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Paper Citation Record · LEDGER

Are standard Object Segmentation models sufficient for Learning Affordance Segmentation?

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2107.02095.

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

pith.paper-citation-record.v1
2107.02095 v1

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:39:59.083244Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T11:01:31.657440Z

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 3a4e260f-7f9b-4e77-95c4-635d41025f14 · inbound

Weakly-Supervised Affordance Grounding Guided by Part-Level Semantic Priors cites this paper.

Weakly-Supervised Affordance Grounding Guided by Part-Level Semantic Priors Are standard Object Segmentation models sufficient for Learning Affordance Segmentation?

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T12:39:59.083244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:39:59.083244Z digest=sha256:2e3b79eae6d57eaa80428e8590a62af36e847a17a9c0408a109278f4fa774d7d

Observation e06b3855-eef4-49dd-a8bc-eee8ef85b470 · inbound

Uncertainty Estimation in Instance Segmentation of Affordances via Bayesian Visual Transformers cites this paper.

Uncertainty Estimation in Instance Segmentation of Affordances via Bayesian Visual Transformers Are standard Object Segmentation models sufficient for Learning Affordance Segmentation?

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-12T11:01:31.659376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T17:57:56.570383Z digest=sha256:05a4849e42592c4b2220670cc2d13aeebb72db6783f3e3325a3818e397d89e46