Paper Citation Record · LEDGER

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis

As of 21 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2507.18997.

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

pith.paper-citation-record.v1
2507.18997 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:08:17.621702Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

verified exact2
verified fuzzy31
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 831da27f-0c57-425d-9633-4331edbe5310 · outbound

This paper cites GAPrompt: Geometry-Aware Point Cloud Prompt for 3D Vision Model.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis GAPrompt: Geometry-Aware Point Cloud Prompt for 3D Vision Model

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:08:17.780462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d50b440b-ca9d-4b26-8462-489d9d272e05 · outbound

This paper cites Vision Graph Prompting via Semantic Low-Rank Decomposition.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Vision Graph Prompting via Semantic Low-Rank Decomposition

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:08:17.757573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation efb7a279-4399-4b21-8d8c-5e5fe1179386 · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis ShapeNet: An Information-Rich 3D Model Repository

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.405858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed6d99c0-1248-4077-9c77-434324f56db3 · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Pointgpt: Auto-regressively generative pre- training from point clouds

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.375735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8c02a81c-2f25-4cb0-be70-e9234421840b · outbound

This paper cites Adaptformer: Adapting vision transformers for scalable visual recogni- tion.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Adaptformer: Adapting vision transformers for scalable visual recogni- tion

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.358246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 241b11aa-328f-4078-a4f2-b869d0eb5a1d · outbound

This paper cites Straight- pcf: Straight point cloud filtering.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Straight- pcf: Straight point cloud filtering

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.342639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 59384dfd-8e1b-404c-acd2-94a3210f2113 · outbound

This paper cites an unresolved cited work.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:08:18.325936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 94f6710f-a21b-4663-a357-f1258a12d54e · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.432236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5f60b30-aed2-4c19-9b05-34544cd73a95 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis An image is worth 16x16 words: Transformers for image recognition at scale

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.309966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3f51d8be-65f1-4e94-8818-fc7dce231077 · outbound

This paper cites T-corresnet: Template guided 3d point cloud completion with correspondence pool- ing query generation strategy.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis T-corresnet: Template guided 3d point cloud completion with correspondence pool- ing query generation strategy

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.293706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d2bf6e6b-e930-4fbd-93a3-9f7c4dca6af8 · outbound

This paper cites Parameter-efficient transfer learning for nlp.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Parameter-efficient transfer learning for nlp

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.446692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e962a7f-460b-4c85-bea9-f0e70f2dbdad · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis LoRA: Low-Rank Adaptation of Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.451517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c70969e9-d469-49c1-86dd-6f9291143d3c · outbound

This paper cites Vi- sual prompt tuning.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Vi- sual prompt tuning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.457060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4d2a05c-4de6-440d-add9-557ba57d626a · outbound

This paper cites Fact: Factor-tuning for lightweight adaptation on vision transformer.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Fact: Factor-tuning for lightweight adaptation on vision transformer

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.255469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9b73ce35-d779-4835-a740-ec1509ddc6e2 · outbound

This paper cites Compacter: Efficient low-rank hypercomplex adapter layers.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Compacter: Efficient low-rank hypercomplex adapter layers

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.466751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bddb3464-9988-4996-8fe9-8667fe53268b · outbound

This paper cites Oneformer3d: One transformer for unified point cloud segmentation.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Oneformer3d: One transformer for unified point cloud segmentation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.227789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ae4d4348-dae5-45a3-a811-646a384f602d · outbound

This paper cites Proxyformer: Proxy alignment assisted point cloud comple- tion with missing part sensitive transformer.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Proxyformer: Proxy alignment assisted point cloud comple- tion with missing part sensitive transformer

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.211691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2f7d69b8-92ba-455f-a78f-baa4244180f8 · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Relation-shape convolutional neural network for point cloud analysis

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.196225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cca83d3d-0bec-4e8a-b23d-5842bd0d38f8 · outbound

This paper cites Insvp: Efficient instance visual prompting from image itself.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Insvp: Efficient instance visual prompting from image itself

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.179614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 09137849-0637-4776-8075-91d4bf191a60 · outbound

This paper cites Stop: Integrated spatial-temporal dynamic prompting for video understanding.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Stop: Integrated spatial-temporal dynamic prompting for video understanding

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.163132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6167249a-e954-4157-b284-bd71f18e99e1 · outbound

