PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter | Paper Citation Record

Observation 61e390cf-053d-4798-a3b4-c8ed2a844327 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter ShapeNet: An Information-Rich 3D Model Repository

Reference 1

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Observation 4736c9d9-57fe-4436-a147-98e7ae1ba91b · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Pointgpt: Auto-regressively generative pre- training from point clouds

Reference 2

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Observation 5c6128d3-bc0c-429d-a368-1473c7d60680 · outbound

This paper cites Adaptformer: Adapt- ing vision transformers for scalable visual recognition.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Adaptformer: Adapt- ing vision transformers for scalable visual recognition

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:31.329554Z

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Observation 2cd2324b-9b75-41ba-868f-85bd6457a73c · outbound

This paper cites Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

Reference 4

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Observation addea1df-8d98-40c0-8bef-ba914377ded7 · outbound

This paper cites Parameter-efficient fine-tuning of large-scale pre-trained language models.Nature Machine In- telligence, 5(3):220–235, 2023.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Parameter-efficient fine-tuning of large-scale pre-trained language models.Nature Machine In- telligence, 5(3):220–235, 2023

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:31.158465Z

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Observation f18cba67-0464-41e0-932e-50a679315bbc · outbound

This paper cites Autoencoders as cross-modal teachers: Can pretrained 2d image transform- ers help 3d representation learning? Kigali, Rwanda, 2023.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Autoencoders as cross-modal teachers: Can pretrained 2d image transform- ers help 3d representation learning? Kigali, Rwanda, 2023

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:30.944774Z

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Observation 429d5500-912e-453f-a77a-ac21fc593389 · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape Data

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:47:23.376800Z

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Observation 4918f824-16b0-443d-b2fb-b2e58b3194ac · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 8

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Observation 344744a1-3345-4f9a-bc52-0bb81ddf4bef · outbound

This paper cites Hippo: Recurrent memory with optimal polynomial projections.Advances in neural information processing sys- tems, 33:1474–1487, 2020.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Hippo: Recurrent memory with optimal polynomial projections.Advances in neural information processing sys- tems, 33:1474–1487, 2020

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:30.648469Z

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Observation 21b078bd-f451-40df-ad8f-11e3858b4ecc · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Efficiently Modeling Long Sequences with Structured State Spaces

Reference 10

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Observation 8856bc42-2a54-42be-9c2f-40993fef2dc8 · outbound

This paper cites Combining recurrent, convolutional, and continuous-time models with linear state space layers.Advances in neural information processing sys- tems, 34:572–585, 2021.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Combining recurrent, convolutional, and continuous-time models with linear state space layers.Advances in neural information processing sys- tems, 34:572–585, 2021

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:30.386411Z

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Observation 15072702-ac59-4f16-99e9-7ccc06bd7595 · outbound

This paper cites On the parameterization and initialization of diagonal state space models.Advances in Neural Information Processing Systems, 35:35971–35983, 2022.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter On the parameterization and initialization of diagonal state space models.Advances in Neural Information Processing Systems, 35:35971–35983, 2022

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:30.112327Z

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Observation dcd203b2-f67a-4790-978d-295646f63283 · outbound

This paper cites Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts

Reference 13

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Observation da9b2334-3e8a-4b5b-aec1-6683838865ca · outbound

This paper cites MambaIRv2: Attentive State Space Restoration.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter MambaIRv2: Attentive State Space Restoration

Reference 14

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Observation 9ebbb07d-9a5e-4908-9192-a08c83253a2f · outbound

This paper cites MambaIR: A Simple Baseline for Image Restoration with State-Space Model.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter MambaIR: A Simple Baseline for Image Restoration with State-Space Model

Reference 15

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Observation b00edac9-045b-44b8-a7da-3ad9f2d2dceb · outbound

This paper cites Demystify Mamba in Vision: A Linear Attention Perspective.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Demystify Mamba in Vision: A Linear Attention Perspective

Reference 16

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Observation c66c6a89-90d1-4167-9bf4-42f1f6d64c3a · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model

Reference 17

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Observation 03428715-c699-4d0d-8a0c-94c9f7b634fc · outbound

This paper cites an unresolved cited work.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Unresolved cited work

Reference 18

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Observation 29685f96-f02a-4b12-8733-a5e31b50204e · outbound

This paper cites Parameter-efficient transfer learning for nlp.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Parameter-efficient transfer learning for nlp

Reference 19

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Observation a6ac511d-0021-41f1-8122-81a0f6823c7d · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter LoRA: Low-Rank Adaptation of Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:18.202112Z

