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Paper Citation Record · LEDGER

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation

As of 7 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2507.18575.

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

pith.paper-citation-record.v1
2507.18575 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:35:41.341056Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

49 of 49 outbound references displayed

  • verified exact2
  • verified fuzzy36
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation deb8ddd4-0fba-49bd-b522-059bec3b262f · outbound

This paper cites A comparative study of real-time semantic segmentation for autonomous driving,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation A comparative study of real-time semantic segmentation for autonomous driving,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d4c9c399-6cda-402f-9246-de79b7d0d01b · outbound

This paper cites Mask-based panoptic lidar segmentation for autonomous driving,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Mask-based panoptic lidar segmentation for autonomous driving,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.097854Z digest=sha256:d0de584f7de10fc9d015bc0ff173ccfbd33b5eea34530892880f5e7472d09e19

Observation 718ccdf4-bdd5-4696-ba89-d50150607d66 · outbound

This paper cites Pointmoseg: Sparse tensor-based end-to-end moving-obstacle segmentation in 3-d lidar point clouds for autonomous driving,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Pointmoseg: Sparse tensor-based end-to-end moving-obstacle segmentation in 3-d lidar point clouds for autonomous driving,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation b5ddb77d-df5f-448f-935f-71b025850814 · outbound

This paper cites Epnet++: Cascade bi-directional fusion for multi-modal 3d object detection,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Epnet++: Cascade bi-directional fusion for multi-modal 3d object detection,

Reference 4

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raw_fallback, observed 2026-08-06T14:35:42.109502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.108057Z digest=sha256:5a871a0564ad43276802b508f0a2a2c2f138133a2f1443f54b720f3092fdcdfa

Observation f129ec39-acdf-4747-ba34-57b9fd0f91d2 · outbound

This paper cites Indoor semantic segmentation for robot navigat- ing on mobile,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Indoor semantic segmentation for robot navigat- ing on mobile,

Reference 5

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raw_fallback, observed 2026-08-06T14:35:42.093616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.113722Z digest=sha256:85ec3d3f7f918a5cf946618e06c77a2b9fa37d4dcdc0cf6d3d2a4398ebd8e457

Observation 2917b212-4678-4ab3-8c7b-591213ad0105 · outbound

This paper cites Multi-view incremental segmentation of 3-d point clouds for mobile robots,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Multi-view incremental segmentation of 3-d point clouds for mobile robots,

Reference 6

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raw_fallback, observed 2026-08-06T14:35:42.078561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.118711Z digest=sha256:4077985f40d560c5dc902c13565e4e1e2cc064db200af9f9a65e35433839a02b

Observation 4f0b1102-6e7f-4a7a-8c15-1e2f8e5644df · outbound

This paper cites Semantickitti: A dataset for semantic scene under- standing of lidar sequences,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Semantickitti: A dataset for semantic scene under- standing of lidar sequences,

Reference 7

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raw_fallback, observed 2026-08-06T14:35:42.062928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.124240Z digest=sha256:bee8ea9bca774e0c149c77cea9e0ac4d590b16f342c045d8251615da003cf534

Observation 43879717-cd7c-4d7d-acdc-0b9c7684136a · outbound

This paper cites Attention is all you need,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Attention is all you need,

Reference 8

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raw_fallback, observed 2026-08-06T14:35:42.047417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.129972Z digest=sha256:013401057a0ecb108d6579640f07013214916213fda48bad665feb996c913d27

Observation b53852d3-77bf-4dd5-b0a9-2708d51217e3 · outbound

This paper cites Point transformer,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Point transformer,

Reference 9

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raw_fallback, observed 2026-08-06T14:35:42.032193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.134841Z digest=sha256:3dc5c644d66a1c1a10edfe9518949f7a7dae6dc3f918e4bcee1dfcdac2e38d21

Observation 631c2bfb-4232-48b7-96c1-8db27f7bc512 · outbound

This paper cites Patchformer: An efficient point transformer with patch attention,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Patchformer: An efficient point transformer with patch attention,