This paper cites Decoupled weight de- cay regularization.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Decoupled weight de- cay regularization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.499455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fe3c3c8-1e77-4ca3-a663-d6d74aa94fee · outbound

This paper cites Sgdr: Stochastic gradient descent with warm restarts.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Sgdr: Stochastic gradient descent with warm restarts

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.136312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1a2c19e6-c6ad-429e-8e0f-d5fcd019aee2 · outbound

This paper cites Differentiable manifold recon- struction for point cloud denoising.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Differentiable manifold recon- struction for point cloud denoising

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.119050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3726b82f-1cdc-4426-abd0-7332c575416d · outbound

This paper cites Score-based point cloud denoising.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Score-based point cloud denoising

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.096542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2d7e5c70-c76f-471c-bbc9-807d2b9ccb3f · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.519509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ec1669f-8735-4e28-b6ef-9a3366f1ceff · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Masked autoencoders for point cloud self-supervised learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.077065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ca3fdec1-120e-407b-b157-c6c2f078d219 · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.529072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07aec542-cd6e-4194-9736-50394151fa58 · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Contrast with reconstruct: Contrastive 3d representation learning guided by generative pretraining

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.049020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 78aae8ca-3b52-4f8f-8b60-c5d826f036a3 · outbound

This paper cites ShapeLLM: Universal 3D Object Understanding for Embodied Interaction.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis ShapeLLM: Universal 3D Object Understanding for Embodied Interaction

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.539497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 630e871c-055f-4f53-a8f5-235cd0e74e7e · outbound

This paper cites Pointcleannet: Learning to denoise and remove outliers from dense point clouds.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Pointcleannet: Learning to denoise and remove outliers from dense point clouds

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.032188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation beda631d-b66a-4cb2-a447-40a097731a21 · outbound

This paper cites Contrastive boundary learning for point cloud segmentation.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Contrastive boundary learning for point cloud segmentation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:18.013760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6a3f1601-b093-475e-bf06-bb4c21ef8108 · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Point- peft: Parameter-efficient fine-tuning for 3d pre-trained mod- els

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.992052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a6e2fb24-a197-489b-9918-54963266e885 · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.976980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 72b162c3-32e8-4d29-83de-4a52dc3d5aa2 · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis 3d shapenets: A deep representation for volumetric shapes

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.960358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0c1b2a03-2f2e-4060-82f6-33de957b6a60 · outbound

This paper cites Componential Prompt-Knowledge Alignment for Domain Incremental Learning.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Componential Prompt-Knowledge Alignment for Domain Incremental Learning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.573455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6739496-5568-41a7-b0a0-824b92c45231 · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.944666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4d91bfb9-8053-44e9-8c7d-2c4f64a6962c · 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.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis A scalable active framework for region annotation in 3d shape collections.ACM Transactions on Graphics (ToG), 35(6):1–12, 2016

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.927432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c15cbecc-9554-4daa-810d-812d98e62756 · outbound

This paper cites Pointr: Diverse point cloud comple- tion with geometry-aware transformers.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Pointr: Diverse point cloud comple- tion with geometry-aware transformers

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.910912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4b6b6b8a-666a-4937-8367-7295e20264bf · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Point-bert: Pre-training 3d point cloud transformers with masked point modeling

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.894728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 574948b3-db73-4072-bc13-198a3ba8a134 · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Instance-aware dynamic prompt tuning for pre-trained point cloud models

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.876943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 502f080c-307c-4098-a575-e5c3e53cbb85 · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Towards compact 3d representations via point feature enhancement masked au- toencoders

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.860703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 78b07442-0815-416c-805d-fcc48b6fce4e · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Point-m2ae: multi-scale masked autoencoders for hierarchical point cloud pre-training

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.844037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation acb41e47-ee25-4872-bd8a-4831ec711ccd · outbound

This paper cites Pcp- mae: Learning to predict centers for point masked autoen- coders.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Pcp- mae: Learning to predict centers for point masked autoen- coders

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.827755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2457ac48-63bf-4fb9-8c26-5335edc0b22d · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Dynamic adapter meets prompt tuning: Parameter-efficient transfer learning for point cloud analysis

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.811583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 83dcb0d6-b191-45ee-b87a-ea64e5f539ef · outbound

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

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Point- clip v2: Prompting clip and gpt for powerful 3d open-world learning

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:08:17.796388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.