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Paper Citation Record · LEDGER

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings

As of 5 August 2026, this Paper Citation Record lists 100 of 111 outbound references and 1 inbound Pith citation observation for arXiv:2605.10706.

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

pith.paper-citation-record.v1
2605.10706 v1

Coverage vector

measured 100 of 111 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-12T05:25:19.181337Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T17:23:26.151875Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

100 of 111 outbound references displayed

  • verified exact7
  • verified fuzzy91
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation e17d7e73-234e-4264-b8ab-6100392617f4 · outbound

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

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings 3d semantic parsing of large-scale indoor spaces

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.829584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Observation f026fd73-272c-4ea5-899b-32971ecf6a79 · outbound

This paper cites Point Convolutional Neural Networks by Extension Operators.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Point Convolutional Neural Networks by Extension Operators

Reference 2

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verified exact
arxiv_id, observed 2026-05-12T05:26:24.085639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Observation ec9916ab-8d70-4254-8757-5060079bc15b · outbound

This paper cites Multimae: Multi-modal multi-task masked autoencoders.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Multimae: Multi-modal multi-task masked autoencoders

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.822849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:41378364ce70b1b5127d9fbb99a6516e7a0928429e6d90a9fe188c3a89818455

Observation a0b870fb-2bab-4b42-b6fb-cc9cb766bafe · outbound

This paper cites Longformer: The Long-Document Transformer.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Longformer: The Long-Document Transformer

Reference 4

Resolution
metadata mismatch
local_arxiv, observed 2026-05-12T05:26:24.093069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:e35dc7503f79bd28d3512a2ebbddd718ad75253dceff3ea835ab45be96c6325f

Observation b9801d25-e6bb-4c05-81c6-a541af055f39 · outbound

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

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings nuscenes: A multimodal dataset for autonomous driving

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.840170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:c14b86ec649165c6a687f1850673c0a14b7b30cf9daca7ea91e97604cd2b2106

Observation 80302894-b693-4be7-83ba-f5294f681713 · outbound

This paper cites Shapeconv: Shape-aware convolutional layer for indoor rgb-d semantic segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Shapeconv: Shape-aware convolutional layer for indoor rgb-d semantic segmentation

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.826174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:4c1e4a8e2bcea8bf9fca5f8ae0389c4a49d7aeabf5f7b4b270d01cdae3d409fc

Observation c5b92366-5b10-486f-9b2f-41259ea377f1 · outbound

This paper cites Spatial information guided convolution for real-time rgbd semantic segmentation.IEEE Transactions on Image Processing, 30:2313–2324.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Spatial information guided convolution for real-time rgbd semantic segmentation.IEEE Transactions on Image Processing, 30:2313–2324

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.843469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:dee46bf7c1a43a5dccfad66616da5bcc430590126b356871e14190b7db692f54

Observation 598cf6bc-3379-459d-9fe7-856032dcd4a9 · outbound

This paper cites Bi-directional cross-modality feature propagation with separation-and-aggregation gate for rgb-d semantic segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Bi-directional cross-modality feature propagation with separation-and-aggregation gate for rgb-d semantic segmentation

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.833213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:c1b20716676eab0b8b936ecdacb01301b2985526991f2d858c89bdd5c549a655

Observation 4129399c-55e2-44f7-9d97-63d529a055f9 · outbound

This paper cites LargeKernel3D: Scaling up Kernels in 3D Sparse CNNs.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings LargeKernel3D: Scaling up Kernels in 3D Sparse CNNs

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:26:24.072977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:cc72f4445e557fd59b8c7b42853f2412ffbe16df9ba96d957744f21400f51180

Observation 4ed03fa7-f3d3-4860-9dc6-56236170963c · outbound

This paper cites A unified point- based framework for 3d segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings A unified point- based framework for 3d segmentation

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.846918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:6544c085f7358e82362f18a42dbef5bb05985a6abd56ed42b75c7963f8eb4c2a

Observation 35757edc-aad2-4a2e-a038-8274f53070d0 · outbound

This paper cites From block-toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked transformers.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings From block-toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked transformers

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.836493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:7fa3972d2776930f21d469054a66211166487684590316fc37b7dbd4f5d557e4

Observation f7f2a44f-1f43-44f3-a788-8a84ee7eccb0 · outbound

This paper cites Rethinking attention with performers.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Rethinking attention with performers

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.660053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:0bcaa2045bf59b63c1bcc72540c29e472b6cc92464f75e0e5503188dbb338d77

