel attention networks,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Image super-resolution using very deep residual channel attention networks,

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 7c6b63fb-2711-469f-9a6f-63c1a4aea121 · outbound

This paper cites A deep journey into super-resolution: A survey,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds A deep journey into super-resolution: A survey,

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3403c901-8fd6-42a5-adf5-17022ee9110c · outbound

This paper cites Attention is all you need,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Attention is all you need,

Reference 19

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9286edcd-219a-4414-85c8-849fae460bc2 · outbound

This paper cites Vmamba: Visual state space model,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Vmamba: Visual state space model,

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3567e80b-cd0f-4e06-b793-7c3f0a074c8d · outbound

This paper cites Rsmamba: Remote sensing image classification with state space model,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Rsmamba: Remote sensing image classification with state space model,

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 0423fb14-618d-4b7b-98b9-41b62492282d · outbound

This paper cites Classifying cervical oct images using masked autoencoders with vmamba,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Classifying cervical oct images using masked autoencoders with vmamba,

Reference 22

Resolution
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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f0009084-bddf-4156-91bf-4d1d7011a1f5 · outbound

This paper cites Face mamba: A facial emotion analysis network based on vmamba*,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Face mamba: A facial emotion analysis network based on vmamba*,

Reference 23

Resolution
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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 72898214-0915-4385-a0b8-26938c58eb5f · outbound

This paper cites Computing and rendering point set surfaces,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Computing and rendering point set surfaces,

Reference 24

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation d73c5005-244e-45d4-b703-2f589a9f48a3 · outbound

This paper cites Parameterization-free projection for geometry reconstruction,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Parameterization-free projection for geometry reconstruction,

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ed8e591d-c554-423c-9674-4908a18fb821 · outbound

This paper cites Consolidation of unorganized point clouds for surface reconstruction,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Consolidation of unorganized point clouds for surface reconstruction,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:36.040568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 88b24112-dbf1-463d-b94f-eb70bfe84ae9 · outbound

This paper cites Efficient deep super-resolution of voxelized point cloud in geometry compression,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Efficient deep super-resolution of voxelized point cloud in geometry compression,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:36.030032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8344133c-2342-405c-b809-8dc8a880261f · outbound

This paper cites Hierarchical attention feature fusion and refinement network for point cloud upsampling,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Hierarchical attention feature fusion and refinement network for point cloud upsampling,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:36.021785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3be7b007-4977-4ef4-9c3a-6f1bcdcdb39f · outbound

This paper cites Point cloud upsampling via a coarse-to-fine network,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Point cloud upsampling via a coarse-to-fine network,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:36.012471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 7307f273-a48a-4d87-8e81-c4849cdc4694 · outbound

This paper cites Point cloud upsampling via disentangled refinement,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Point cloud upsampling via disentangled refinement,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:36.003369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation edb7098f-b07d-45e1-bfbe-498b24c13f51 · outbound

This paper cites HALS: A Height-Aware Lidar Super-Resolution Framework for Autonomous Driving.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds HALS: A Height-Aware Lidar Super-Resolution Framework for Autonomous Driving

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-15T21:14:35.834275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 6dcc8c6f-5840-4967-9055-9319d7cd36af · outbound

This paper cites Fbrnn: feedbackrecurrentneuralnetworkforextremeimagesuper-resolution,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Fbrnn: feedbackrecurrentneuralnetworkforextremeimagesuper-resolution,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.994619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation d1cc8a53-e197-40bb-8f58-3e2398d0c451 · outbound

This paper cites Image super-resolution with cross-scale non-local attention and exhaustive self- exemplars mining,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Image super-resolution with cross-scale non-local attention and exhaustive self- exemplars mining,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.986073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3c5f239c-4fab-44fb-95f7-26b7a93bc8d8 · outbound

