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Paper Citation Record · LEDGER

Large Language Models are Geographically Biased

As of 10 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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-24T04:39:51.175279Z digest=sha256:6025783cd8178f7d90506a648857163b6d20614f0cda3c4b24d694d28a3d05c0

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-23T23:55:10.846601Z digest=sha256:073260954a6cf968038aa5ef8c2234de3d76940ea1d87adca623ccb91ae701ba

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.

source=pdf_text observed=2026-08-08T11:42:07.587425Z digest=sha256:81a73d66ce5b10a535f4229a9b419add88a94cd7570824bb8678329a2b2cb681

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.

source=arxiv_source observed=2026-08-07T10:55:00.710441Z digest=sha256:a869fb604acb1e184b0138ecf8e8987a287d7585d5b03da1e0a396da47a38fc7

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.

source=arxiv_source observed=2026-08-06T14:20:39.489448Z digest=sha256:baa6ab0178e95841bdece3c6d89e87a8805576385d90d2602779d67f60fceb42

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.

source=pdf_text observed=2026-08-04T08:23:45.461318Z digest=sha256:97a3d369f71757377a857f379f047b3bb0033c5843c0aa3c31816ac682c3a09e

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.

source=pdf_text observed=2026-08-02T18:44:30.111125Z digest=sha256:366d845c86283b4452de18ae77f06ef056154fff78c78dab94a18e958e84c446

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T08:30:47.680521Z digest=sha256:5442bd1e65ab79851b47fc57db6d2ef66a94f8cb2fa7f21fe33ea4b2f14c5100

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-10T11:52:49.311085Z digest=sha256:8c3817bc5a9d3fbdccaaf0188550680ce4e7d3b0f3573d777714ac1cf74c7ee2

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T01:58:34.970947Z digest=sha256:366df040df0e9c38dddea036dfb2a42f554595519f63fbff456f6e7a3fb78335

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-05T06:19:21.376934Z digest=sha256:73bdd5d765b0629b67cc3904b99cc603ab091344f8990de0b54f691715217ea5

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-09T19:17:18.204350Z digest=sha256:2e7a7db544cbf255979316250d3f61be0b952ec4ed89f458736db21fa3a6e0d5

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-22T07:29:49.950084Z digest=sha256:25655b64962d7736109f615b4b4a5174f6a588e83e1f55a1d5b254613309e4c0

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T12:11:02.997277Z digest=sha256:91ac61cfdefac1d4be674e4cb76a8b76d569ca7059242e9dd36d61c4e8c85227

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T02:33:20.915747Z digest=sha256:14d4459242afbd2614ea416668fe435d1fb88c557bb22fe80681b080883bc3ee

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.

source=pdf_text observed=2026-07-12T22:22:51.778713Z digest=sha256:76f9f9eba6459cb24a8d2cbb5414e6eaf8925d9145f86f4af37b3204d50a579f

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T11:28:53.277638Z digest=sha256:85e71bd3158b4c300feedbf3e31779ef4a763394b85fef01b2b2f76757ae1b72

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-02T22:36:01.492596Z digest=sha256:bc205df43bf4305a3bb901c472fd62b9f38e963d0e02853f4f19f0513bde792a

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.

source=arxiv_source observed=2026-08-08T04:28:44.613179Z digest=sha256:62ff58e6e21afe1d438fbe3b4ab33748115dfb244b5f683f8cdf5f26c25e3a7e

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.

source=pdf_text observed=2026-08-08T04:17:31.810090Z digest=sha256:b058a948b1e56e2c8d81983fa8dc54018dae4b5b6db3c0c25100a6d1341d5eff