Observation d0cec2c3-1b19-4044-917d-502a298e1178 · outbound

This paper cites Fast tree-field integra- tors: From low displacement rank to topological transformers.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Fast tree-field integra- tors: From low displacement rank to topological transformers

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.669476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:dfc01eaffce53d558e40f394c94409fb61b8aced05be4618760cc8f25644445a

Observation 74f2ab04-b33e-43f7-a604-944e8cad9325 · outbound

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

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings 4d spatio-temporal convnets: Minkowski convolutional neural networks

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.686249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:a60c3367c6205c775c801bdb970f9dc11222624b9944b25d30d12f586bba1f1a

Observation 99a9a0c6-b90b-4cfd-98fb-edc618c2f0f6 · outbound

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

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Scannet: Richly-annotated 3d reconstructions of indoor scenes

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.708516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:9e8d46ddee7b1aeadbdd08bd02ca846624d028d21fcf8be20d48cd40226a38e5

Observation 6181f4e7-bf31-4e82-8526-84e4922c22c3 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-05-12T05:26:24.024617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:fd88bd689e8a140a61e9651bd2740b3a530c826fcb145f6ed59d90868b38b472

Observation 102b2081-3244-4d19-8333-b6951bc32b53 · outbound

This paper cites Fast kernel methods: Sobolev, physics-informed, and additive models.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Fast kernel methods: Sobolev, physics-informed, and additive models

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.812747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:fa79039d16c31ebdc45a5603b4094c801ef08709964052724caf22d47ba03af6

Observation 5e9eaa7e-4741-4407-a7dd-9a723dc44340 · outbound

This paper cites Asymformer: Asymmetrical cross-modal representation learning for mobile platform real-time rgb-d se- mantic segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Asymformer: Asymmetrical cross-modal representation learning for mobile platform real-time rgb-d se- mantic segmentation

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.797886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:00890473ce9c5212ed27ce9a6e66377a06e6cea7a1d300e86fccb6f41cb984c5

Observation 550d0912-7f44-4055-a27d-cf663cf506a9 · outbound

This paper cites American Mathematical Soc.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings American Mathematical Soc

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.774456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:64b187f9509837fc3a2c0b3f76703720f3082deffb7118c6d320337e5fe042f9

Observation 45a5cd45-5b9f-49f4-8551-28660c2d98f1 · outbound

This paper cites Omnivore: A single model for many visual modalities.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Omnivore: A single model for many visual modalities

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.764700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:a900faaf94c800ec3ec5569cc0b74f3e68edbcabc9a5109c60f4e11f82098806

Observation d4061575-af44-490d-a8b0-27e83045707f · outbound

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

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings 3d semantic segmentation with submanifold sparse convolutional networks

Reference 21

Resolution
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raw_fallback, observed 2026-05-12T11:21:31.788069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:efd1e7420d265b66098128b9f83cd6eccdc5b52cc0ea670547bd0aa3757bd80a

Observation 83213618-7939-4401-9c80-9cb860b4f599 · outbound

This paper cites Accelerating the nonuniform fast fourier transform.SIAM Review, 46(3):443–454.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Accelerating the nonuniform fast fourier transform.SIAM Review, 46(3):443–454

Reference 22

Resolution
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raw_fallback, observed 2026-05-12T11:21:31.816688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:3a080bf0bce2c7f4af3ebba36ab1f2d5b62001c54c4f55d6106db01cb4fe8236

Observation 711769c2-326f-4260-9f69-1d14d5c7e8e4 · outbound

This paper cites Martin, and Shi-Min Hu.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Martin, and Shi-Min Hu

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.734502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:0ceba7797399d3eacd8a826d311ab0cbdc5ac69d29a768f94633eb4ac5e79955

Observation 414369c0-e02d-4b84-8058-412feb5d0ac2 · outbound

This paper cites Learning rich features from rgb-d images for object detection and segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Learning rich features from rgb-d images for object detection and segmentation

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.741098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:353f80523b38c2195acfcb83c848dc9a24be39fbec65a5e17e790d23f5667cec

Observation b2e8fecb-8537-4721-98d6-7aff54c12c2a · outbound

This paper cites Deberta: Decoding-enhanced bert with disentangled attention.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Deberta: Decoding-enhanced bert with disentangled attention

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.732443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:33880de6a732297659d7ae403cd549aa1a5bd2bf9810d969f04de544f54f6ad0