This paper cites Apointclouddensityenhancementmethodbasedonsuper-resolutionconvolutional neural network,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Apointclouddensityenhancementmethodbasedonsuper-resolutionconvolutional neural network,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.975266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.670064Z digest=sha256:27bf20e6f6a2a6fbed8075f95ae70f467839224dca52b375541ce43ff597b846

Observation 03cd752c-3a8f-4108-9675-f891df3b6a19 · outbound

This paper cites Lsr-ribnet: A novel lidar super-resolution model for scene semantic segmentation in outdoor environments,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Lsr-ribnet: A novel lidar super-resolution model for scene semantic segmentation in outdoor environments,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.966615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.672638Z digest=sha256:d78a896fdaf56413efc7fd18aabc8dcd7736d133f6c6df68972125eb0ed45c28

Observation 9f2808a4-930b-4d74-b8c5-b8b54d7b7fa2 · outbound

This paper cites Up-sampling method for low-resolution lidar point cloud to enhance 3d object detection in an autonomous driving environment,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Up-sampling method for low-resolution lidar point cloud to enhance 3d object detection in an autonomous driving environment,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.955825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.675687Z digest=sha256:abb8637d5117b16674a37f390968cbefc6991059d73211e6a9682826001c2003

Observation 5b088ed4-554a-4509-bd93-7fb37f177025 · outbound

This paper cites Channel attention based network for lidar super-resolution,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Channel attention based network for lidar super-resolution,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.947863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.678972Z digest=sha256:e511d870f4821ced2caa275e001191f83bf00c59fd33325cf0394a9f6f04d6ae

Observation 9e6de603-9ece-457d-87fb-1d42c855be9c · outbound

This paper cites Tulip: Transformer for upsampling of lidar point clouds,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Tulip: Transformer for upsampling of lidar point clouds,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.939754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.682636Z digest=sha256:29c5ca74e5ec69059b464bc5120cb6c36af25ed0d9bf4ecb0930ae6a562d64d9

Observation a19818a4-17bb-45e3-ac1d-e9f86c5ceda5 · outbound

This paper cites U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:35.685662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:35.685662Z digest=sha256:da0ed7cda1a00a8a308bced1fcbe9dd0504236a4206f6b09f45f85d1364b3e3e

Observation 79e790f4-9bbd-4f55-a494-1217a44fb875 · outbound

This paper cites Weak-Mamba-UNet: Visual Mamba Makes CNN and ViT Work Better for Scribble-based Medical Image Segmentation.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Weak-Mamba-UNet: Visual Mamba Makes CNN and ViT Work Better for Scribble-based Medical Image Segmentation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:35.689719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:35.689719Z digest=sha256:777564106a8d04ddf936ca0efc4314fe79ec234580ce102b6c0f4c5e1d92dbbc

Observation c8a5edb2-5932-4e00-9b81-989f48080c5b · outbound

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

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:35.693264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:35.693264Z digest=sha256:3975171d42ee221ce622768dd2a6ca7ff120fc364157cd09429240e26496ccff

Observation 1bfe44a3-aa43-44ca-a66f-6401d1ad74e0 · outbound

This paper cites Vision Mamba: A Comprehensive Survey and Taxonomy.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Vision Mamba: A Comprehensive Survey and Taxonomy

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:35.697299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:35.697299Z digest=sha256:674b0f21db0730970af2e69269c47cc005400fb46d3155d12cd54e5ee3300778

Observation d3ccd5b2-7ac3-4ed2-8388-2bab76c7d50a · outbound

This paper cites Frnet: Frustum-range networks for scalable lidar segmentation,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Frnet: Frustum-range networks for scalable lidar segmentation,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.931104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.700927Z digest=sha256:0f2814dec34aff0bb35fb969d5bbeb26545fbd2266dc847cda2d8c4cff14e9e3

Observation a8b5c9b3-e823-4205-a28a-50c73039c173 · outbound

This paper cites Uniseg: A unified multi-modal lidar segmentation network and the openpcseg codebase,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Uniseg: A unified multi-modal lidar segmentation network and the openpcseg codebase,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.921859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.703921Z digest=sha256:cdf6cea14112af0a695707e9c003967c87bd3c8d0404f2ca6cb132830d4a6355