Reference 10

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raw_fallback, observed 2026-08-06T14:35:42.016241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.139717Z digest=sha256:a43f4c0d1dd43b0e886a276326535c8beb8bdb26b373b284c39aefaa6fdd666f

Observation 810e0957-57a8-40af-864a-1bd2b624a40e · outbound

This paper cites Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding

Reference 11

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no resolver link, observed 2026-08-06T14:35:41.145174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.145174Z digest=sha256:647d093b9b341d25739059a76f8fea715dbdc0f4c3d360db17ceecf0d13addc6

Observation acef9686-57e2-4951-924a-e2856e0a3fb4 · outbound

This paper cites Octformer: Octree-based transformers for 3d point clouds,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Octformer: Octree-based transformers for 3d point clouds,

Reference 12

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raw_fallback, observed 2026-08-06T14:35:41.999942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.150486Z digest=sha256:f72ba9f646ed2ff3a29e65036b1c7608c4aa58c36fe4186bcca02ec987b9b387

Observation 376e8717-1569-43ab-a835-a378e6507073 · outbound

This paper cites Point transformer v2: Grouped vector attention and partition-based pooling,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Point transformer v2: Grouped vector attention and partition-based pooling,

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.984206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.155066Z digest=sha256:3b47b94bdd4a96051b10f1785b2f713bae09c0fc0863c9ecd88d69542736d840

Observation 977e3cbc-3781-4ddf-a66a-1c8634357d4f · outbound

This paper cites Point transformer v3: Simpler faster stronger,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Point transformer v3: Simpler faster stronger,

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.968041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.161272Z digest=sha256:d4a0cfa36fa2e44ef003d3c9e37ca0a8f2701857e302e6b6df8a9076a2d66a01

Observation df7cf804-a240-4954-bc49-370d168dec48 · outbound

This paper cites Fast point transformer,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Fast point transformer,

Reference 15

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raw_fallback, observed 2026-08-06T14:35:41.953107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.166101Z digest=sha256:5d97cd7085203fc7c642efa14f5befc4a1b0ca592e6028bfaf2030078aca6ad1

Observation 948e144e-250e-4582-abdc-74baf55e85ca · outbound

This paper cites Stratified transformer for 3d point cloud segmentation,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Stratified transformer for 3d point cloud segmentation,

Reference 16

Resolution
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raw_fallback, observed 2026-08-06T14:35:41.938026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.171789Z digest=sha256:80a1e22f453278ecb1386eed28848e7be8910fb17ec8a93cfad0dada028081fa

Observation b0485756-2fc7-4045-bf06-683a776c9c71 · outbound

This paper cites Spherical transformer for lidar-based 3d recognition,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Spherical transformer for lidar-based 3d recognition,

Reference 17

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raw_fallback, observed 2026-08-06T14:35:41.923109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.176660Z digest=sha256:a5362ba2cae6979576c77b199a042fe1a21b8d2246d956f7dad96b36719e39cb

Observation 02a460d8-d12b-43ec-ba4f-dc1d9f2896df · outbound

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

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 18

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no resolver link, observed 2026-08-06T14:35:41.182131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.182131Z digest=sha256:ce4a4fa928be00bc143234ff140ba28d55c411db4c882fafc120642dfb745680

Observation 705fe000-296f-4776-8429-6b54f5d80db2 · outbound

This paper cites Vision mamba: Efficient visual representation learning with bidirectional state space model,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Vision mamba: Efficient visual representation learning with bidirectional state space model,

Reference 19

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raw_fallback, observed 2026-08-06T14:35:41.907493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.187601Z digest=sha256:dd04ef212796df1f4ab4b6162231b27205051b5277ff1528b685845609bd8d4e

Observation 7a3a8db8-656a-4e42-8082-d4e2d56427d0 · outbound

This paper cites Vmamba: Visual state space model,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Vmamba: Visual state space model,