Observation b449a578-4764-4b39-a91a-b2797286ba30 · outbound

This paper cites Point-to-voxel knowledge distillation for lidar semantic segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Point-to-voxel knowledge distillation for lidar semantic segmentation

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.727577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:c8080839c176f20fea616fb2efcebc131810091fe30adeb0b4f7cc140b5e9310

Observation 7f4ea39b-f4dd-4ab3-8990-e1d0a2cc440c · outbound

This paper cites Acnet: Attention based network to exploit complementary features for rgbd semantic segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Acnet: Attention based network to exploit complementary features for rgbd semantic segmentation

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.730053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:fceeddaf1ff015c33bd18fda9435330146c8a2ca3bca8410530f4a1175e0d740

Observation a38593d8-d08f-47c8-8c37-3ff78cc929b7 · outbound

This paper cites Fourier position embedding: enhancing atten- tion’s periodic extension for length generalization.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Fourier position embedding: enhancing atten- tion’s periodic extension for length generalization

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.683515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:fc96a6754a83976a71be881f246848d0699241ec66a96aeca4021df91e5a0598

Observation 157071bf-4987-4b20-b50a-161c588f053c · outbound

This paper cites Hierarchical point-edge interaction network for point cloud semantic segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Hierarchical point-edge interaction network for point cloud semantic segmentation

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.711289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:b2a07c0e61f2fdb993637c2c00a9ea83f47fed18085f2284d2a2f682c59db602

Observation 1648d094-a5fc-41f5-bac7-641f8c01b4ec · outbound

This paper cites Transformers are rnns: fast autoregressive transformers with linear attention.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Transformers are rnns: fast autoregressive transformers with linear attention

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.758403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:bd9b9c500222772326aaa710726dd27df81665e5ec5ae84e46e9c4d917d9b4b9

Observation 1845b759-ea63-438a-909d-bbac0d612fd0 · outbound

This paper cites Reformer: The efficient transformer.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Reformer: The efficient transformer

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.751969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:bd57f9c2f20fc0f4b3ec714533cc1837084ea767b36c3f1b6aa2ba9e5f387a6e

Observation b02ec138-d15b-4c87-bd25-21a7d26f0881 · outbound

This paper cites Rethinking range view representation for lidar segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Rethinking range view representation for lidar segmentation

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.819730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:e949814946bf22465a45723071558d44b6ae3a3bb0aebd1a55e6825ef0696859

Observation bf2c9ee1-b3a7-4c49-94df-c6f741965bd3 · outbound

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

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Spherical transformer for lidar-based 3d recognition

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.630777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:70ed62093299c44bac8862657df9a979aeada5a6b43e94150040ecdc6c7146a9

Observation bf52a95d-f37a-4b01-953a-1c5f98bc043a · outbound

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

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Stratified transformer for 3d point cloud segmentation

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.604567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:bb23385fb38e9f06c6e1e1f4bca531524787547ce3371cb115479bd20d83ebf8

Observation c0484989-e704-47dd-af02-0105838c668e · outbound

This paper cites Large-scale point cloud semantic segmentation with superpoint graphs.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Large-scale point cloud semantic segmentation with superpoint graphs

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.784911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:cb7d337c33e887d3dae3e34213dd1f79bcf2f1618da0132f4f8f3550ffb185a3

Observation 8d8929dc-8e2a-45f2-b2c2-6abf6df7f393 · outbound

This paper cites Pointgrid: A deep network for 3d shape understanding.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Pointgrid: A deep network for 3d shape understanding

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.705875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:4719952c74f8939bc24de57acef09a2705f6f71a0136bf1ce76830c2f35b05c6

Observation e7fa03f5-cd4d-4896-ac20-ca87273044ec · outbound

This paper cites Seggcn: Efficient 3d point cloud segmentation with fuzzy spherical kernel.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Seggcn: Efficient 3d point cloud segmentation with fuzzy spherical kernel

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.553172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:820f5ccb4371f659a9c029b45b8b716d1a944625dd4475aa6bcd5f237d7e83f6

Observation 7c34d8ea-78fc-4c47-9bac-ad16866eed2f · outbound

This paper cites Pointcnn: Convolution on x-transformed points.Advances in neural information processing systems, 31.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Pointcnn: Convolution on x-transformed points.Advances in neural information processing systems, 31

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.602020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:a4e20efdeeb8272e8b7bb0de8b3f2bfcf7e3b00456f9f459cb3f9ac501ec3e61

