Paper Citation Record · LEDGER

Large Language Models are Geographically Biased

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2402.02680.

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

pith.paper-citation-record.v1
2402.02680 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 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 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:42:07.587425Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
metadata mismatch0

External citation measurements

13
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c8065300-b304-40cd-901e-60c3ba6bef58 · inbound

Beyond principlism: Practical strategies for ethical AI use in research practices cites this paper.

Beyond principlism: Practical strategies for ethical AI use in research practices Large Language Models are Geographically Biased

Reference 38

Resolution: metadata mismatch; arxiv_id, observed 2026-05-24T04:43:54.027425Z

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.

Observation 267c4663-ffba-473a-920a-5ce3c4020240 · inbound

Quantifying Geospatial in the Common Crawl Corpus cites this paper.

Quantifying Geospatial in the Common Crawl Corpus Large Language Models are Geographically Biased

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-23T23:55:53.615494Z

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.

Observation 5aa2272c-1d70-438c-9df5-54897d2db05d · inbound

Breaking Down Bias: On The Limits of Generalizable Pruning Strategies cites this paper.

Breaking Down Bias: On The Limits of Generalizable Pruning Strategies Large Language Models are Geographically Biased

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T11:42:07.587425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 092840db-a920-4f63-8a9d-72d3ea02516f · inbound

Around the World in 24 Hours: Probing LLM Knowledge of Time and Place cites this paper.

Around the World in 24 Hours: Probing LLM Knowledge of Time and Place Large Language Models are Geographically Biased

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T10:55:00.710441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e318d8a-5a4d-4f1f-8bd8-ee2b12cc9d1e · inbound

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning cites this paper.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Large Language Models are Geographically Biased

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T14:20:39.489448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cb5b3a0-dc0a-47fe-b5ed-240892351064 · inbound

Generating the Modal Worker: A Cross-Model Audit of Race and Gender in LLM-Generated Personas Across 41 Occupations cites this paper.

Generating the Modal Worker: A Cross-Model Audit of Race and Gender in LLM-Generated Personas Across 41 Occupations Large Language Models are Geographically Biased

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-04T08:23:45.461318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 429a166f-7dbd-4d69-989c-e5ba81e075da · inbound

The Rise of AI in Weather and Climate Information and its Impact on Global Inequality cites this paper.

The Rise of AI in Weather and Climate Information and its Impact on Global Inequality Large Language Models are Geographically Biased

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-02T18:44:30.111125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73287b02-b046-40d3-8584-a49811678085 · inbound

Geographic Blind Spots in AI Control Monitors: A Cross-National Audit of Claude Opus 4.6 cites this paper.

Geographic Blind Spots in AI Control Monitors: A Cross-National Audit of Claude Opus 4.6 Large Language Models are Geographically Biased

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T08:35:19.322049Z

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.

Observation 90c37278-9b09-4256-9c99-d97854db5293 · inbound

SPAGBias: Uncovering and Tracing Structured Spatial Gender Bias in Large Language Models cites this paper.

SPAGBias: Uncovering and Tracing Structured Spatial Gender Bias in Large Language Models Large Language Models are Geographically Biased

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:55:20.860211Z

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.

Observation 617e1157-673e-4c0f-b155-83081a3b253d · inbound

Culturally uneven urban perception in large language models cites this paper.

Culturally uneven urban perception in large language models Large Language Models are Geographically Biased

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:21:03.434063Z

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.

Observation a9f0ebdd-4a81-470f-a53e-8cc7fe788063 · inbound

Culturally uneven urban perception in large language models cites this paper.

Culturally uneven urban perception in large language models Large Language Models are Geographically Biased

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-05T06:20:44.404297Z

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.

Observation ddc9619a-7f7a-4405-8292-b127385d18b6 · inbound

Unbox Responsible GeoAI: Navigating Climate Extreme and Disaster Mapping cites this paper.

Unbox Responsible GeoAI: Navigating Climate Extreme and Disaster Mapping Large Language Models are Geographically Biased

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:46:40.716215Z

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.

Observation 7d96fa02-06b7-49de-bc69-0a52d8490796 · inbound

SDGBiasBench: Benchmarking and Mitigating Vision--Language Models' Biases in Sustainable Development Goals cites this paper.

SDGBiasBench: Benchmarking and Mitigating Vision--Language Models' Biases in Sustainable Development Goals Large Language Models are Geographically Biased

Reference 38

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T07:31:13.935718Z

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.

Observation aacb634a-2b37-46c4-8498-c4021fd61197 · inbound

Enhancing the Socioeconomic Understanding of Foundation Models with Urban Mobility cites this paper.

Enhancing the Socioeconomic Understanding of Foundation Models with Urban Mobility Large Language Models are Geographically Biased

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T01:16:25.169310Z

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.

Observation 8f32d38f-03a8-4da2-8877-f1402d5d2039 · inbound

The Geography of Algorithmic Judgment: LLM Intermediaries, Place Identity, and Racial Steering in Housing Search cites this paper.

The Geography of Algorithmic Judgment: LLM Intermediaries, Place Identity, and Racial Steering in Housing Search Large Language Models are Geographically Biased

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-06-28T02:41:31.993661Z

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.

Observation f0b9db8a-43f7-47ba-920f-acc7a1403061 · inbound

Benchmarking Open-Weight Foundation Models for Global AI Technical Governance cites this paper.

Benchmarking Open-Weight Foundation Models for Global AI Technical Governance Large Language Models are Geographically Biased

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-12T22:22:51.778713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation feb1e15d-5829-4ce5-bd75-898b27be7d3a · inbound

Multimodal and Multiscale Spatial-Temporal Semantic Search and Recommendation with AI Foundation Models cites this paper.

Multimodal and Multiscale Spatial-Temporal Semantic Search and Recommendation with AI Foundation Models Large Language Models are Geographically Biased

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-06-30T11:34:38.021247Z

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.

Observation 9c55b0ae-3f90-44c4-92e5-1e6c8a84f6f7 · inbound

Multimodal and Multiscale Spatial-Temporal Semantic Search and Recommendation with AI Foundation Models cites this paper.

Multimodal and Multiscale Spatial-Temporal Semantic Search and Recommendation with AI Foundation Models Large Language Models are Geographically Biased

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:37:25.321618Z

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.

Observation d18fcc7a-e45d-4330-bf16-aabeda9a0a7b · inbound

Mapping the City Through the Lens of Language Models cites this paper.

Mapping the City Through the Lens of Language Models Large Language Models are Geographically Biased

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T04:28:44.613179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42b63746-05fd-4fbb-be3d-fb1512eee4ae · inbound

On the missing benchmarks layer and a potential solution cites this paper.

On the missing benchmarks layer and a potential solution Large Language Models are Geographically Biased

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T04:17:31.810090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.