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Observation 2d640ae8-6a69-4631-87e4-e1b76d3ed53b · outbound

This paper cites Vi- sual prompt tuning.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Vi- sual prompt tuning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:29.565445Z

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Observation bc457ddc-544a-4586-b44a-9c162014d7a5 · outbound

This paper cites Revisiting the parameter efficiency of adapters from the perspective of precision redundancy.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Revisiting the parameter efficiency of adapters from the perspective of precision redundancy

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:29.349065Z

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Observation 745862b4-5e3a-4d98-a3f2-6cb8301f8df5 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 23

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Observation 1af8d278-5850-4cca-9a4e-fcf470efdd63 · outbound

This paper cites Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:18.559441Z

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Observation b2a7c996-c6d2-47e3-a8ea-c30228cf7d4a · outbound

This paper cites PointMamba: A Simple State Space Model for Point Cloud Analysis.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter PointMamba: A Simple State Space Model for Point Cloud Analysis

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:18.609783Z

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Observation 0b3e4a04-2b0d-4f45-8171-74c5f194aeae · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Masked discrimi- nation for self-supervised learning on point clouds

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:29.123696Z

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Observation d879fceb-3210-431b-a7d2-189c9cb0e932 · outbound

This paper cites P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks

Reference 27

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Observation 8c99659a-ffca-490e-aa2b-3146aae6aecf · outbound

This paper cites VMamba: Visual State Space Model.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter VMamba: Visual State Space Model

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:18.866960Z

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Observation ec946569-a2e1-4d4f-92d7-8dd64d75d6bf · outbound

This paper cites Re- thinking network design and local geometry in point cloud: A simple residual mlp framework.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Re- thinking network design and local geometry in point cloud: A simple residual mlp framework

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:28.928353Z

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Observation cfd0fec7-6bb1-48a4-af42-f0d78e277f56 · outbound

This paper cites An end-to- end transformer model for 3d object detection.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter An end-to- end transformer model for 3d object detection

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:28.712062Z

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Observation 29e83e15-8f54-46b7-b69e-6ce0ad9b50ed · outbound

This paper cites A computer oriented geodetic data base and a new technique in file sequencing.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter A computer oriented geodetic data base and a new technique in file sequencing

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:28.551077Z

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Observation c9df4e61-9da6-4864-ad60-28a96847801a · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Masked autoencoders for point cloud self-supervised learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:28.397028Z

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Observation 92836fff-ae57-47ae-a453-39895deac0dc · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:28.205825Z

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Observation 693af659-9bfa-4e1c-9abd-55575986b7d4 · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Pointnet++: Deep hierarchical feature learning on point sets in a metric space

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:27.905470Z

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Observation f5df5980-113f-4aeb-a4f7-b0a5d1e8143d · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Contrast with reconstruct: Contrastive 3d representation learning guided by generative pretraining

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:27.607858Z

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Observation 3c55d82e-415a-4128-8a98-0ada5e9fa697 · outbound

This paper cites Simplified State Space Layers for Sequence Modeling.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Simplified State Space Layers for Sequence Modeling

Reference 36

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Observation 4d3e8129-db8f-487f-8224-f5117c8d1fac · outbound

This paper cites Parameter-efficient Prompt Learning for 3D Point Cloud Understanding.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Parameter-efficient Prompt Learning for 3D Point Cloud Understanding

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:47:22.689088Z

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Observation c47decfb-81e5-4653-92d6-4bede0c40bcc · outbound

This paper cites X-3d: Explicit 3d structure modeling for point cloud recog- nition.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter X-3d: Explicit 3d structure modeling for point cloud recog- nition

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:27.358034Z

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Observation 5ff8d899-9b16-4d1e-81b1-952148d8372a · outbound

This paper cites Point- peft: Parameter-efficient fine-tuning for 3d pre-trained mod- els.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Point- peft: Parameter-efficient fine-tuning for 3d pre-trained mod- els

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:27.073686Z

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Observation c3ee399f-294b-4e0f-a1cd-eeaf0fb05cb4 · outbound

This paper cites Multimodal few-shot learning with frozen language models.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Multimodal few-shot learning with frozen language models

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:26.792359Z

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Observation 461a9f85-16aa-4d36-9cf1-9561c8739334 · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:26.451727Z

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Observation 18496a4c-cbcc-4771-b416-ccc80186a025 · outbound

This paper cites Attention is all you need.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Attention is all you need

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:26.249954Z

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Observation e1a68a27-07aa-43df-89df-8a86ad039511 · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Unsupervised point cloud pre-training via oc- clusion completion