Observation bcdcf909-a2d9-4e57-9726-49d229ba5092 · outbound

This paper cites Pamba: enhancing global interaction in point clouds via state space model.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Pamba: enhancing global interaction in point clouds via state space model

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.599428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:eb3b1b5ea599145f2011a874e518fad46f6957bf432a06d5000e25f5f996c2dd

Observation 6674da57-ccfd-4ba6-bd7e-7f5658c22a58 · outbound

This paper cites Pointmamba: A simple state space model for point cloud analysis.Advances in neural information processing systems, 37:32653–32677.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Pointmamba: A simple state space model for point cloud analysis.Advances in neural information processing systems, 37:32653–32677

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.666546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:6dc2b1669d967716e188907493f2b22ecffc38ca72118f90fa566c730534f9cc

Observation 92400f1b-0218-4973-be92-a467dab2451b · outbound

This paper cites Meta architecture for point cloud analysis.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Meta architecture for point cloud analysis

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.672645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:0cc429a2e8bd69a1599e0cf29e88b3e9b0cb7d47cd01e452cc1d6499992fdaff

Observation cc0208f2-cfd8-44cd-aedc-b08a3a1d4870 · outbound

This paper cites Masked discrimination for self-supervised learning on point clouds.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Masked discrimination for self-supervised learning on point clouds

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.656579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:a64311f985691a00bd926f4586f4727b4af2cdf52be3ba77256d866b1a8667e9

Observation 319bc936-1934-44a1-ba6c-2513006fc32a · outbound

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

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:26:24.029470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:b1328c5460ae5d177b1dbc8317ff0d962ce183e0055fbc2ecdaf1d4f14c4bfb8

Observation ac856287-4639-4de1-8557-34a7ccf6c0c4 · outbound

This paper cites Point2sequence: Learning the shape representation of 3d point clouds with an attention-based sequence to sequence network.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Point2sequence: Learning the shape representation of 3d point clouds with an attention-based sequence to sequence network

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.714233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:62c0f89421596f37f8dfe1518ec660a8f76faf8e1500967cb35bca705c1f0b7d

Observation b3b22b10-48bc-4d07-af84-d859316fed02 · outbound

This paper cites Relation-shape convolutional neural network for point cloud analysis.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Relation-shape convolutional neural network for point cloud analysis

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.768181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:2d0a753caf455a64c1a3c2e1bd070383bca517b862daad561287c12a90fb6d3c

Observation 236488dd-0b65-4971-b111-83ca63aa66e0 · outbound

This paper cites Multi-space alignments towards universal lidar segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Multi-space alignments towards universal lidar segmentation

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.663131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:1ff6843917d1e1ccd1c540f61950757bcedbee3f0b72bd37f60538c3ac1280d3

Observation 02e0d1e1-0628-47d6-9a57-f42f10ac09f8 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Swin transformer: Hierarchical vision transformer using shifted windows

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.617930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:4f68da018f1f34a776f4dab0072d1c966d01e9b3df2ab54177fc940b1b46e0ff

Observation 8fbbd184-f1a4-4828-8c02-240879438564 · outbound

This paper cites Transformers in 3D Point Clouds: A Survey.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Transformers in 3D Point Clouds: A Survey

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:26:24.051379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:044b8807a9d1adf1aae3a77d68dfd0a8f422bc5eb3b410e414700a4f3078381a

Observation 0076c983-24d3-4ec3-91b9-a5c9b15375b5 · outbound

This paper cites Stable, fast and accurate: Kernelized attention with relative positional encoding.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Stable, fast and accurate: Kernelized attention with relative positional encoding

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.650191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:32cd584ae76e34a0fffa6c9176a00f914f275d2c43f8a4691175d0060e3e47c1

Observation a57a68f6-1c64-423f-aac2-35f318468e64 · outbound

This paper cites Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:26:24.061914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:2943b7fc54c25e8d288d21bc85d899eb1685e58d2f77593a0106ec546ff947ea

Observation 33ad24c6-2534-4615-a06e-0e0376cfe093 · outbound

This paper cites Indoor segmentation and support inference from rgbd images.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Indoor segmentation and support inference from rgbd images

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.633689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:2ebb14dd2465e8eeb79b282c7cfaee5abb2ca85fb7845354dc10b435333fec69

Observation 8b0c48a3-0c95-4976-82f7-7d2a70f7af86 · outbound

This paper cites Masked autoencoders for 3d point cloud self-supervised learning.World Scientific Annual Review of Artificial Intelligence, 1:2440001.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Masked autoencoders for 3d point cloud self-supervised learning.World Scientific Annual Review of Artificial Intelligence, 1:2440001

