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Paper Citation Record · LEDGER

Instance Correction for Learning with Open-set Noisy Labels

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2106.00455.

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

pith.paper-citation-record.v1
2106.00455 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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:43:36.484987Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T16:55:17.689892Z

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 ac4b5ab6-f77c-4d55-b8be-67d94657fd36 · inbound

Open set label noise learning with robust sample selection and margin-guided module cites this paper.

Open set label noise learning with robust sample selection and margin-guided module Instance Correction for Learning with Open-set Noisy Labels

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T21:43:36.484987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T21:43:36.484987Z digest=sha256:a3bd8a0a5e40db78af261b3f47dc633058230b7760c5c452b6d5e07cf1ce5888

Observation b256e60f-81b7-4946-9496-fc89b97c94d3 · inbound

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty cites this paper.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Instance Correction for Learning with Open-set Noisy Labels

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-08T16:55:17.709828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-08T16:55:17.630941Z digest=sha256:2caa63182bffddc09e748958a988412904e4d6e72eccb7d40a110d78459a65b6