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Paper Citation Record · LEDGER

Point Cloud Understanding via Attention-Driven Contrastive Learning

As of 15 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2411.14744.

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

pith.paper-citation-record.v1
2411.14744 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

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measured 68 of 68 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

68 of 68 outbound references displayed

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External citation measurements

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Outbound references

Observation baea57f2-e29f-4aac-b4e6-3b9285664b01 · outbound

This paper cites Maskclr: Attention-guided contrastive learning for robust action representation learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Maskclr: Attention-guided contrastive learning for robust action representation learning

Reference 1

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Observation 93738aad-904d-4f6e-be0e-0f648a6930e0 · outbound

This paper cites Learning representations and generative models for 3d point clouds.

Point Cloud Understanding via Attention-Driven Contrastive Learning Learning representations and generative models for 3d point clouds

Reference 2

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Observation 552df88a-6957-485f-8354-9aaa8c3b12de · outbound

This paper cites An overview of augmented reality.

Point Cloud Understanding via Attention-Driven Contrastive Learning An overview of augmented reality

Reference 3

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Observation 1bca8966-b585-4f3b-92f0-c31166da9713 · outbound

This paper cites BEiT: BERT Pre-Training of Image Transformers.

Point Cloud Understanding via Attention-Driven Contrastive Learning BEiT: BERT Pre-Training of Image Transformers

Reference 4

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Observation 271b9934-8e53-453f-bda2-1809859d7b11 · outbound

This paper cites Pointgpt: Auto-regressively generative pre- training from point clouds.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointgpt: Auto-regressively generative pre- training from point clouds

Reference 5

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Observation ad33447d-4677-4c73-82c0-376cfbc734b9 · outbound

This paper cites 3d point cloud processing and learning for autonomous driving: Impacting map cre- ation, localization, and perception.

Point Cloud Understanding via Attention-Driven Contrastive Learning 3d point cloud processing and learning for autonomous driving: Impacting map cre- ation, localization, and perception

Reference 6

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Observation 79ad3b31-c76d-40b7-9b0f-585da9480d27 · outbound

This paper cites Multi-view 3d object detection network for autonomous driving.

Point Cloud Understanding via Attention-Driven Contrastive Learning Multi-view 3d object detection network for autonomous driving

Reference 7

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Observation 07db0219-6b67-403b-af58-9ba59cb9a43f · outbound

This paper cites Pra-net: Point relation-aware network for 3d point cloud analysis.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pra-net: Point relation-aware network for 3d point cloud analysis

Reference 8

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Observation 2ff5ff91-4bb5-4ff1-bb2f-1da9636da940 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Point Cloud Understanding via Attention-Driven Contrastive Learning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 9

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Observation a5ce1970-c754-45e2-82b0-9f3b6d8701f0 · outbound

This paper cites Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?.

Point Cloud Understanding via Attention-Driven Contrastive Learning Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?

Reference 10

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Observation 407ab37b-efcc-4850-bb23-f48aa469b912 · outbound

This paper cites Why does unsupervised pre-training help deep learning? In Proceedings of the thirteenth international con- ference on artificial intelligence and statistics , pages 201–.

Point Cloud Understanding via Attention-Driven Contrastive Learning Why does unsupervised pre-training help deep learning? In Proceedings of the thirteenth international con- ference on artificial intelligence and statistics , pages 201–

Reference 11

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Observation be9fb503-9fad-4c05-bdf8-0f6184bd744e · outbound

This paper cites Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape Data.

Point Cloud Understanding via Attention-Driven Contrastive Learning Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape Data

Reference 12

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Observation 4d672c25-1a7c-486e-afdd-7fa45cdee83b · outbound

This paper cites Point cloud interaction and ma- nipulation in virtual reality.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point cloud interaction and ma- nipulation in virtual reality

Reference 13

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Observation ed330813-9031-4514-a097-ea5b435e7456 · outbound

This paper cites Generative adversarial networks.

Point Cloud Understanding via Attention-Driven Contrastive Learning Generative adversarial networks

Reference 14

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Observation d14cfb5c-4947-4347-863a-4e09a934de8c · outbound

This paper cites Mvtn: Multi-view transformation network for 3d shape recognition.

Point Cloud Understanding via Attention-Driven Contrastive Learning Mvtn: Multi-view transformation network for 3d shape recognition

Reference 15

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Observation 3b3998e8-d8b4-42c8-a0ed-2a2b280c95ca · outbound

This paper cites Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model.

Point Cloud Understanding via Attention-Driven Contrastive Learning Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model

Reference 16

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Observation c7ed3567-2dd1-4428-a8aa-0b399279857b · outbound

This paper cites Masked autoencoders are scalable vision learners.