Observation 811618aa-56a4-43f1-9ed5-d11a7df51338 · outbound

This paper cites Attention U-Net: Learning Where to Look for the Pancreas.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Attention U-Net: Learning Where to Look for the Pancreas

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:35.707429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:35.707429Z digest=sha256:ac6a2500b315dc9cb2860df2552881d6976a60878bf536d3eaac4d17fdf8571d

Observation a0ed9938-dee4-4867-a15c-b7496f3eeb5a · outbound

This paper cites Mixed transformer u-net for medical image segmentation,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Mixed transformer u-net for medical image segmentation,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.912181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.711402Z digest=sha256:e55b791163fced03d9e53299af0ceab9b2b373c24c98ee6580c55ecdb5e24786

Observation b3db928c-a64b-47f2-a287-e38a59e008eb · outbound

This paper cites Deep residual learning for image recognition,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Deep residual learning for image recognition,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.900951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.714472Z digest=sha256:f75c888b54f7f8f6b8a1af466b11446189ff74b5542de5499e56b6b59f5a46b4

Observation e76be8ec-36ea-4a01-a71e-ce6b6856dbd3 · outbound

This paper cites Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.890806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.717756Z digest=sha256:4eb8bf395c112f83556c3314f475f5b57f35d3d9da6f42e6fdefadcdefd2210f

Observation cf8ea427-4cb8-42a9-a321-52c2d695890d · outbound

This paper cites Panoptic nuscenes: A large-scale benchmark for lidar panoptic segmentation and tracking,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Panoptic nuscenes: A large-scale benchmark for lidar panoptic segmentation and tracking,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.880187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.720844Z digest=sha256:9a73d548cdc9d8ca350ff7e2f7a3a416bee53079c730fd45809ac3e3a7789416

Observation 1af7ff77-60ed-43af-81ce-b53489d5aced · outbound

This paper cites Pcn: Point completion network,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Pcn: Point completion network,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.871010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.724009Z digest=sha256:aaed1102220421e6e5046eadc9a3b1114797f4cc8a336a5dc83575197f0815a1

Observation e07bf36a-5d79-4e4d-b919-572dcc07fb5f · outbound

This paper cites Implicit lidar network: Lidar super-resolution via interpolation weight prediction,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Implicit lidar network: Lidar super-resolution via interpolation weight prediction,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.861674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.727296Z digest=sha256:46e6476937136cdfbf55f8ab6fc4b73b59598d07ba787e9f702b38df65787b0e

Observation 8ebf707c-1023-4829-b3a6-c265dc27538c · outbound

This paper cites Decoupled Weight Decay Regularization.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Decoupled Weight Decay Regularization

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:35.731141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:35.731141Z digest=sha256:61a3b0d8389a477f3c158cdcbb06459a18a0289d79bcf5a369d4a09c64083bb0

Observation ec780522-60ac-4377-bb56-45d9e0d12342 · outbound

This paper cites CAS-ViT: Convolutional Additive Self-attention Vision Transformers for Efficient Mobile Applications.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds CAS-ViT: Convolutional Additive Self-attention Vision Transformers for Efficient Mobile Applications

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:35.735724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:35.735724Z digest=sha256:24de88e50fd4d564c115ba53f929e45d9621e72660d01802cc66c71f946941f1

Observation 6334e9d6-d9a6-40bd-8b8c-c83c13134b44 · outbound

This paper cites Swinir: Image restoration using swin transformer,.

SRMamba: Mamba for Super-Resolution of LiDAR Point Clouds Swinir: Image restoration using swin transformer,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:35.851760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T21:14:35.739462Z digest=sha256:7ebdb0daf0393cd80c7fbbc3ca89b1e1a3f368f892e4b9d096fc24c2fe651f12

Pith citing papers

No inbound Pith citation observations are available.