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Paper Citation Record · LEDGER

View-Invariant Policy Learning via Zero-Shot Novel View Synthesis

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.03685.

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

pith.paper-citation-record.v1
2409.03685 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T20:30:35.868879Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:29:37.502893Z

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 4113dd4d-3deb-4639-8c61-6ddefe60b888 · inbound

WARPED: Wrist-Aligned Rendering for Robot Policy Learning from Egocentric Human Demonstrations cites this paper.

WARPED: Wrist-Aligned Rendering for Robot Policy Learning from Egocentric Human Demonstrations View-Invariant Policy Learning via Zero-Shot Novel View Synthesis

Reference 101

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:01:02.818831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T15:14:24.932972Z digest=sha256:da2e79f389d5028f3ae494accd47f8509edfb9954d5d8180653d555a81ddff98

Observation 3e4c805f-dbd9-4f90-9012-0483ab98d7c7 · inbound

DockAnywhere: Data-Efficient Visuomotor Policy Learning for Mobile Manipulation via Novel Demonstration Generation cites this paper.

DockAnywhere: Data-Efficient Visuomotor Policy Learning for Mobile Manipulation via Novel Demonstration Generation View-Invariant Policy Learning via Zero-Shot Novel View Synthesis

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-10T10:19:20.146245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T10:17:26.903231Z digest=sha256:7fe1cc045f7db73bf23da3922128bcb81133571aabecf556cadef6fe1e0c94b1

Observation 7dd2032e-ae8b-4d27-81ed-f73ae8b79d37 · inbound

VistaBot: View-Robust Robot Manipulation via Spatiotemporal-Aware View Synthesis cites this paper.

VistaBot: View-Robust Robot Manipulation via Spatiotemporal-Aware View Synthesis View-Invariant Policy Learning via Zero-Shot Novel View Synthesis

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:41:13.145235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-09T21:18:12.192842Z digest=sha256:555585d55f4ae24738a20863249d940c44f226a4575bebb2653909a6b5187b6e

Observation 4a4fda37-b3d2-4843-9aa0-cd6ec0a87549 · inbound

One Demo is Worth a Thousand Trajectories: Action-View Augmentation for Visuomotor Policies cites this paper.

One Demo is Worth a Thousand Trajectories: Action-View Augmentation for Visuomotor Policies View-Invariant Policy Learning via Zero-Shot Novel View Synthesis

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-04T01:19:20.787326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-26T20:30:35.868879Z digest=sha256:c73e00bdf661190196c237d4e97d21cf67b7ebb2784d84a7f679a99b91a446e3

Observation 6a9bc384-f000-4779-a000-cabe59ea8e3b · inbound

UniviewVLA: A Unified Multiview Vision-Language-Action Model with World Modeling cites this paper.

UniviewVLA: A Unified Multiview Vision-Language-Action Model with World Modeling View-Invariant Policy Learning via Zero-Shot Novel View Synthesis

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-04T06:29:37.504400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-26T14:27:40.585782Z digest=sha256:0bf0dc85c5788441593d20352c510da289ed64cfbf0003f6e19d6353e5913645