Point Cloud Understanding via Attention-Driven Contrastive Learning Masked autoencoders are scalable vision learners

Reference 17

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Observation 409ed794-3888-4d72-9094-b41ad1c0a56a · outbound

This paper cites Atten- tion discriminant sampling for point clouds.

Point Cloud Understanding via Attention-Driven Contrastive Learning Atten- tion discriminant sampling for point clouds

Reference 18

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Observation 52fed73b-6848-4b25-92c8-7d521c8ccee3 · outbound

This paper cites Clip2point: Transfer clip to point cloud classifica- tion with image-depth pre-training.

Point Cloud Understanding via Attention-Driven Contrastive Learning Clip2point: Transfer clip to point cloud classifica- tion with image-depth pre-training

Reference 19

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Observation 891c9b6c-7704-4d13-9a83-70f91c754705 · outbound

This paper cites Self-supervised Modal and View Invariant Feature Learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Self-supervised Modal and View Invariant Feature Learning

Reference 20

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Observation 4e497889-cf0e-45b5-a7d3-eb91c5a07d8c · outbound

This paper cites So-net: Self- organizing network for point cloud analysis.

Point Cloud Understanding via Attention-Driven Contrastive Learning So-net: Self- organizing network for point cloud analysis

Reference 21

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Observation 8995eed4-fc78-4f2e-a036-3db849fa5060 · outbound

This paper cites Pointcnn: Convolution on x-transformed points.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointcnn: Convolution on x-transformed points

Reference 22

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Observation 4cf7ce91-4992-4b21-b1f0-f49c3cdf5cec · outbound

This paper cites General point model pretrain- ing with autoencoding and autoregressive.

Point Cloud Understanding via Attention-Driven Contrastive Learning General point model pretrain- ing with autoencoding and autoregressive

Reference 23

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Observation 2c10a092-53d5-423a-8b04-1cd07a0c6541 · outbound

This paper cites Pointmamba: A simple state space model for point cloud analysis.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointmamba: A simple state space model for point cloud analysis

Reference 24

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Observation 724bfbbc-df71-4009-a169-73059417a34c · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Masked dis- crimination for self-supervised learning on point clouds

Reference 25

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Observation 7e157fe1-aed5-44c4-8750-d2e87c4fb250 · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy

Reference 26

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Observation bd8bbbb6-7c46-432e-8697-0e52742f2bba · outbound

This paper cites Deep image translation with an affinity-based change prior for un- supervised multimodal change detection.

Point Cloud Understanding via Attention-Driven Contrastive Learning Deep image translation with an affinity-based change prior for un- supervised multimodal change detection

Reference 27

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Observation 4a1836a8-9e89-47a7-8090-23b3fe5ba22f · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework

Reference 28

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Observation 763ddcc8-90f7-434c-8329-72c51434dae1 · outbound

This paper cites Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders.

Point Cloud Understanding via Attention-Driven Contrastive Learning Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders

Reference 29

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Observation 3b7e714c-4da6-49af-9a7d-dc0e128b9988 · outbound

This paper cites Self-supervised learning of pretext-invariant representations.

Point Cloud Understanding via Attention-Driven Contrastive Learning Self-supervised learning of pretext-invariant representations

Reference 30

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Observation cd8a7d5d-3144-4e22-8658-40d13b843386 · outbound

This paper cites From image collections to point clouds with self-supervised shape and pose networks.

Point Cloud Understanding via Attention-Driven Contrastive Learning From image collections to point clouds with self-supervised shape and pose networks

Reference 31

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Observation 3b5c2cde-b822-47b0-b29e-6facd05f3efb · outbound

This paper cites Masked autoencoders for point cloud self-supervised learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Masked autoencoders for point cloud self-supervised learning

Reference 32

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Observation 54a3fb0a-c889-4ced-9def-cc64ad5bfebe · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 33

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Observation 5a551712-1e2f-453f-ae56-92f25d82190c · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointnet++: Deep hierarchical feature learning on point sets in a metric space

Reference 34

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Observation 0da31cb1-6f0d-4c1e-b504-9fcf36d92628 · outbound

This paper cites Contrast with reconstruct: Contrastive 3d representation learning guided by generative pretraining.

Point Cloud Understanding via Attention-Driven Contrastive Learning Contrast with reconstruct: Contrastive 3d representation learning guided by generative pretraining

Reference 35

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7b78220e-d998-47e8-ac57-26d484525521 · outbound

This paper cites Shapellm: Universal 3d object understanding for embodied interaction.

