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Paper Citation Record · LEDGER

AI-AI Bias: large language models favor communications generated by large language models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.12856.

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

pith.paper-citation-record.v1
2407.12856 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 2026-08-08T17:14:45.367515Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T20:57:43.377717Z

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 b931bf52-0db3-4433-9940-26877f0b8e58 · inbound

Pencils to Pixels: A Systematic Study of Creative Drawings across Children, Adults and AI cites this paper.

Pencils to Pixels: A Systematic Study of Creative Drawings across Children, Adults and AI AI-AI Bias: large language models favor communications generated by large language models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-08T17:14:45.367515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:14:45.367515Z digest=sha256:c660a70fb2e2bd3a4afe106c66e915eba4b483f360fa5a718f2a4697f3422c82

Observation 5e0fe448-67e3-423b-a83d-cf56ea102f48 · inbound

Evaluating LLM Agent Collusion in Double Auctions cites this paper.

Evaluating LLM Agent Collusion in Double Auctions AI-AI Bias: large language models favor communications generated by large language models

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:57:43.419672Z

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=arxiv_source observed=2026-08-06T20:57:41.149357Z digest=sha256:2c93cdf30d246367a9c40a2856d6bc61f4e8dedba6f0433e1d96a8b65725245f