Paper Citation Record · LEDGER

3D-MVP: 3D Multiview Pretraining for Robotic Manipulation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2406.18158.

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

pith.paper-citation-record.v1
2406.18158 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:59:26.711288Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T08:07:11.960048Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

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 84da3673-2a32-4842-8123-6cac36c08c2b · inbound

MapleGrasp: Mask-guided Feature Pooling for Language-driven Efficient Robotic Grasping cites this paper.

MapleGrasp: Mask-guided Feature Pooling for Language-driven Efficient Robotic Grasping 3D-MVP: 3D Multiview Pretraining for Robotic Manipulation

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T05:59:26.711288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 731497c7-ccb4-475e-b22e-434e38b58bae · inbound

Fake or Real, Can Robots Tell? Evaluating VLM Robustness to Domain Shift in Single-View Robotic Scene Understanding cites this paper.

Fake or Real, Can Robots Tell? Evaluating VLM Robustness to Domain Shift in Single-View Robotic Scene Understanding 3D-MVP: 3D Multiview Pretraining for Robotic Manipulation

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-19T08:07:11.963561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0119dd3d-dd82-4560-97fd-a4e6193e7c71 · inbound

Self-supervised Learning Of Visual Pose Estimation Without Pose Labels By Classifying LED States cites this paper.

Self-supervised Learning Of Visual Pose Estimation Without Pose Labels By Classifying LED States 3D-MVP: 3D Multiview Pretraining for Robotic Manipulation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T17:59:16.497930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e353d52-a9b9-4193-aa70-a30cdb30477e · inbound

Learning 3D Reconstruction with Priors in Test Time cites this paper.

Learning 3D Reconstruction with Priors in Test Time 3D-MVP: 3D Multiview Pretraining for Robotic Manipulation

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-13T16:48:02.665061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 096613ce-455f-43e9-89d5-57f49442f7f2 · inbound

ProGAL-VLA: Grounded Alignment through Prospective Reasoning in Vision-Language-Action Models cites this paper.

ProGAL-VLA: Grounded Alignment through Prospective Reasoning in Vision-Language-Action Models 3D-MVP: 3D Multiview Pretraining for Robotic Manipulation

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T08:30:57.276484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9fec5fc7-e303-487e-8712-84b8de551f9b · inbound

R3D: Revisiting 3D Policy Learning cites this paper.

R3D: Revisiting 3D Policy Learning 3D-MVP: 3D Multiview Pretraining for Robotic Manipulation

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:00:04.210783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.