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Paper Citation Record · LEDGER

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering

As of 7 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2607.20487.

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

pith.paper-citation-record.v1
2607.20487 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T12:28:26.950225Z

measured 35 of 35 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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Outbound references

Observation 96af6e79-d96b-48e7-949f-51a9797bfe60 · outbound

This paper cites Social media and fake news in the 2016 elec- tion.Journal of economic perspectives, 31(2):211–236,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Social media and fake news in the 2016 elec- tion.Journal of economic perspectives, 31(2):211–236,

Reference 1

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Observation 006a2cc2-ed65-4591-89d5-786053ed7957 · outbound

This paper cites Detecting linguistic bias in govern- ment documents using large language models.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Detecting linguistic bias in govern- ment documents using large language models

Reference 7

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source=pdf_text observed=2026-08-02T12:28:23.393692Z digest=sha256:61f7331857fc51a3ebe3e04302f155c358973a3cff0ed7248f2064df966458cd

Observation 4a128925-288c-49d2-a338-0775d4c63102 · outbound

This paper cites Bias and fairness in large language models: A survey.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Bias and fairness in large language models: A survey

Reference 8

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Observation 52ec2288-cb02-4b1b-b481-53440a5c2df8 · outbound

This paper cites Selective classification for deep neural networks.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Selective classification for deep neural networks

Reference 9

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Observation 26689dc2-554c-4e3d-b46c-3adc7638ac4f · outbound

This paper cites Anah-v2: Scaling analytical hallucination annotation of large language mod- els.Advances in Neural Information Processing Systems, 37:60012–60039,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Anah-v2: Scaling analytical hallucination annotation of large language mod- els.Advances in Neural Information Processing Systems, 37:60012–60039,

Reference 10

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Observation bf6206a7-bea0-400a-9ea4-5142911f20bb · outbound

This paper cites On calibration of modern neural net- works.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering On calibration of modern neural net- works

Reference 11

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source=pdf_text observed=2026-08-02T12:28:24.053706Z digest=sha256:90c854e81c2bcc55b04fab0af4b4dd76a98ebe9d7ebd271b2da2bc0ecc4917a2

Observation 604368a1-5ebb-40ba-b482-8d653b693b6c · outbound

This paper cites Qbias - A Dataset on Media Bias in Search Queries and Query Suggestions.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Qbias - A Dataset on Media Bias in Search Queries and Query Suggestions

Reference 12

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source=pdf_text observed=2026-08-02T12:28:24.248793Z digest=sha256:51d1f42a55634c9417b5cd7414a03f9767c64593097121ab71175ca3f4d7c595

Observation 6e5b598b-6556-407a-b976-f0ca3a5e137b · outbound

This paper cites The levers of political persua- sion with conversational artificial intelligence.Science, 390(6777):eaea3884,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering The levers of political persua- sion with conversational artificial intelligence.Science, 390(6777):eaea3884,

Reference 14

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Observation 2cf18c6c-b906-4bf3-97f8-b16f0cd83496 · outbound

This paper cites Debertav3: Improving deberta using electra-style pre-training with gradient-disentangled embedding shar- ing,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Debertav3: Improving deberta using electra-style pre-training with gradient-disentangled embedding shar- ing,

Reference 15

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Observation 908467b8-e301-4109-b9cb-3e3ea7194c20 · outbound

This paper cites A survey on hallucination in large language models: Prin- ciples, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 43(2):1–55,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering A survey on hallucination in large language models: Prin- ciples, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 43(2):1–55,

Reference 16

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Observation 35ea8d15-54d3-4daf-9b3a-d22acfe80e49 · outbound

This paper cites ANAH: Analytical Annotation of Hallucinations in Large Language Models.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering ANAH: Analytical Annotation of Hallucinations in Large Language Models

Reference 17

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Observation daafe9f2-66f3-4b00-b7a1-66bb008d3ebc · outbound

This paper cites How can we know when language models know? on the calibration of language models for question answering.Transactions of the Association for Computational Linguistics, 9:962–977,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering How can we know when language models know? on the calibration of language models for question answering.Transactions of the Association for Computational Linguistics, 9:962–977,

Reference 18

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Observation 0d9771dc-8330-4b3d-9014-1e9899e64a01 · outbound

