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Paper Citation Record · LEDGER

A large scale multi-view RGBD visual affordance learning dataset

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2203.14092.

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

pith.paper-citation-record.v1
2203.14092 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T06:28:14.882558Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 3164627b-93dc-4cb8-9ab8-297293ef054f · inbound

Filling the Pareto-Optimal Front for Affordance Segmentation on Embedded Devices Using RGB-D Cameras cites this paper.

Filling the Pareto-Optimal Front for Affordance Segmentation on Embedded Devices Using RGB-D Cameras A large scale multi-view RGBD visual affordance learning dataset

Reference 11

Resolution
unresolved
no resolver link, observed 2026-07-31T12:04:50.503444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T12:04:50.503444Z digest=sha256:f4c9df11eb74c66ef493c32f4ae2bbe0aa2bb69cee12f3ac0535bdb962e5f827

Observation 01e94916-44f7-42b0-be78-80e97d415db6 · inbound

Lightweight Neural Networks for Affordance Segmentation: Enhancement of the Decoder Module cites this paper.

Lightweight Neural Networks for Affordance Segmentation: Enhancement of the Decoder Module A large scale multi-view RGBD visual affordance learning dataset

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-03T06:28:14.882558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:14.882558Z digest=sha256:1b83f1262fede2d505cdd6aac101fbea98eb36ad4b5fe82bd7b5f15167e20eed