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Paper Citation Record · LEDGER

Evolutionary Data Measures: Understanding the Difficulty of Text Classification Tasks

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1811.01910.

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

pith.paper-citation-record.v1
1811.01910 v2

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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:27:34.583284Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T15:09:58.532489Z

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 be3a4967-da54-4e5f-8e49-8540e83ada8b · inbound

Aligning Human and Machine Attention for Enhanced Supervised Learning cites this paper.

Aligning Human and Machine Attention for Enhanced Supervised Learning Evolutionary Data Measures: Understanding the Difficulty of Text Classification Tasks

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-09T11:27:34.583284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:27:34.583284Z digest=sha256:8508726f285dc7d23ec0747f1d347f88412dd6e937ce019b23ec2d65ad8b7d7e

Observation da56d67b-407a-4b2f-8cfa-def08a2c4331 · inbound

Small Language Models in the Real World: Insights from Industrial Text Classification cites this paper.

Small Language Models in the Real World: Insights from Industrial Text Classification Evolutionary Data Measures: Understanding the Difficulty of Text Classification Tasks

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:09:58.572634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T15:09:53.168566Z digest=sha256:135406726ef548225893ae7876409014efc6165993fc0275d7e340f67a9a979a