Reference 20

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raw_fallback, observed 2026-08-06T14:35:41.892459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.192536Z digest=sha256:7049532e53d756d8d535352915ee4360faea4c22a147043bc5f89dd5ecd521d6

Observation 2869a65c-c21f-4cad-85a7-4de2789fcd05 · outbound

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

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation LocalMamba: Visual State Space Model with Windowed Selective Scan

Reference 21

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no resolver link, observed 2026-08-06T14:35:41.197297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.197297Z digest=sha256:fc357b50c7ed762253022b0459982a37fc240fcf0ed8d1c67b145792c9f243b5

Observation 523e9910-7440-4ea0-979c-2bab3e480c39 · outbound

This paper cites EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba

Reference 22

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no resolver link, observed 2026-08-06T14:35:41.202881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.202881Z digest=sha256:efde501bacbed07854fd3b35e75a322a7661f730df8afbd367182524e7e09b6b

Observation 0bf9c88e-159a-4c90-8bfb-ead569fe876d · outbound

This paper cites VM-UNet: Vision Mamba UNet for Medical Image Segmentation.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation VM-UNet: Vision Mamba UNet for Medical Image Segmentation

Reference 23

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no resolver link, observed 2026-08-06T14:35:41.207934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.207934Z digest=sha256:078dde2d476fc2d33bfffb1bbf8086ed11f7a433f5156a2dd7e45fe4c4d4f84f

Observation 8ae2a6f7-7f79-42ad-b955-77015704d204 · outbound

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

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy

Reference 24

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no resolver link, observed 2026-08-06T14:35:41.213503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.213503Z digest=sha256:378b566d3ff40e302b9ce069ac7890351eb21eee087756ff3084cd88ad12516a

Observation 3db89f6d-faf2-4f6a-a158-973eab5d91a8 · outbound

This paper cites Point Cloud Mamba: Point Cloud Learning via State Space Model.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Point Cloud Mamba: Point Cloud Learning via State Space Model

Reference 25

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no resolver link, observed 2026-08-06T14:35:41.218628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.218628Z digest=sha256:b84a9868e5aa726cae0d595f439fb26779f1b2d69af12eba7fddba01fda4f57e

Observation 3ed8cbb3-ef51-48bc-afb4-6c44b806c135 · outbound

This paper cites Serialized Point Mamba: A Serialized Point Cloud Mamba Segmentation Model.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Serialized Point Mamba: A Serialized Point Cloud Mamba Segmentation Model

Reference 26

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no resolver link, observed 2026-08-06T14:35:41.223746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.223746Z digest=sha256:964749395b1ddd30e434b83e3d066653c2cc3e6171a5f6edb9acb57d2a49c49e

Observation 7da4bce5-dc36-422d-8897-391b73fce999 · outbound

This paper cites 3d semantic segmentation with submanifold sparse convolutional networks,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation 3d semantic segmentation with submanifold sparse convolutional networks,

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.877742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.229163Z digest=sha256:8e38d39d7614e7b795a88eee2613aa35477749ca29c98396142f929818a99613

Observation 5d8050ff-37f9-48d0-9204-5ec1fae23e65 · outbound

This paper cites Scannet: Richly-annotated 3d reconstructions of indoor scenes,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Scannet: Richly-annotated 3d reconstructions of indoor scenes,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.862371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.234220Z digest=sha256:66c7c32b824dc6f1585ecf82a6dab67eabffc18454bbdec602b83041ca80e967

Observation 565489d1-08ef-4012-bf14-4cb19ece1683 · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation nuscenes: A multimodal dataset for autonomous driving,

Reference 29

Resolution
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raw_fallback, observed 2026-08-06T14:35:41.847404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.238732Z digest=sha256:fd78d15135853f0709fc583a803783987a5ccd7578f9dbb83074e17c75c378ac

Observation 925d906f-e223-4092-9d51-caba5d6c1987 · outbound

This paper cites Jamba: A Hybrid Transformer-Mamba Language Model.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Jamba: A Hybrid Transformer-Mamba Language Model

