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Paper Citation Record · LEDGER

The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.11081.

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

pith.paper-citation-record.v1
2411.11081 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T18:47:07.102184Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T23:09:14.452724Z

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 1df8bac3-7cfb-4be6-852d-24257bd48bd2 · inbound

Are Large Language Models the future crowd workers of Linguistics? cites this paper.

Are Large Language Models the future crowd workers of Linguistics? The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T18:47:07.102184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:47:07.102184Z digest=sha256:ff5738eb569e98f16467debba4c5ddbf479bd6bcfa41f8bba896fe2f7480a511

Observation a5133762-0725-4d1b-8413-116d23ae1ef8 · inbound

Prosocial Behavior Detection in Player Game Chat: From Aligning Human-AI Definitions to Efficient Annotation at Scale cites this paper.

Prosocial Behavior Detection in Player Game Chat: From Aligning Human-AI Definitions to Efficient Annotation at Scale The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-05T23:09:14.516362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T23:09:09.175250Z digest=sha256:572561303e0b780f536777bf4f0bf709e81f46903e299f90818539ebd9d46a2e