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.644420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:3d620140e48bf0855a108e700f597fbac21186977cd25ee1f07ba3abdaae085b

Observation 411761af-39cd-47a0-afaa-f868bf65c37c · outbound

This paper cites Oa-cnns: Omni-adaptive sparse cnns for 3d semantic segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Oa-cnns: Omni-adaptive sparse cnns for 3d semantic segmentation

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.636909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:3f4d885ff65ca02acce067a274b01659d5fc7b3979f3e87cf93ab0920a07af68

Observation 5b612b32-980d-4444-a441-ebfd8cedb23c · outbound

This paper cites Pointcept: A codebase for point cloud perception research.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Pointcept: A codebase for point cloud perception research

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.610050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:9f62dd0b436958ad89b110403fda673f2f90ff74504cf4f40d1ad74aaefa4dd1

Observation 7cc19d77-2a92-4aa5-90f9-902b77f141f5 · outbound

This paper cites Train short, test long: Attention with linear biases enables input length extrapolation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Train short, test long: Attention with linear biases enables input length extrapolation

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.805435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:b85e14e63cafbb3bc774652d3ff62f02a5bd11b62149d6c0379f40195c22bd54

Observation cddb1f87-f058-437b-8844-b931b6c47de8 · outbound

This paper cites Qi, Hao Su, Kaichun Mo, and Leonidas J.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Qi, Hao Su, Kaichun Mo, and Leonidas J

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.576303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:6f169c5ced10ebc80b6b037906590487a1c613d85a952a4c333eca5fdaeb4835

Observation 0200186f-1dca-4b6b-a7ad-2e4252580fa8 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space.Advances in neural information processing systems, 30.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Pointnet++: Deep hierarchical feature learning on point sets in a metric space.Advances in neural information processing systems, 30

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.746325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:869369fa186d1c2d833419f4ca3cedcabe8cd472d9298bb5b8f7a854c1341f8c

Observation 2620fb77-eb39-4ba3-9589-9ab748d0d330 · outbound

This paper cites Pointnext: Revisiting pointnet++ with improved training and scaling strategies.Advances in neural information processing systems, 35:23192–23204.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Pointnext: Revisiting pointnet++ with improved training and scaling strategies.Advances in neural information processing systems, 35:23192–23204

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.720109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:0cd1556d6e49c1b70f5b31e429a23be5a2e02659bdcb17c82cf38774e02bf9b9

Observation fdb00e1a-ad79-46d1-8b2c-95ad087fe1fa · outbound

This paper cites an unresolved cited work.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-05-12T11:21:31.794217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:6c3cf42e616a68b4275ef248d0f6762451f99c7683686076b66905b7adb53490

Observation 0901e746-ce18-4de7-b7ac-84f4f213c73f · outbound

This paper cites Turner, René Wagner, Adrian Weller, and Krzysztof Marcin Choromanski.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Turner, René Wagner, Adrian Weller, and Krzysztof Marcin Choromanski

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.550240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:370cf54d2ac9dbbda613eee34927a889e566b5cf86688d7bd8aacc1f7f72c8f2

Observation 3bd1fab8-5556-4504-88d2-dd2fab2fcc46 · outbound

This paper cites Efficient 3d semantic segmentation with su- perpoint transformer.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Efficient 3d semantic segmentation with su- perpoint transformer

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.625780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:29913b72adfc39fd88667c4f678ddc8fe5e1933a60b593cbb80a90f8013e5958

Observation f682a6ce-d5a9-4096-8c3a-6763d939ed32 · outbound

This paper cites Language-grounded indoor 3d semantic segmentation in the wild.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Language-grounded indoor 3d semantic segmentation in the wild

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.771418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:6af6950002f3bcffe72e800f8b0c74c3af72521b6495ac6fda72f5781932f266

Observation 87833ebc-687e-4818-9268-1e690545ef1f · outbound

This paper cites Gritsenko, Matthias Minderer, Dmitry Kalashnikov, Jonathan Tompson, Vikas Sindhwani, and Krzysztof Marcin Choromanski.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Gritsenko, Matthias Minderer, Dmitry Kalashnikov, Jonathan Tompson, Vikas Sindhwani, and Krzysztof Marcin Choromanski

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.801014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:3fa224768b5cfe51ff4612d1054a2ee52bf482e44a4fdbaf67e7e1998bc3d649

