Paper Citation Record · LEDGER

Overcoming the Machine Penalty with Imperfectly Fair AI Agents

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.03724.

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

pith.paper-citation-record.v1
2410.03724 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:49:29.165296Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T16:41:06.195040Z

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 3f55288e-0612-4e49-8879-76ed1951f96d · inbound

Static network structure cannot stabilize cooperation among Large Language Model agents cites this paper.

Static network structure cannot stabilize cooperation among Large Language Model agents Overcoming the Machine Penalty with Imperfectly Fair AI Agents

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T19:49:29.165296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fa762ca-da0e-4f82-b2d7-9a19698b5f02 · inbound

A Survey on Large Language Model-Based Social Agents in Game-Theoretic Scenarios cites this paper.

A Survey on Large Language Model-Based Social Agents in Game-Theoretic Scenarios Overcoming the Machine Penalty with Imperfectly Fair AI Agents

Reference 124

Resolution: unresolved; no resolver link, observed 2026-08-11T21:58:46.894763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6a00816-e829-4a55-8d44-f60b5397e79d · inbound

Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers cites this paper.

Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers Overcoming the Machine Penalty with Imperfectly Fair AI Agents

Reference 167

Resolution: unresolved; no resolver link, observed 2026-08-07T22:50:33.263526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9367be0a-c0e7-4652-adfc-d574b4c63e41 · inbound

Large Language Models are Near-Optimal Decision-Makers with a Non-Human Learning Behavior cites this paper.

Large Language Models are Near-Optimal Decision-Makers with a Non-Human Learning Behavior Overcoming the Machine Penalty with Imperfectly Fair AI Agents

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T23:49:46.488288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c2a3535-e9fc-428c-b5b8-56f17b74df39 · inbound

From Digital Distrust to Codified Honesty: Experimental Evidence on Generative AI in Credence Goods Markets cites this paper.

From Digital Distrust to Codified Honesty: Experimental Evidence on Generative AI in Credence Goods Markets Overcoming the Machine Penalty with Imperfectly Fair AI Agents

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T04:34:30.757211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7e4595d-d2cd-4094-956d-b2ef5de7a74a · inbound

When Numbers Start Talking: Implicit Numerical Coordination Among LLM-Based Agents cites this paper.

When Numbers Start Talking: Implicit Numerical Coordination Among LLM-Based Agents Overcoming the Machine Penalty with Imperfectly Fair AI Agents

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-16T16:41:06.197324Z

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.