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Paper Citation Record · LEDGER

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

As of 16 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:1706.02413.

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

pith.paper-citation-record.v1
1706.02413 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T09:15:58.967751Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T19:18:54.866137Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3a771535-14a6-45e6-9c32-e7585ea7bc44 · inbound

LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention cites this paper.

LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 198

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metadata mismatch
local_arxiv, observed 2026-05-14T23:07:42.926664Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=arxiv_source observed=2026-05-14T23:07:42.245641Z digest=sha256:0151d54d05475be43fd515c3fecc550ed63d2276c27f9cdebacc0c077746033b

Observation 30383b84-05b8-444c-8d4f-2abb81c600c4 · inbound

GraphFusion3D: Dynamic Graph Attention Convolution with Adaptive Cross-Modal Transformer for 3D Object Detection cites this paper.

GraphFusion3D: Dynamic Graph Attention Convolution with Adaptive Cross-Modal Transformer for 3D Object Detection PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 14

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verified exact
local_arxiv, observed 2026-05-17T02:18:52.821121Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-05-17T02:14:52.684497Z digest=sha256:df5b9ffb088f5a0ef0a09abea58794140ef847d1ce66c113abbf6f899c02af46

Observation b3517e81-0c09-47a2-81bc-bdef60e6f785 · inbound

InCoM: Intent-Driven Perception and Structured Coordination for Mobile Manipulation cites this paper.

InCoM: Intent-Driven Perception and Structured Coordination for Mobile Manipulation PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 34

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verified exact
local_arxiv, observed 2026-05-15T19:10:15.944249Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-05-15T19:07:46.733450Z digest=sha256:e9ff8b494db7dbcc233426979b67698c0a7ac99d0fbd37ed93f46bf3c59631b0

Observation 9a257408-1517-4109-bf90-71bae3402c84 · inbound

Semantic Foam: Unifying Spatial and Semantic Scene Decomposition cites this paper.

Semantic Foam: Unifying Spatial and Semantic Scene Decomposition PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 33

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verified exact
arxiv_id, observed 2026-05-12T08:51:24.050089Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-05-07T13:41:49.665324Z digest=sha256:1c0aafa563bea151d00a2d12553816abb6ef2cb9ca1b41e05f0bea995a71983c

Observation dd753582-aa67-4687-b261-63578a4a2b7b · inbound

Semantic Foam: Unifying Spatial and Semantic Scene Decomposition cites this paper.

Semantic Foam: Unifying Spatial and Semantic Scene Decomposition PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-07-01T09:25:40.303312Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-07-01T09:15:58.967751Z digest=sha256:59889e2af0503b9214a36ba3478f4ea3182ae7b3e10458f0eb3ead2172ea22c8

Observation 389e695c-3417-4308-a674-c78161ec3d6f · inbound

From Spherical to Gaussian: A Comparative Analysis of Point Cloud Cropping Strategies in Large-Scale 3D Environments cites this paper.

From Spherical to Gaussian: A Comparative Analysis of Point Cloud Cropping Strategies in Large-Scale 3D Environments PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 27

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verified exact
arxiv_id, observed 2026-05-09T06:00:34.496791Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-05-08T19:15:57.936114Z digest=sha256:c0789f21e7e5d8da7559e07972f41c8522f007ed30e28bec34b892087ca7883d

Observation 6dd3d622-bef0-4cfa-ab4e-5081efc4dab1 · inbound

From Spherical to Gaussian: A Comparative Analysis of Point Cloud Cropping Strategies in Large-Scale 3D Environments cites this paper.

From Spherical to Gaussian: A Comparative Analysis of Point Cloud Cropping Strategies in Large-Scale 3D Environments PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 27

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verified exact
local_arxiv, observed 2026-05-22T09:51:21.677027Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-05-22T09:50:31.499822Z digest=sha256:96559f39e5b17b9b0dcad9744c4df10e6c7e9d08d21d9733ca80dbe12be5cbd2

Observation c7c3111b-a2cd-45a2-ae13-1159b6e12b8d · inbound

Structural MAT: Clean and Scalable Medial Axis Simplification via Explicit Surface Correspondence cites this paper.

Structural MAT: Clean and Scalable Medial Axis Simplification via Explicit Surface Correspondence PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 119

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verified exact
arxiv_id, observed 2026-05-11T22:56:33.353895Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=arxiv_source observed=2026-05-08T02:09:48.998349Z digest=sha256:f5ec6ed28450003ed7573bdce88d7d59ff08b90e0ecd853487c5a3b483a4a319

Observation c1e18194-cfa4-4324-9deb-b4ac06348c3f · inbound

Mix3R: Mixing Feed-forward Reconstruction and Generative 3D Priors for Joint Multi-view Aligned 3D Reconstruction and Pose Estimation cites this paper.