Observation 5f917a67-b94b-4ee6-bbf1-0d58e46cc0f6 · outbound

This paper cites Efficient multi-task rgb-d scene analysis for indoor environments.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Efficient multi-task rgb-d scene analysis for indoor environments

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.556104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:5042f2799eeebef5752ccaca3b4262153f1324a6b61ca4a7b0b4f12b0f7a54f9

Observation 57a28055-f2cf-4a03-92d9-1d5f53df3e48 · outbound

This paper cites Efficient rgb-d semantic segmentation for indoor scene analysis.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Efficient rgb-d semantic segmentation for indoor scene analysis

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.738425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:2ecf2bcbdb50b1d802ad307de41789065366ff48c5ca605dfc55d83c4f88a57a

Observation 9d53da78-10c4-4756-a0de-18a08cfca430 · outbound

This paper cites Self-attention with relative position representations.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Self-attention with relative position representations

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.743618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:c84e44e29bb091a882b92d9ce17359393abff2c0ba57d4b8435ee42056931558

Observation 381aca78-a025-436e-b76c-c7014321fe8d · outbound

This paper cites Sun rgb-d: A rgb-d scene under- standing benchmark suite.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Sun rgb-d: A rgb-d scene under- standing benchmark suite

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.754965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:e0f1400009e1f63b850a2b611681139261420ba761cf09938cbe205b4055ea23

Observation 3c7c3db4-8482-437c-acac-c430077e2f83 · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.Neurocomput., 568(C), February 2024.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Roformer: Enhanced transformer with rotary position embedding.Neurocomput., 568(C), February 2024

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.749042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:54a16cd2a3020b4de0419ef7eb03e13baffda76198033a2518ec9274bd5feed3

Observation b6f808a7-f71a-4fed-a667-270f3f98b532 · outbound

This paper cites Searching efficient 3d architectures with sparse point-voxel convolution.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Searching efficient 3d architectures with sparse point-voxel convolution

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.761541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:bc76ba335cfff5a8265809480ac8fb3b351da8baec054efab953172158faa4e3

Observation d33c3e8c-770f-430c-9757-fdee85119b51 · outbound

This paper cites Tangent convolutions for dense prediction in 3d.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Tangent convolutions for dense prediction in 3d

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.628250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:05d56c55f3a1638d4088e9f773027e18fb10eed3559ad2c3e99208fdd76da8e5

Observation a2854725-7889-4927-9397-9b00b2b96695 · outbound

This paper cites Segcloud: Semantic segmentation of 3d point clouds.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Segcloud: Semantic segmentation of 3d point clouds

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.703156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:9dac090f2609216f0fe04bba7e4b1358f4ecbc304871cfb803e4904956ac3402

Observation b91d66f3-f44d-419c-9225-ea2ae1f3a881 · outbound

This paper cites Kpconv: Flexible and deformable convolution for point clouds.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Kpconv: Flexible and deformable convolution for point clouds

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.777855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:ce658d1282e1af15ddf5b96492b2fef2a67e05a777e49773f43c110b403136ff

Observation ebc8dcc5-a613-45cc-9c41-98840517c647 · outbound

This paper cites Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.615401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:5ba52132387102017179f61af8afddd0a45b96b57c88423a1d3554af811e0f10

Observation b1b55f92-146a-4248-9c70-bbeddf185b58 · outbound

This paper cites Gomez, Łukasz Kaiser, and Illia Polosukhin.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Gomez, Łukasz Kaiser, and Illia Polosukhin

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.612595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:fd45b20f50c1126d68b1fc141d6e84187e329cc7337aa3cf3fd57e984a4f8f21

Observation 5e789a47-aedb-423a-ac5e-70e0a7ee00a9 · outbound

This paper cites Graph attention convo- lution for point cloud semantic segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Graph attention convo- lution for point cloud semantic segmentation

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.639548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:019a33348fb997128ba7b13d40d4c112ce2c1d8edf23ad1bc8aa148ac9bd7530

Observation 8081e231-9e9f-42cf-8c57-71aae980f3dd · outbound

This paper cites Octformer: Octree-based transformers for 3d point clouds.ACM Transac- tions on Graphics (TOG), 42(4):1–11.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Octformer: Octree-based transformers for 3d point clouds.ACM Transac- tions on Graphics (TOG), 42(4):1–11

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.623226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:630b04fbedc4169132c37607f0983cc16cb1590e5422e48b541393af37e5f91c

Observation 9d460081-ff35-43d6-8847-f52bc8893a65 · outbound

This paper cites Deep parametric continuous convolutional neural networks.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Deep parametric continuous convolutional neural networks

