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Paper Citation Record · LEDGER

Improving Deep Regression with Ordinal Entropy

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2301.08915.

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

pith.paper-citation-record.v1
2301.08915 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 2026-08-07T05:50:25.583797Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T20:03:12.273215Z

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 0303e183-009a-414a-bbaf-2e31244ba30f · inbound

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression cites this paper.

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Improving Deep Regression with Ordinal Entropy

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T05:50:25.583797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:50:25.583797Z digest=sha256:ca250160a243cce091f02c15a6755f325e01ba9bf3b3547f0eacf24f7f5fd695

Observation d4ee894a-9b24-4bc8-9fdd-3e44fad60f28 · inbound

Hierarchical Awareness Adapters with Hybrid Pyramid Feature Fusion for Dense Depth Prediction cites this paper.

Hierarchical Awareness Adapters with Hybrid Pyramid Feature Fusion for Dense Depth Prediction Improving Deep Regression with Ordinal Entropy

Reference 67

Resolution
verified exact
arxiv_id, observed 2026-05-13T20:03:12.274461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T20:01:57.029143Z digest=sha256:bf755cfbce591111538420587084fd0583489d50852f938632657f22f4289d7b