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Paper Citation Record · LEDGER

Robust Loss Functions under Label Noise for Deep Neural Networks

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1712.09482.

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

pith.paper-citation-record.v1
1712.09482 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:27:12.830564Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-24T10:59:21.514213Z

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 110a5703-ba7a-499c-b345-083d0c1d2a56 · inbound

Universal hidden monotonic trend estimation with contrastive learning cites this paper.

Universal hidden monotonic trend estimation with contrastive learning Robust Loss Functions under Label Noise for Deep Neural Networks

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-24T10:59:21.517572Z

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=pdf_text observed=2026-05-24T10:58:21.620110Z digest=sha256:4343af10490d7129e7c494eadf93f9bafe68ffadab33a1ddcbcedbed4f021c47

Observation 6a591ce6-1c8f-4f10-a830-2e9505b1ca95 · inbound

Optimal Query Allocation in Extractive QA with LLMs: A Learning-to-Defer Framework with Theoretical Guarantees cites this paper.

Optimal Query Allocation in Extractive QA with LLMs: A Learning-to-Defer Framework with Theoretical Guarantees Robust Loss Functions under Label Noise for Deep Neural Networks

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-05-23T18:53:21.380081Z

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=2026-05-23T18:49:39.718108Z digest=sha256:46fdc53d99273ca19b1942db931b8e11ec902c484e955b0e3184b27d8aeb5599

Observation a0f5775c-08c6-4a22-bea6-98a34cb01ccc · inbound

Integrating SAM Supervision for 3D Weakly Supervised Point Cloud Segmentation cites this paper.

Integrating SAM Supervision for 3D Weakly Supervised Point Cloud Segmentation Robust Loss Functions under Label Noise for Deep Neural Networks

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T15:27:12.830564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:27:12.830564Z digest=sha256:52fa3a20e003360aa4d3b328b618cf4f34d67fc2cb610f9e80febdfdb03345e8