Paper Citation Record · LEDGER

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation

As of 13 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2507.22454.

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

pith.paper-citation-record.v1
2507.22454 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:42:22.855477Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:32:58.781274Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T13:33:00.766295Z

Reference resolution

40 of 40 outbound references displayed

verified exact0
verified fuzzy28
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3b0359a5-6db6-489b-a264-bb12b5fbc847 · outbound

This paper cites Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.742406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45b7a7ed-b21a-4028-8fd1-60fc12fa1072 · outbound

This paper cites TurboReg: TurboClique for Robust and Efficient Point Cloud Registration.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation TurboReg: TurboClique for Robust and Efficient Point Cloud Registration

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.748453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5495fbd-9c8a-4118-ae36-ef5e6ef1c7d6 · outbound

This paper cites Mamba4d: Efficient 4d point cloud video understanding with disentangled spatial-temporal state space models,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Mamba4d: Efficient 4d point cloud video understanding with disentangled spatial-temporal state space models,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.222309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 77000b42-4447-4f77-ba50-a0d105afc5ec · outbound

This paper cites Deep learning for lidar point clouds in autonomous driving: A review,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Deep learning for lidar point clouds in autonomous driving: A review,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.212774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 818bf941-2481-478e-9860-1abacbf56bd3 · outbound

This paper cites Mne-slam: Multi-agent neural slam for mobile robots,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Mne-slam: Multi-agent neural slam for mobile robots,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.204288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f307c18d-f963-4a89-b007-23440a0c5d17 · outbound

This paper cites Dvlo: Deep visual-lidar odometry with local-to-global feature fusion and bi-directional structure alignment,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Dvlo: Deep visual-lidar odometry with local-to-global feature fusion and bi-directional structure alignment,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.195708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 39307bb0-8253-4dba-b8b7-f974130b3ccc · outbound

This paper cites Translo: A window-based masked point transformer framework for large-scale lidar odometry,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Translo: A window-based masked point transformer framework for large-scale lidar odometry,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.186429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6649315e-e766-40b0-af5c-c7879ee493f8 · outbound

This paper cites Compact 3D Gaussian Splatting For Dense Visual SLAM.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Compact 3D Gaussian Splatting For Dense Visual SLAM

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.767128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e5f42f7-1f72-4291-a5af-9e76b9304132 · outbound

This paper cites SemGauss-SLAM: Dense Semantic Gaussian Splatting SLAM.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation SemGauss-SLAM: Dense Semantic Gaussian Splatting SLAM

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.770294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04d453e4-9d93-4cc1-97a9-d70cb2ab0e87 · outbound

This paper cites Sni-slam: Semantic neural implicit slam,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Sni-slam: Semantic neural implicit slam,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.177511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 34dce0b1-cd74-436a-b072-fbfd3c8405f3 · outbound

This paper cites Plgslam: Progressive neural scene represenation with local to global bundle adjustment,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Plgslam: Progressive neural scene represenation with local to global bundle adjustment,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.168456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c9836fa3-78b1-433e-b5a5-9882a6eeb359 · outbound

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

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Rangeldm: Fast realistic lidar point cloud generation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.159729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b520bac0-9769-4ea6-96c8-08f1bbfe0093 · outbound

This paper cites Deep generative modeling of lidar data,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Deep generative modeling of lidar data,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.150449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ed45dcd1-1de6-4868-aeca-cbb07139adbd · outbound

This paper cites Learning to generate realistic lidar point clouds,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Learning to generate realistic lidar point clouds,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.141212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c7b15898-5eaa-46c2-bec7-3e13f1b83fa5 · outbound

This paper cites Learning compact representations for lidar completion and generation,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Learning compact representations for lidar completion and generation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.132824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 65ee7bba-5d3f-495a-8af0-b4ddabe4c0da · outbound

This paper cites Lidar data synthesis with denoising diffusion probabilistic models,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Lidar data synthesis with denoising diffusion probabilistic models,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.124140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation af75b3c2-de12-4e2d-b52f-2b3eede318bd · outbound

This paper cites Towards realistic scene gener- ation with lidar diffusion models,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Towards realistic scene gener- ation with lidar diffusion models,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.115478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 88b4efdc-7801-4a37-bd9d-d783054f5657 · outbound

This paper cites Generative adversarial net- works,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Generative adversarial net- works,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.107021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0fe0e945-5612-4a3a-a8c7-22d450c868e1 · outbound

This paper cites Auto-encoding variational bayes,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Auto-encoding variational bayes,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.798986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 848d8270-b39b-43b8-943e-1b44871788ac · outbound

This paper cites Glidr: Topo- logically regularized graph generative network for sparse lidar point clouds,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Glidr: Topo- logically regularized graph generative network for sparse lidar point clouds,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.092155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation da067785-f81d-427e-a463-7b9c239371f0 · outbound