Point Cloud Understanding via Attention-Driven Contrastive Learning Shapellm: Universal 3d object understanding for embodied interaction

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.444104Z digest=sha256:2e91881bc5f9604b05652467f6a1b4fa91a71c4fcdb5bf7f0c08f51b71a20464

Observation 5bc303ed-03af-457c-9633-793c0dba9e61 · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointnext: Revisiting pointnet++ with improved training and scaling strategies

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.448658Z digest=sha256:a42a38d1e90976625fd64e2f34e1409aa022354ea7f64cc933383415ad6d9092

Observation 207d52b4-4663-4059-b623-a465854edb5d · outbound

This paper cites Spatiotempo- ral contrastive video representation learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Spatiotempo- ral contrastive video representation learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.102771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.452745Z digest=sha256:100c1989b124de0b010d51ef1e2d99d6d602f346a2bb226b817e4cfd3f02e7d0

Observation 345cf29e-b129-4ab6-b0a5-f699a11f5079 · outbound

This paper cites Improving language understanding by gener- ative pre-training.

Point Cloud Understanding via Attention-Driven Contrastive Learning Improving language understanding by gener- ative pre-training

Reference 39

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no resolver link, observed 2026-08-12T15:02:29.456807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.456807Z digest=sha256:c178178669501a1cfeea967207e5b4623d421ec3fd6eeeebffc472776fe4b4c8

Observation 3427be56-0e2b-43cf-8e06-508d9fed31a4 · outbound

This paper cites Surface representa- tion for point clouds.

Point Cloud Understanding via Attention-Driven Contrastive Learning Surface representa- tion for point clouds

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.080296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.460969Z digest=sha256:f8843061d5d5f50801e6f9213aabf48fef4527c4e14e8f72736ca14c5ce2ee4b

Observation 95c965bf-06fd-4060-b008-630f6f064a7c · outbound

This paper cites Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud

Reference 41

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no resolver link, observed 2026-08-12T15:02:29.465805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.465805Z digest=sha256:3f81af0bcbc724f02382ec6f123194fdb012e6b38006eaf214ff2431a6e6b448

Observation b80f86a0-76c7-4ee6-9633-87c60bf0ea00 · outbound

This paper cites Detecting formal thought disorder by deep contextualized word representations.

Point Cloud Understanding via Attention-Driven Contrastive Learning Detecting formal thought disorder by deep contextualized word representations

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.065560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.470436Z digest=sha256:d1a8da929acc0e77363552053a4f6d3c4f63a70373a11b5afa7c9b745ab02843

Observation 196242b6-a3c3-401e-811b-e5b6b5c3f96a · outbound

This paper cites Self-supervised deep learning on point clouds by reconstructing space.

Point Cloud Understanding via Attention-Driven Contrastive Learning Self-supervised deep learning on point clouds by reconstructing space

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.050442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.474611Z digest=sha256:cf1aa7c5beabcd282e38d5e38c8727c4e021b0698faab3c959a32c229177e37d

Observation a27fb856-ee6c-407a-9fa0-14a56b88ff94 · outbound

This paper cites Exploring 3d navigation: combining speed-coupled flying with orbiting.

Point Cloud Understanding via Attention-Driven Contrastive Learning Exploring 3d navigation: combining speed-coupled flying with orbiting

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.035371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.478811Z digest=sha256:b24f2142bc7002ad39b62d8a1781cfa72ee09101df300d8b40acc94c2a42bf7f

Observation a4084798-037f-4d0a-a9f4-9d8594038c98 · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.482839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.482839Z digest=sha256:34e9a6756b4bd980ad76f8d000698e66e63c7dfc40f36b7d99b532c754c87d51

Observation ad7495c6-c6ef-43b2-b531-4a03efec5a8c · outbound

This paper cites Unsupervised point cloud pre-training via oc- clusion completion.

Point Cloud Understanding via Attention-Driven Contrastive Learning Unsupervised point cloud pre-training via oc- clusion completion

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.487158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.487158Z digest=sha256:a1f7614ab099fa6d83ccd8c67abcfcd640132f844149b1b02a3f2e272e17bb0b

Observation d2f491c3-6221-45f9-97f9-c21f382edbd9 · outbound

This paper cites Dynamic graph cnn for learning on point clouds.

