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Paper Citation Record · LEDGER

Multi-Task Learning for Dense Prediction Tasks: A Survey

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2004.13379.

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

pith.paper-citation-record.v1
2004.13379 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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:56:11.381126Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T10:33:56.190421Z

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 5265ca2e-0c2d-4c01-9ec7-27310bb27c40 · inbound

Tri-MTL: A Triple Multitask Learning Approach for Respiratory Disease Diagnosis cites this paper.

Tri-MTL: A Triple Multitask Learning Approach for Respiratory Disease Diagnosis Multi-Task Learning for Dense Prediction Tasks: A Survey

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-15T23:56:11.381126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:56:11.381126Z digest=sha256:1220cedf31c40e9fa9a207cdd48b04f7763c583e161ce934389111ce54d56930

Observation bdd55c9d-9100-488b-a672-8f6769e29a6e · inbound

Improving Vessel Segmentation with Multi-Task Learning and Auxiliary Data Available Only During Model Training cites this paper.

Improving Vessel Segmentation with Multi-Task Learning and Auxiliary Data Available Only During Model Training Multi-Task Learning for Dense Prediction Tasks: A Survey

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-05T10:33:56.294059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T10:33:54.668420Z digest=sha256:49d34a899f263485b928af488d57edaeeb75f145961c4d6cdfd1d6e3d480d898