Reference 30

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unresolved
no resolver link, observed 2026-08-06T14:35:41.243354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.243354Z digest=sha256:fae6b231d5a49014a477a851d51297ccbfe77cc1e128ec01da57f1b01b7ea9e2

Observation bd8daf33-e3bd-48b1-8232-ac20a49a06e4 · outbound

This paper cites MambaVision: A Hybrid Mamba-Transformer Vision Backbone.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation MambaVision: A Hybrid Mamba-Transformer Vision Backbone

Reference 31

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no resolver link, observed 2026-08-06T14:35:41.248300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.248300Z digest=sha256:ee5f70421ddf498e1ef1d1222b5bb8755918000a5ba46fd70e09c6858fa1f877

Observation 0125617c-98b2-43d3-bae2-3209cc516791 · outbound

This paper cites MAP: Unleashing Hybrid Mamba-Transformer Vision Backbone's Potential with Masked Autoregressive Pretraining.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation MAP: Unleashing Hybrid Mamba-Transformer Vision Backbone's Potential with Masked Autoregressive Pretraining

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:35:41.431779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.253163Z digest=sha256:334d411119bfe3249202954b53d310f8f5a7842a04ddfc573e8c16753d2e7e68

Observation 0a7cc978-5a2f-4e00-a518-6ca14f7ac017 · outbound

This paper cites MaskMamba: A Hybrid Mamba-Transformer Model for Masked Image Generation.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation MaskMamba: A Hybrid Mamba-Transformer Model for Masked Image Generation

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:35:41.406146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.258783Z digest=sha256:4a4c84bd1241315a58cf8934a2d42831ef546ba7b3929ae6f19813fde3ec8047

Observation 3231256e-71a1-44ca-b90b-2b9552036f46 · outbound

This paper cites Pct: Point cloud transformer,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Pct: Point cloud transformer,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.832364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.263547Z digest=sha256:eef2613044ee5bb24ecf2dab9649f9c2c3a6c681194dc22548c016f7464498fc

Observation 9e6cf212-cc3e-4b70-8af2-bbaef9c91429 · outbound

This paper cites Gaussian radar transformer for semantic segmentation in noisy radar data,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Gaussian radar transformer for semantic segmentation in noisy radar data,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.817178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.268203Z digest=sha256:0b6ee06dea5a1f67b6ce8e97e185bb5c2adc2c369da2797c3f1ae5ba4fde590b

Observation ab4ad5a5-a753-4a45-af7a-a1d268194f4e · outbound

This paper cites Transformers are ssms: Generalized models and efficient algorithms through structured state space duality,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Transformers are ssms: Generalized models and efficient algorithms through structured state space duality,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.802208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.274231Z digest=sha256:7ad45791b8628440a9f362e9538d5085d52fc92c2ed7d9afba1c7239a38ed6bd

Observation f8ced228-0406-4c5a-adb8-3787f29f2536 · outbound

This paper cites Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T14:35:41.279944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.279944Z digest=sha256:43eeff6a1d472a373ba95b76d1fe7ec893ad6e6c80e6bf9b022966ea38bd8060

Observation 54566c65-513c-4577-a066-6c0911a4d65a · outbound

This paper cites Mim-istd: Mamba-in-mamba for efficient infrared small target detection,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Mim-istd: Mamba-in-mamba for efficient infrared small target detection,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.786521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.285164Z digest=sha256:720aa181e627f6c49b17fd193a519eeac5358d04603ea6fb2bd9e3c4ff78183b

Observation c99edb32-6899-4cb7-b744-e60e05156b41 · outbound

This paper cites Omega: Efficient occlusion-aware navigation for air-ground robot in dynamic environments via state space model,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Omega: Efficient occlusion-aware navigation for air-ground robot in dynamic environments via state space model,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.771354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.290036Z digest=sha256:aec5cddc3f694f463527b07ec89a551dec097f14c6afcf82715b0a97456eb5b1