Point Cloud Understanding via Attention-Driven Contrastive Learning Dynamic graph cnn for learning on point clouds

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.003191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.492160Z digest=sha256:ae1f0ccb424ba84ee7fb662b5df70fbfe7dfcc17fd231f8d6f65cbb2823974b9

Observation 401ba033-b8ec-43ee-ac0f-7720c3f11dd0 · outbound

This paper cites P2p: Tuning pre-trained image models for point cloud analysis with point-to-pixel prompting.

Point Cloud Understanding via Attention-Driven Contrastive Learning P2p: Tuning pre-trained image models for point cloud analysis with point-to-pixel prompting

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.988861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.496362Z digest=sha256:d67970f3846834e53121cbbdeeae14fce0938fcd64c21e209a14c61920c95fc4

Observation 6706fcdb-20f7-4a7f-92e2-b3d6e59969e0 · outbound

This paper cites PoinTramba: A Hybrid Transformer-Mamba Framework for Point Cloud Analysis.

Point Cloud Understanding via Attention-Driven Contrastive Learning PoinTramba: A Hybrid Transformer-Mamba Framework for Point Cloud Analysis

Reference 49

Resolution
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no resolver link, observed 2026-08-12T15:02:29.500659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.500659Z digest=sha256:dc1986639b2dce3d2134a4bb537400e77e468993889c62b33187ba54e1be971c

Observation 42770447-8211-4bbf-a029-9ee1a73db0da · outbound

This paper cites Point transformer v3: Simpler faster stronger.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point transformer v3: Simpler faster stronger

Reference 50

Resolution
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no resolver link, observed 2026-08-12T15:02:29.505240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.505240Z digest=sha256:ef9da151d509c5f084c71ba42f485d4bde9ddebe34a9c2d03b60a11042cf142e

Observation e4c35407-5f76-46c1-b3c7-a400b21db2b5 · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning 3d shapenets: A deep representation for volumetric shapes

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.509545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.509545Z digest=sha256:9d0eabee4a4b2bfa20cf7f57b69b751fe32a8fbc3384091ad966eab44f9473b2

Observation 9e7ead83-494e-4f1d-9e7e-93ea2c9a34bd · outbound

This paper cites Pointcontrast: Unsupervised pre- training for 3d point cloud understanding.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointcontrast: Unsupervised pre- training for 3d point cloud understanding

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.513864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.513864Z digest=sha256:e34598fc5d565947ac490d131990a4f9fc3c86cf477c6c073e2b50d21796f6e9

Observation c7b9612c-8a16-4c73-b3de-a19dfcdf13e4 · outbound

This paper cites Ulip: Learning a unified representation of language, images, and point clouds for 3d understanding.

Point Cloud Understanding via Attention-Driven Contrastive Learning Ulip: Learning a unified representation of language, images, and point clouds for 3d understanding

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.947952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.517961Z digest=sha256:732f7f3e4505a090219b00f8939ab31673435cfb113fb434b9210ac10c40e564

Observation 3fd99a41-bfc4-4a1d-b347-ab2b206466f0 · outbound

This paper cites Ulip-2: Towards scalable multimodal pre-training for 3d understanding.

Point Cloud Understanding via Attention-Driven Contrastive Learning Ulip-2: Towards scalable multimodal pre-training for 3d understanding

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.933619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.522683Z digest=sha256:b974c86337b7e6f5de29649ce202e58f84f12a01abf14ca3ab001fe25124e8d5

Observation 0022ba92-18df-41de-b3b3-f098cbc82e62 · outbound

This paper cites A scalable active framework for region annotation in 3d shape collections.ACM Transactions on Graphics (ToG), 35(6):1–12, 2016.

Point Cloud Understanding via Attention-Driven Contrastive Learning A scalable active framework for region annotation in 3d shape collections.ACM Transactions on Graphics (ToG), 35(6):1–12, 2016

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.917595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.526959Z digest=sha256:ea0edfc41e0263dcd427fa63850f8148528fb4865b913764358005dbcd4ba378

Observation b93b111f-4656-41af-8374-a32db048e2b7 · outbound

This paper cites Seq- gan: Sequence generative adversarial nets with policy gra- dient.

Point Cloud Understanding via Attention-Driven Contrastive Learning Seq- gan: Sequence generative adversarial nets with policy gra- dient

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.903174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.531601Z digest=sha256:f47a4a099c96276d4015d9eebf75892314e54176faefebd0c3b5cea4259fa3ba

Observation 3710a2b5-8b8f-4b9f-916e-3931aedfa8d1 · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Point-bert: Pre-training 3d point cloud transformers with masked point modeling

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.889051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.536245Z digest=sha256:0ae8b406602c18199c69d9b114674180bb011ed09aaf2f321308c607789c556b

Observation b701f068-8c08-45b3-b379-d6363e0a1d7d · outbound

This paper cites Towards compact 3d representations via point feature enhancement masked au- toencoders.