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:26.098922Z

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Observation eaeeb5a5-bcef-4f52-85e7-e73f2f87fd8b · outbound

This paper cites Dynamic graph cnn for learning on point clouds.Acm Transactions On Graphics (TOG), 38(5):1–12, 2019.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Dynamic graph cnn for learning on point clouds.Acm Transactions On Graphics (TOG), 38(5):1–12, 2019

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:25.909565Z

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Observation 9914a220-66b8-4376-b926-bf639da4a86e · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter P2p: Tuning pre-trained image models for point cloud analysis with point-to-pixel prompting

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:25.665312Z

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Observation e1fc10ab-ef5e-4326-b55d-fc40b39a5d4b · outbound

This paper cites Point transformer v2: Grouped vector atten- tion and partition-based pooling.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Point transformer v2: Grouped vector atten- tion and partition-based pooling

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:25.356398Z

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Observation 1be31fb0-b922-4501-bd6f-fd25bfc0d5bf · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Point transformer v3: Simpler, faster, stronger

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:25.070084Z

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Observation da13b0fc-4b1e-4d52-91d2-3dfd4f1b1ffa · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter 3d shapenets: A deep representation for volumetric shapes

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:24.857834Z

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Observation 762469a5-12f5-48ea-8e8a-2b4c2fad39e8 · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Point-bert: Pre-training 3d point cloud transformers with masked point modeling

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:24.679576Z

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Observation 2f363491-4633-4b97-aced-b82d535fdf22 · outbound

This paper cites Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.arXiv preprint arXiv:2106.10199,.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.arXiv preprint arXiv:2106.10199,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:20.640464Z

Source-reported events for the cited work

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Observation 1cfc6e69-078c-4a8d-a3f3-6e2774ea92a6 · outbound

This paper cites Sfr: Semantic-aware feature ren- dering of point cloud.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Sfr: Semantic-aware feature ren- dering of point cloud

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:24.564643Z

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Observation d080bbc9-1044-4601-8891-99e3d5d7c0e3 · outbound

This paper cites Instance-aware dynamic prompt tuning for pre-trained point cloud models.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Instance-aware dynamic prompt tuning for pre-trained point cloud models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:24.470717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4707ee05-6002-4583-85c2-cf6e2bdf1a23 · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Towards compact 3d representations via point feature enhancement masked au- toencoders

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:24.310050Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7ed43861-4880-401b-9bd6-6f998371b8af · outbound

This paper cites LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:47:22.322011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 597496b2-6931-4aaa-a31d-e74a50db739b · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Point- m2ae: Multi-scale masked autoencoders for hierarchical point cloud pre-training

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:24.170226Z

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Observation adb9828b-e184-4934-841f-41f5c9c3c47f · outbound

This paper cites Tip- adapter: Training-free adaption of clip for few-shot classifi- cation.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Tip- adapter: Training-free adaption of clip for few-shot classifi- cation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:24.037277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bee54b7f-f7e1-407c-a7d6-cda50076af08 · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Learning 3d representations from 2d pre-trained models via image-to-point masked autoencoders

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:23.871733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d9e489e4-8649-44cf-9947-23090c5c938b · outbound

This paper cites Parameter-Efficient and Memory-Efficient Tuning for Vision Transformer: A Disentangled Approach.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Parameter-Efficient and Memory-Efficient Tuning for Vision Transformer: A Disentangled Approach

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:47:22.091410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 60a899b5-b827-4978-b5ca-a1417588b0c8 · outbound

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

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Point cloud pre-training with diffusion models

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:23.780123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5803166a-5c26-42c4-8c5b-afe3dd068785 · outbound

This paper cites Conditional prompt learning for vision-language mod- els.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Conditional prompt learning for vision-language mod- els

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:21.492936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23b48c81-6339-4535-b72f-08d49c6cce90 · outbound

This paper cites Learning to prompt for vision-language models.In- ternational Journal of Computer Vision, 130(9):2337–2348,.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Learning to prompt for vision-language models.In- ternational Journal of Computer Vision, 130(9):2337–2348,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:21.629713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0aa56492-0fd3-49ea-913c-3ad2a659466c · outbound

This paper cites Dynamic adapter meets prompt tuning: Parameter-efficient transfer learning for point cloud analysis.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Dynamic adapter meets prompt tuning: Parameter-efficient transfer learning for point cloud analysis

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:47:23.633492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 22d61f84-75c2-4845-845e-af304e282a4c · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:21.850906Z

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