Observation 49578ddb-fa17-470d-a367-0b9bf5272547 · outbound

This paper cites Lion: Linear group rnn for 3d object detection in point clouds,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Lion: Linear group rnn for 3d object detection in point clouds,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.755426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.295628Z digest=sha256:175a68907bb9c69be170a75ee2dfe9db895b321c65cf847b168b0f7302798c98

Observation 97210143-9bf7-4536-9a20-4065a4881f6f · outbound

This paper cites 3d semantic parsing of large-scale indoor spaces,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation 3d semantic parsing of large-scale indoor spaces,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.738426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.300917Z digest=sha256:717c33d90a509e4dc1274664ea4d4b22d560744af1ef78665def338d0111dd64

Observation 9d37deea-9959-48b1-9565-b6910541342e · outbound

This paper cites Decoupled weight decay regularization,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Decoupled weight decay regularization,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.722682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.306383Z digest=sha256:0238b348136189696ab608f6b35b1876832fca551b2184c1e51e7acc6db50a7e

Observation c55d0524-ef7a-420c-8ce6-f361d0ecf6f8 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Pointnet++: Deep hierarchical feature learning on point sets in a metric space,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.707229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.311285Z digest=sha256:5f85aa3d1c076eabd88a4bebe976e97f7d5cc3232426b6304923873f86b703fe

Observation 0496f2b4-6c6f-4c79-a554-77dbee0541e0 · outbound

This paper cites 4d spatio-temporal convnets: Minkowski convolutional neural networks,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation 4d spatio-temporal convnets: Minkowski convolutional neural networks,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.690364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.316090Z digest=sha256:b43423e5b02cc515c59987697c31c377f32851a91df810e277c7f5393faac9f3

Observation ceaa1fca-a2fd-4479-bd77-833f94ac4e3e · outbound

This paper cites O-cnn: Octree-based convolutional neural networks for 3d shape analysis,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation O-cnn: Octree-based convolutional neural networks for 3d shape analysis,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.672964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.320860Z digest=sha256:9935992ba5c8d31a0adce0e45fc7fd127605dabdbcac1bd055593c5b1617d71b

Observation fb7171f2-c6f3-4f11-8071-56bc114b1a34 · outbound

This paper cites Search- ing efficient 3d architectures with sparse point-voxel convolution,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Search- ing efficient 3d architectures with sparse point-voxel convolution,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.655959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.325457Z digest=sha256:26d72bbb6e05185de2a169a2209a9dba12d027c88ce85c67a778e0a94dd36fc4

Observation 898213b7-64df-472f-bc44-ea186cc1442b · outbound

This paper cites Cylindrical and asymmetrical 3d convolution networks for lidar segmentation,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Cylindrical and asymmetrical 3d convolution networks for lidar segmentation,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.640343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.330561Z digest=sha256:f575ae9190e1e5a3860b66cd019f4d07e2166e250217f4c79f83ae6f7f8aaaa2

Observation a771f264-fcb8-4eee-b853-9f99ae715044 · outbound

This paper cites 2-s3net: Attentive feature fusion with adaptive feature selection for sparse semantic segmentation network,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation 2-s3net: Attentive feature fusion with adaptive feature selection for sparse semantic segmentation network,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.624582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.335936Z digest=sha256:e229a1b57eb62290aac329d0d3899ecc42221009727b88bc8ab2beecf7a47286

Observation d135b47d-8609-46d5-b5d4-e309487c9e3a · outbound

This paper cites Pointnext: Revisiting pointnet++ with improved training and scaling strategies,.

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation Pointnext: Revisiting pointnet++ with improved training and scaling strategies,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:35:41.607727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:35:41.341056Z digest=sha256:17618e52751f1a6517a0f3f1597428cb2f1d58c1f965b0a4cc4a37f4fa4aa5ed

Pith citing papers

No inbound Pith citation observations are available.