Point Cloud Understanding via Attention-Driven Contrastive Learning Towards compact 3d representations via point feature enhancement masked au- toencoders

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.873905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.540700Z digest=sha256:c5ef21c24ec3654d1da17424afd899c6d7bc7dfd9016ad59ff28369f0b54dc2c

Observation 7bbaae1d-fecf-420e-9126-b9799228bff6 · outbound

This paper cites Point-m2ae: multi-scale masked autoencoders for hierarchical point cloud pre-training.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point-m2ae: multi-scale masked autoencoders for hierarchical point cloud pre-training

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.859899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.544977Z digest=sha256:9cbe43c6690eb08f2957fd3dfd3f63c10f0dc97f125b23b563a416712a426c9b

Observation 344503da-2ed2-40c9-9c09-a612e68aeadf · outbound

This paper cites Pointclip: Point cloud understanding by clip.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointclip: Point cloud understanding by clip

Reference 60

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no resolver link, observed 2026-08-12T15:02:29.549419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.549419Z digest=sha256:d85741e10b52adfd80df957bc32a1528e687959eb16e4457937f6309bdfd70f9

Observation cf69d5f5-97ae-4548-9df2-53087ab91c15 · outbound

This paper cites Learning 3d representations from 2d pre-trained models via image-to-point masked autoencoders.

Point Cloud Understanding via Attention-Driven Contrastive Learning Learning 3d representations from 2d pre-trained models via image-to-point masked autoencoders

Reference 61

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no resolver link, observed 2026-08-12T15:02:29.553565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.553565Z digest=sha256:276e9ad7ca811278f98ee6af543c50cab8060d43f9281b6cc1f876daad930df5

Observation d030eed5-aba7-4df7-bc4a-91989fe13600 · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Point Cloud Mamba: Point Cloud Learning via State Space Model

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.557826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.557826Z digest=sha256:afa2046f6f59929799c67aea3e6456c2233528c02e6266f7219d222411a3c5bb

Observation 39e658a0-db9f-410e-96b5-26df7c8b466d · outbound

This paper cites Self-supervised pretraining of 3d features on any point-cloud.

Point Cloud Understanding via Attention-Driven Contrastive Learning Self-supervised pretraining of 3d features on any point-cloud

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.562532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.562532Z digest=sha256:6b0db9e91fb61b4cb8fbe22416d4b2acb4cc3b83343697b0c873a06be7f88b3b

Observation 93ba131c-0ebc-4b75-accd-918b46c010f8 · outbound

This paper cites Point cloud pre-training with diffusion models.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point cloud pre-training with diffusion models

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.820880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.567133Z digest=sha256:b53fe4d9354247b4a488056a299f92f97258ecb0c7519c66ea873414870efe41

Observation 6018777d-c94a-4fa7-868d-4559ac5d2b54 · outbound

This paper cites Point- clip v2: Prompting clip and gpt for powerful 3d open-world learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point- clip v2: Prompting clip and gpt for powerful 3d open-world learning

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.806971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.571388Z digest=sha256:3061687451ee3bd9a24778297e5ade23a90914e47c5de9e0f70ac39dbeaab1a3

Observation aead56e4-fb34-43b6-8ed9-0e4b5d5e8b6f · outbound

This paper cites 3d-vista: Pre-trained transformer for 3d vision and text alignment.

Point Cloud Understanding via Attention-Driven Contrastive Learning 3d-vista: Pre-trained transformer for 3d vision and text alignment

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.793451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.576146Z digest=sha256:2bbe0a2e755f3222943714ad4b584ee649cfffecc8fff66a698591a483337c6d

Observation 3923ae20-b792-4512-a0cd-c139c170e596 · outbound

This paper cites Preliminary Transformer-based self-supervised learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Preliminary Transformer-based self-supervised learning

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.779374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.580306Z digest=sha256:feca46aed755ba01ad3bd0f4423c5e2fd1721b90dc96e4db70ea8144263df2e3

Observation 4e389784-8766-4040-a5ca-3b53a61f852d · outbound

This paper cites an unresolved cited work.

Point Cloud Understanding via Attention-Driven Contrastive Learning Unresolved cited work

Reference 208

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unresolved
raw_fallback, observed 2026-08-12T15:02:30.380498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:02:29.336161Z digest=sha256:b09a8bcd3251f5766dc3710bc042125f18c537986d7fb67e558f7ad88f13d826

Pith citing papers

No inbound Pith citation observations are available.