Mix3R: Mixing Feed-forward Reconstruction and Generative 3D Priors for Joint Multi-view Aligned 3D Reconstruction and Pose Estimation PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 39

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verified exact
arxiv_id, observed 2026-05-12T10:46:31.434467Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-05-08T01:27:27.943100Z digest=sha256:067cbdaa55c475a682c3e0d7b63d27a0f325b14e492c694dee89cd6d2939151a

Observation 21e7ce9f-42e1-41a2-8f7e-0eb2d8e2a8cd · inbound

End-to-End Keyword Spotting on FPGA Using Graph Neural Networks with a Neuromorphic Auditory Sensor cites this paper.

End-to-End Keyword Spotting on FPGA Using Graph Neural Networks with a Neuromorphic Auditory Sensor PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 25

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verified exact
arxiv_id, observed 2026-05-12T02:51:17.474902Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-05-12T02:51:10.476343Z digest=sha256:0567090fa3025b530b75bb882317a1b588005eccd3cfe6669dd427568f488706

Observation 5ad38d4d-eabe-4b1e-87ca-28c8c596c124 · inbound

OPTNet: Ordering Point Transformer Network for Post-disaster 3D Semantic Segmentation cites this paper.

OPTNet: Ordering Point Transformer Network for Post-disaster 3D Semantic Segmentation PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 12

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metadata mismatch
local_arxiv, observed 2026-05-20T14:08:20.882050Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-05-20T14:08:03.033683Z digest=sha256:3ed655e85ec28c3246ce46e8fa269781d22af2c7928db9ddedb08e3ba3ef100c

Observation c80aa196-7253-48ec-a52d-e8f798135bed · inbound

Learning Representations from 3D Gaussian Splats cites this paper.

Learning Representations from 3D Gaussian Splats PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-06-29T08:43:15.410515Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-06-29T08:38:34.337340Z digest=sha256:58691b9135ac14ce0053b7e4cd24f2c63a2596d687998e7ae2f738bdd7ded1eb

Observation b64a7b13-fb30-4f22-9d19-72187f54dc08 · inbound

WHU-Infra3D: A Full-stack Multi-modal Dataset and Benchmark for 3D Roadside Infrastructure Inventory cites this paper.

WHU-Infra3D: A Full-stack Multi-modal Dataset and Benchmark for 3D Roadside Infrastructure Inventory PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 43

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malformed identifier
local_arxiv, observed 2026-07-02T07:26:45.752415Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-06-28T06:58:45.485058Z digest=sha256:ab30f8753298ec108fdbd8df55ed0927e29eaae58d1fd4f4c68211d390cb8fa2

Observation 4314d95c-755c-463f-baad-dc0f7208d3ca · inbound

Fourier Features Let Agents Learn High Precision Policies with Imitation Learning cites this paper.

Fourier Features Let Agents Learn High Precision Policies with Imitation Learning PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 34

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T08:47:50.420063Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=arxiv_source observed=2026-06-27T10:42:50.638059Z digest=sha256:5ded6b1d2b70ea374da7fe2274a8b5fe970b3e218f5d3970707965a589213ce1

Observation c66afb2e-b37e-40cc-a778-205899f3984b · inbound

Human-in-the-Loop Atlas-Based 3D Asset Segmentation for Interactive Content Workflows cites this paper.

Human-in-the-Loop Atlas-Based 3D Asset Segmentation for Interactive Content Workflows PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-07-03T19:18:54.867518Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-06-27T01:55:56.022604Z digest=sha256:a46438cbf6875f0bce142073519e7c95e57ffe485ad4d1c5f939822b0e010589

Observation 75458cab-b205-4af6-9a4d-1a7217ca89a3 · inbound

Chronos: A Physics-Informed Full-History Framework for Non-Markovian Long-Horizon Manipulation cites this paper.

Chronos: A Physics-Informed Full-History Framework for Non-Markovian Long-Horizon Manipulation PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-06-30T15:04:46.797116Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-06-30T05:12:47.183078Z digest=sha256:fe4c26c4c75e1fdcbac135ee3eacd63c563d8a70c25c84b9299cc12f9271323d

Observation 682c4393-d307-4eea-9c7e-5323f09d722f · inbound

From Grasps to Dexterity: Large-Scale Grasp Pretraining for Dexterous Manipulation cites this paper.

From Grasps to Dexterity: Large-Scale Grasp Pretraining for Dexterous Manipulation PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 49

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verified exact
local_arxiv, observed 2026-07-01T12:35:43.641118Z

Source-reported events for the cited work

Unavailable: named source frontier unavailable.

source=pdf_text observed=2026-07-01T01:59:30.986555Z digest=sha256:ea510f9cd7e993dcd743134e612df3c180426772a8406ea34fe8027af75321ea