This paper cites High-resolution image synthesis with latent diffusion models,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation High-resolution image synthesis with latent diffusion models,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.804380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e3cc7d6-f99d-4a06-b7d6-0ebe995cf10d · outbound

This paper cites Diffusion probabilistic models for 3d point cloud generation,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Diffusion probabilistic models for 3d point cloud generation,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.076919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b9b9ae13-49e2-4808-9d4f-8cff6ff47057 · outbound

This paper cites Denoising diffusion probabilistic models,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Denoising diffusion probabilistic models,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.809754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ec358a9-c15a-4858-b754-f29df74a3865 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject- driven generation,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Dreambooth: Fine tuning text-to-image diffusion models for subject- driven generation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.062019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7dd94cc5-3716-47a3-981e-8b671c909e39 · outbound

This paper cites Palette: Image-to-image diffusion models,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Palette: Image-to-image diffusion models,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.052849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fa5c6aa0-a915-47c3-9149-c6bf5e9d16cc · outbound

This paper cites Ml-semreg: Boosting point cloud registration with multi-level semantic consistency,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Ml-semreg: Boosting point cloud registration with multi-level semantic consistency,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.043329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 505ffcec-645b-4054-b7f9-8482d9d3ef8c · outbound

This paper cites Hemora: Unsupervised heuristic consensus sampling for robust point cloud registration,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Hemora: Unsupervised heuristic consensus sampling for robust point cloud registration,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.033810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e61dfb07-39dd-4b61-81fe-7d485c8a73bf · outbound

This paper cites MCN-SLAM: Multi-Agent Collaborative Neural SLAM with Hybrid Implicit Neural Scene Representation.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation MCN-SLAM: Multi-Agent Collaborative Neural SLAM with Hybrid Implicit Neural Scene Representation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.822329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11090cec-6c30-4fb3-a0ba-9e8acd3f607d · outbound

This paper cites Regformer: An efficient projection-aware transformer network for large-scale point cloud registration,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Regformer: An efficient projection-aware transformer network for large-scale point cloud registration,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.024865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b8397512-b3a5-41bc-96ac-537ef3b2eae5 · outbound

This paper cites Difflow3d: toward robust uncertainty-aware scene flow estimation with iterative diffusion-based refinement,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Difflow3d: toward robust uncertainty-aware scene flow estimation with iterative diffusion-based refinement,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.015914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d9a40f7d-765c-484e-837c-0484eca2eab5 · outbound

This paper cites Visual point cloud fore- casting enables scalable autonomous driving,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Visual point cloud fore- casting enables scalable autonomous driving,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:23.006522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 88a59f6b-ce14-4153-92fd-4fc5d4023975 · outbound

This paper cites Carla: An open urban driving simulator,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Carla: An open urban driving simulator,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.833563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0c47611-a2e8-47c8-be49-d076e1136e68 · outbound

This paper cites A topology layer for machine learning,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation A topology layer for machine learning,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:22.991050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4cdc6c2a-6dd5-45ae-ae57-231bc086ba83 · outbound

This paper cites A topological regularizer for classifiers via persistent homology,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation A topological regularizer for classifiers via persistent homology,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:22.981004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 91146616-a577-4dfb-ae3e-82009294e3b3 · outbound

This paper cites A topological loss function for deep-learning based image segmentation using persistent homology,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation A topological loss function for deep-learning based image segmentation using persistent homology,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:22.971695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2e9e0537-cd4e-48e6-a15e-abf06719dcf9 · outbound

This paper cites Applying Topological Persistence in Convolutional Neural Network for Music Audio Signals.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Applying Topological Persistence in Convolutional Neural Network for Music Audio Signals

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.844024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b84ce3e6-2556-4e9f-9f24-bd94113ded11 · outbound

This paper cites Learning persistent homology of 3d point clouds,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Learning persistent homology of 3d point clouds,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:22.961683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 434e9dcf-a25f-4aff-a8da-56c519172e6d · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation U-net: Convolutional networks for biomedical image segmentation,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.849854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca739234-c953-4904-8d55-7b25b15fcd81 · outbound

This paper cites Vision gnn: An image is worth graph of nodes,.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Vision gnn: An image is worth graph of nodes,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:42:22.946072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bd1079ec-35b7-45c3-8513-85692dae1a40 · outbound

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

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.855477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 88781d91-4fe3-4be4-8a86-49849386d266 · inbound

Perception Graph for Cognitive Attack Reasoning in Augmented Reality cites this paper.

Perception Graph for Cognitive Attack Reasoning in Augmented Reality TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:33:00.844831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.