Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-25T04:46:50.086940Z
Paper Citation Record · LEDGER
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt
As of 7 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 1 inbound Pith citation observation for arXiv:2605.23825.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T02:12:25.342418Z
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
19 of 19 outbound references displayed
- verified exact1
- verified fuzzy16
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation df6e8990-f055-429a-a981-afbcc7f909ee · outbound
This paper cites Findings of the Association for Computational Linguistics: ACL 2023 , year =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt Findings of the Association for Computational Linguistics: ACL 2023 , year =
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:17:01.441916Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c54c0229-ff60-47ad-b023-6fbc2abfa625 · outbound
This paper cites PLOS ONE , volume =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt PLOS ONE , volume =
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:17:00.313955Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 36e51cd4-5549-4444-bc58-a2aa3811015f · outbound
This paper cites Proceedings of the 40th International Conference on Machine Learning (ICML) , year =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt Proceedings of the 40th International Conference on Machine Learning (ICML) , year =
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:17:01.419431Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1dba27e5-628f-43d8-9620-41ea58941e61 · outbound
This paper cites Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL) , year =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL) , year =
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:17:01.399965Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 53757b5c-974a-4288-9dcf-e434e19ea07a · outbound
This paper cites Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models , booktitle =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models , booktitle =
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:17:01.383284Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 428442f2-7db0-4036-979d-6cdcbc651587 · outbound
This paper cites and Kizilcec, Ren.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt and Kizilcec, Ren
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:17:01.390725Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 33349a97-fd59-434d-9b19-91d37595bfe6 · outbound
This paper cites Towards Measuring the Representation of Subjective Global Opinions in Language Models.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt Towards Measuring the Representation of Subjective Global Opinions in Language Models
Reference 7
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-25T04:50:21.509185Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4b4f0469-2a00-4fb2-8172-155f10f13c8c · outbound
This paper cites and Ritter, Alan and Xu, Wei , title =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt and Ritter, Alan and Xu, Wei , title =
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:15:53.476336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 131696cb-b070-41ea-a449-4f66bf3f3377 · outbound
This paper cites Proceedings of the First Workshop on Cross-Cultural Considerations in NLP , year =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt Proceedings of the First Workshop on Cross-Cultural Considerations in NLP , year =
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:17:01.412126Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation fc938547-9014-424f-8bd3-d5acf9f9fb72 · outbound
This paper cites and Mishkin, Pamela and Zhang, Chong and Agarwal, Sandhini and Slama, Katarina and Ray, Alex and others , title =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt and Mishkin, Pamela and Zhang, Chong and Agarwal, Sandhini and Slama, Katarina and Ray, Alex and others , title =
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:17:01.432816Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation df5eb2a4-09b3-4b1f-8062-5a9c28b477bf · outbound
This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
Reference 11
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-25T04:50:21.494821Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d6922543-5504-4275-83f2-ff4a942cb0a6 · outbound
This paper cites Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback , journal =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback , journal =
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:15:53.455758Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f2fc2229-3100-4e1f-aa9c-3c6ce4a33659 · outbound
This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL) , year =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL) , year =
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:15:53.452187Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 2acc34a8-d4a0-438c-8bf2-026bdd1f9392 · outbound
This paper cites SuperCLUE: A Comprehensive Chinese Large Language Model Benchmark.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt SuperCLUE: A Comprehensive Chinese Large Language Model Benchmark
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:50:21.486415Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3735ca90-00ff-4283-93a0-98baedc86fda · outbound
This paper cites NeurIPS Datasets and Benchmarks , year =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt NeurIPS Datasets and Benchmarks , year =
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:15:53.473083Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9ef8966d-f78f-4219-9325-0977e491f7d5 · outbound
This paper cites Findings of the Association for Computational Linguistics: EMNLP 2023 , year =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt Findings of the Association for Computational Linguistics: EMNLP 2023 , year =
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:15:53.458976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ca76286c-a55a-4983-9160-ad07dec63202 · outbound
This paper cites and Narayanan, Arvind , title =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt and Narayanan, Arvind , title =
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:15:53.462830Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 7c2310ee-c663-4add-93ce-fcb8f493c571 · outbound
This paper cites and Gebru, Timnit and McMillan-Major, Angelina and Shmitchell, Shmargaret , title =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt and Gebru, Timnit and McMillan-Major, Angelina and Shmitchell, Shmargaret , title =
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:15:53.469422Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1948d9e9-1ff5-4f5f-9fc2-4f8907cf7256 · outbound
This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL) , year =.
It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL) , year =
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T13:15:53.466215Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Pith citing papers
Observation 04caf148-30d4-4fe7-b727-d6604c17401f · inbound
Estimating the Geopolitical Preferences of Large Language Models from United Nations Voting Data cites this paper.
Estimating the Geopolitical Preferences of Large Language Models from United Nations Voting Data It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T02:12:25.342418Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.