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.647092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:47589cc29105ea98843abf04965d4924b56aa073f5b7b5b2597286a7d6cab907

Observation dec7c5b0-a7cc-4bb4-b4dd-218141eb4fa8 · outbound

This paper cites Multimodal token fusion for vision transformers.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Multimodal token fusion for vision transformers

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.725016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:669b9cb974d85b29ce43b89147de3b815143ca0c8873db0609d759b62b954764

Observation db42266f-43a6-44a7-b236-604dc26ff656 · outbound

This paper cites Deep multimodal fusion by channel exchanging.Advances in neural information processing systems, 33:4835–4845.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Deep multimodal fusion by channel exchanging.Advances in neural information processing systems, 33:4835–4845

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.695192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:071b1573b6bf40d9cf54d1490e9ccfa8419d7a75a3c0e9b3de9144d03000f961

Observation 55d368ea-e4d0-4646-9295-462c0f482f1f · outbound

This paper cites Sarma, Michael M.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Sarma, Michael M

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.675181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:35893accdff9a5b20830d4d32dc338fcd177b32d37f1ebffd8b0403f910d619b

Observation d9e2cd38-5e84-4d22-861f-b99b5269a8f0 · outbound

This paper cites Pointconvformer: Revenge of the point-based convolu- tion.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Pointconvformer: Revenge of the point-based convolu- tion

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.689335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:44224ce4f78e4b8aa160e3e15e2bf0c9ee1ff784250de019af3ff9c7eed2b287

Observation c8ae81ae-152c-48a3-bce9-764f1b740123 · outbound

This paper cites Pointconv: Deep convolutional networks on 3d point clouds.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Pointconv: Deep convolutional networks on 3d point clouds

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.717243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:d6f630dc7fbaf0bc199d8f4b3a3a2ff00e04016d5bd5527e90c20049fb16b77b

Observation e9d3451f-b81e-47e0-ac15-717eb0fbe684 · outbound

This paper cites Point transformer v3: Simpler faster stronger.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Point transformer v3: Simpler faster stronger

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.781485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:83ee25c99d0cb1db864317b994269ff6d694a87db88d6fd9463bbe52ca0dceb6

Observation 45552188-7b44-45db-ae8a-9288c756bf22 · outbound

This paper cites Point transformer v2: Grouped vector attention and partition-based pooling.Advances in Neural Information Processing Systems, 35:33330–33342.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Point transformer v2: Grouped vector attention and partition-based pooling.Advances in Neural Information Processing Systems, 35:33330–33342

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.596268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:1af10baa9ec5d4cef57705546c53b172baa0173d7adfda4244cd5a400be89c9f

Observation b348bddd-0a27-499d-ab7f-bcc0535e2d87 · outbound

This paper cites Towards large-scale 3d representation learning with multi-dataset point prompt training.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Towards large-scale 3d representation learning with multi-dataset point prompt training

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.546923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:54d767013403d74036567ebbbcd7e11de793c5165b9d9e0860ec93efce44208e

Observation ab10ceb8-a855-4c5f-8adb-aafbea2dcd78 · outbound

This paper cites 3d shapenets: A deep representation for volumetric shapes.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings 3d shapenets: A deep representation for volumetric shapes

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.722578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:6d320a330a474460cf323e8e886680c021c8a59d3b8ecf1ddb13fcf0522d9df4

Observation 9a5e46b0-c253-43df-90ab-aa23be3d9052 · outbound

This paper cites Attentional shapecontextnet for point cloud recognition.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Attentional shapecontextnet for point cloud recognition

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.809083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:5ee106d985841bb87720ad20f0ff23e2a4536f302de0c7f1366bbd0eee39b442

Observation 2cb99c91-e682-4a70-aa5c-c87820fcd5f8 · outbound

This paper cites Paconv: Position adaptive convolution with dynamic kernel assembling on point clouds.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Paconv: Position adaptive convolution with dynamic kernel assembling on point clouds

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.653377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:3d12f6d0032716423cbb327ee42843bf84e5c38766eb4c0ef46ba39d0b71d538

Observation 7eb91e47-41c2-4e9a-86ba-7699da41b4d3 · outbound

This paper cites Spidercnn: Deep learning on point sets with parameterized convolutional filters.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Spidercnn: Deep learning on point sets with parameterized convolutional filters

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.586260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:9502118d6141bacd13b2faf6eb4192832431243bd6247abe51155bac35de0eae

