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Paper Citation Record · LEDGER

HybridTM: Combining Transformer and Mamba for 3D Semantic Segmentation

As of 10 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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+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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raw_fallback, observed 2026-08-06T14:35:42.141467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.097854Z digest=sha256:3b4b914fe20bc5a8f32c25349cde4621cc24d1bc7cdfac8415ae4280de826378

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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raw_fallback, observed 2026-08-06T14:35:42.126064Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T14:35:41.102816Z digest=sha256:86e1842d8f0ccd40cf27e6e8bf1aa836e4bdf0e4c76aeca4ff159ca6a2aaf6ae

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.108057Z digest=sha256:3d58d961af35fa3ca1d2dd2c5cf409a7d72cbf340493000ae30ca921ca4573a7

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.113722Z digest=sha256:a2bfc7b766d7fc5254057c8deb208e42dc388c09c60a01dada32f1729d51c2c0

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.118711Z digest=sha256:68acbad961822e15e282d43bedcfcd05d83b0c0c9264f29763adebcda1eb227e

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.124240Z digest=sha256:37b6aad22bc85bd29442afae610059e852c2971214f6a8bccebbb43001573891

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.129972Z digest=sha256:4539e934011002c2d62051005c13fc9609de630e10f54fd17bd7d06ab066219a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.134841Z digest=sha256:c582214a550f00165e2b6ad6b6976f6383fa003ff9a5bd8667bd902ed0931988

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.139717Z digest=sha256:5061da73f732106cd232cb48a39cc48744c1e1f9386755368aa534349fb80b52

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:d983c7ac8f13d693fc772f60d3ab490181a862102e6b6aafea54b26a380eb96b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.150486Z digest=sha256:6f38c5d693e635a53ea496e24944db290c1fe90b5aef5c918ec47a3701f27893

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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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.155066Z digest=sha256:51b29f7b0622e59c9a6434d75c80cb02eb86916de844e102beb853cdaaaaa6ef

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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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.161272Z digest=sha256:d6c2e0e931fffacda225c62e52dc2cc98979101f37e9fbce43c603c466097ded

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.166101Z digest=sha256:b0a5fdc7985fb3f23843a44dcc0f9403380cb0682e38ecfbb1815974ba916b65

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.171789Z digest=sha256:5ee4c73d0931a880a701e20ddfbd593ddcf484e8b5605e424904884b47cc3bd8

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.176660Z digest=sha256:b778f72edada5107cc5287e1f14fe545d9c0bd57c14d93aed6636f4bc38a87ff

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:b6feef595918663a30370352b4aba64ab5b2d5514ecb1bd54e92603d99cd9a45

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.187601Z digest=sha256:e195a7d1729939d514aaf24940542187fa0e22fd1979d66303e1a1f534800ff8

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.192536Z digest=sha256:d6e8127efdbe6e93312fa718060401f9cf9fc915012b001a983e3e93a1f95aa7

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:c77764d47f346fcda19988b3839f0c9b4c7fdb15a2dc92b6cff18fec45e4b950

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.202881Z digest=sha256:3b389fa5ff5914ce20d3e425be097a1d0649318d738646735054097d532456dc

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=sha256:2e64e263a3750dc574f9ddcee2bdd18b08b44c428b30659eae28b5ca13e9f7e0

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=sha256:140f4d1e5a47abda93e054ec55c7b10968a7b86cac25f6bd824f617b769f3c8b

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=sha256:6bbb662e42b4d27a9bb3ee48af282b0a6733b7308e04164cfe0e7fe75145a90f

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:35:41.223746Z digest=sha256:807977681693f030291a2b1df5505786935be611084127a0051cbec533b96238

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.229163Z digest=sha256:612d7216af83e98de90e20d5358374dac82517861bba4c4eb3985170b124768c

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.234220Z digest=sha256:0eadaf4714b7bf513a0e1a1de7c67c62d1c3d0daca1a11b2cdb6cdaf3cbc1078

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.238732Z digest=sha256:d17a6c4213db1dd51664f5083f19519bb315fd50b90a8eb4b01aaba47ea70606

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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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:a7b67f0c05e7268e5f02ff51fa958c21994a99948859cc96226eaa76d424a489

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=sha256:212611870f1ae7237e13e8db8f7cf7fa01f100bf2704e552db2a3eca84a04b4d

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.253163Z digest=sha256:617bf29bd2eea059b1bcebf3687b6e600c5f43e91a5361732f5473906b731aae

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.258783Z digest=sha256:f2d2133e1debf3471a3223748eb07b173fae568b15df0f17c978d7822f41d9ab

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.263547Z digest=sha256:e71732bb342ba487f1a51fafa9891f155ffe7da74a87aeb23bc9e230c9b1a6ad

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.268203Z digest=sha256:cff6372e5793933823033ad0514d62b90035bb6dc9c6c7664d2bf3ac3f2bb9ce

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.274231Z digest=sha256:49e2d9282040031fc95c634fbdb0137d59dacff8496f8b453caaf100343703c5

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=sha256:28041e54da05016ba5b4a2fdf9bd68020d6d11c88762c799d513c078a6f7b34b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.285164Z digest=sha256:d16887a1a41ebb9e2d1f7aabde44abb313f16f934a854d93b255eab91d1976a6

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.290036Z digest=sha256:ff796258d2de8e3c10680170ba262229ba66f2ef6b7ee6b046f9f58a790033a0

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.295628Z digest=sha256:48509b19731a04c5695301892ad542a477d1c2d120fe7081b41d06ed09cd2ec7

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.300917Z digest=sha256:154a37bc4dba8a9a5c097c8ea1e6292791016f1e4e1e54c0d2817904f2d92e31

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.306383Z digest=sha256:0f0e2729199b6c8f60d7e9e15e5050d1cc47a31a7dc11c5013af2649c3a1a544

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.311285Z digest=sha256:a4983014c8d8bde9a3c140aab32ac88d3650be59346cb7093edba96b0fd81ccc

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.316090Z digest=sha256:4e718bb69c1af52d614319038514235c35c3e83b25b40ba9d4b8ee243c8e2e13

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.320860Z digest=sha256:4a7cb63cb2a54be2cfdbe8a978977e5c5106a4be18c0179cf96c5cf577d69410

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.325457Z digest=sha256:41165059951f250a251211e8cc005b9b5aa1b8fb55c4cb9dd04c6fd199901c78

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.330561Z digest=sha256:0da223635c86db8b76d0d1341b4096205dc8eb1c65fd33c3b5ccaea022e992e3

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.335936Z digest=sha256:bd7e2f672b8ced10e855501d76d75aa13727199b7355282450629dac3ee724b5

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T14:35:41.341056Z digest=sha256:4d1c4dd1cf61c45228ae8e64d01ccc6a9fa8c4c144420bb89e407b1fe3270e18

Pith citing papers

No inbound Pith citation observations are available.