Observation 0eb234b4-0aa0-4b0a-8df5-95e58b16f826 · outbound

This paper cites 2dpass: 2d priors assisted semantic segmentation on lidar point clouds.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings 2dpass: 2d priors assisted semantic segmentation on lidar point clouds

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.569478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:69d483ce2f928b47ed90bb2cb21a256c81e8f6a601c1725ed5e393ee63e299de

Observation f5282848-dc3e-49e1-9345-4b657f8a51e4 · outbound

This paper cites Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.573014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:9156ffd271c40b8886b96e52802454cc8d02bf1b8bc605b20c6b6b406a69b59e

Observation 7efa3888-dc80-4d3b-90e0-fbb6bb113315 · outbound

This paper cites One inlier is first: Towards efficient position encoding for point cloud registration.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings One inlier is first: Towards efficient position encoding for point cloud registration

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.791304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:553e471339cdba560ce3740ea1b0cb12098980a6014a75b43221db11ac73214a

Observation 4304ab44-da28-4fdb-acaf-09452f85857a · outbound

This paper cites Modeling point clouds with self-attention and gumbel subset sampling.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Modeling point clouds with self-attention and gumbel subset sampling

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.592888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:68930edfa25b2f26839b2d8a8b0b69bce8879a0988eb12cf3ff6298b9994b8ee

Observation 9389db65-5e74-4316-8076-498167cc234a · outbound

This paper cites Swin3d: A pretrained transformer backbone for 3d indoor scene understanding.Computational Visual Media, 11(1):83–101.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Swin3d: A pretrained transformer backbone for 3d indoor scene understanding.Computational Visual Media, 11(1):83–101

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.579629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:e591b337826b41521fcf8d1a716b0d35a6729bce16c69b37b3fcb524780ce7d7

Observation b4ee2522-8614-432f-96ae-a787e5e338d7 · outbound

This paper cites Scannet++: A high-fidelity dataset of 3d indoor scenes.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Scannet++: A high-fidelity dataset of 3d indoor scenes

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.700709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:7e2f601ef8655223af20e4257d5b65513edb28e0dd5b9f28c10d5730f10806ed

Observation 108d27eb-b8e3-4cc3-b050-7ed17253364c · outbound

This paper cites Dformerv2: Geometry self-attention for rgbd semantic segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Dformerv2: Geometry self-attention for rgbd semantic segmentation

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.582914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:737b960818dc2e01e191e9df26deb52e37da3de821d4057e7e6db3d56b9a0daa

Observation 95f5f433-8160-4aa8-874d-6b682db5b7b6 · outbound

This paper cites Omnisegmentor: A flexible multi-modal learning framework for semantic segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Omnisegmentor: A flexible multi-modal learning framework for semantic segmentation

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.680413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:9de520dd7e3b8eef81545413148f7a0bf171b1dd73ddefddd64265575dab40f3

Observation fe1002a3-e46f-4fdc-85d2-cb7177fda331 · outbound

This paper cites DFormer: Rethinking RGBD representation learning for semantic segmentation.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings DFormer: Rethinking RGBD representation learning for semantic segmentation

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.566140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:7187ea26f72fb1b3403bb7a2cd1c666451ddc107ab3371ffaac0888f3bfe1ece

Observation b6203a35-77c9-41aa-9768-274446ae5c40 · outbound

This paper cites Point-bert: Pre-training 3d point cloud transformers with masked point modeling.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Point-bert: Pre-training 3d point cloud transformers with masked point modeling

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T11:21:31.559044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:6ec4a59450cb41de40773628665c1587044ed257a79f56e01e3dbed47ae3fb58

Observation c45ecf6a-1ed3-4a85-a630-7f996bb77781 · outbound

This paper cites Litept: Lighter yet stronger point transformer.

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings Litept: Lighter yet stronger point transformer

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:26:24.019699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T05:25:19.181337Z digest=sha256:d5de15bd158153f751da80e2457c5c49e29e9c630362b12afafb5b83875371e8

Pith citing papers

Observation 0a693711-3644-466d-ab19-1443bb48c33b · inbound

ClockRoPE: Random Fourier Rotations for Temporal Routine Modeling cites this paper.

ClockRoPE: Random Fourier Rotations for Temporal Routine Modeling RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-01T17:28:41.017250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-08-01T17:23:26.151875Z digest=sha256:d0e1bda1ef8e587a48ede98bd6e8e97ce914f744ad813d44c72e956fa4e7c3e3