This paper cites Evaluating large language models for accuracy incentivizes hallucinations.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Evaluating large language models for accuracy incentivizes hallucinations

Reference 19

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Observation 06be5e7d-ae55-48e8-a1ad-b5884dcfd232 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in neural infor- mation processing systems, 33:9459–9474,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in neural infor- mation processing systems, 33:9459–9474,

Reference 20

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Observation 6ad94c63-5ff1-4b86-9ac5-e0836b4bad69 · outbound

This paper cites Persuad- ing voters using human–artificial intelligence dialogues.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Persuad- ing voters using human–artificial intelligence dialogues

Reference 22

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Observation a4b67cfb-8438-410a-8c3b-8bccc920d781 · outbound

This paper cites Singh, Rylan Schaeffer, Andrew Poulton, Sanmi Koyejo, Pontus Stenetorp, Sharan Narang, and Dieuwke Hupkes.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Singh, Rylan Schaeffer, Andrew Poulton, Sanmi Koyejo, Pontus Stenetorp, Sharan Narang, and Dieuwke Hupkes

Reference 23

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Observation 924b5037-f46a-4247-981c-15e6336553b4 · outbound

This paper cites an unresolved cited work.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Unresolved cited work

Reference 24

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source=pdf_text observed=2026-08-02T12:28:25.738438Z digest=sha256:28e97a940fb95ee7788baf346a02690a36e149d28828ad1c5b73765f407ff5b5

Observation b1f3512a-b123-40bc-b53f-a7458220a1f5 · outbound

This paper cites Biases in large language models: origins, in- ventory, and discussion.ACM Journal of Data and Infor- mation Quality, 15(2):1–21,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Biases in large language models: origins, in- ventory, and discussion.ACM Journal of Data and Infor- mation Quality, 15(2):1–21,

Reference 25

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Observation 206d11f4-d603-40cf-b36f-ca8892ee32ab · outbound

This paper cites RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models, May.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models, May

Reference 26

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Observation aee39b06-e140-4eb6-8d6c-28b03ac16b8a · outbound

This paper cites What large language models do not talk about: An empirical study of moderation and censorship practices,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering What large language models do not talk about: An empirical study of moderation and censorship practices,

Reference 27

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Observation e66ddec3-6ed6-4ecf-a756-132a75e366be · outbound

This paper cites https://huggingface.co/open-llm-leaderboard, March.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering https://huggingface.co/open-llm-leaderboard, March

Reference 28

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Observation b8f0d0d2-6594-45e5-a362-f5a92c84a256 · outbound

This paper cites Assessing political bias in large language models.Journal of Computational Social Sci- ence, 8(2):42, May.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Assessing political bias in large language models.Journal of Computational Social Sci- ence, 8(2):42, May

Reference 29

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Observation 5b13614d-0d6b-4c47-9d74-1789ce45335e · outbound

This paper cites Measuring Political Prefer- ences in AI Systems: An Integrative Approach, March.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Measuring Political Prefer- ences in AI Systems: An Integrative Approach, March

Reference 30

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Observation fba1fe84-d1ab-4131-9029-817e9c058ae5 · outbound

This paper cites Whose Opinions Do Language Models Re- flect?, March.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Whose Opinions Do Language Models Re- flect?, March

Reference 31

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Observation 7bad3cef-fa92-4262-a595-54632c8162cf · outbound

This paper cites The spread of true and false news online.sci- ence, 359(6380):1146–1151,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering The spread of true and false news online.sci- ence, 359(6380):1146–1151,

Reference 32

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Observation 2fcd4586-fad2-45f7-a7c6-b6eaffa61313 · outbound

This paper cites Siren’s Song in the AI Ocean: A Survey on Hallucination in Large Language Models, September.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Siren’s Song in the AI Ocean: A Survey on Hallucination in Large Language Models, September

Reference 34

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Observation 7fbebd6b-a308-4e1f-9ab2-fdb737bd0f50 · outbound

This paper cites Detained in Russia since Feb.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Detained in Russia since Feb

Reference 35

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source=pdf_text observed=2026-08-02T12:28:26.950225Z digest=sha256:76b729eec31a095605f0a81dfc9fa4db968bc4039d3bb7a485f70262a7d64fa5

Observation 912288ff-cc05-480d-bc7e-0dde209aa287 · outbound

This paper cites Llm-generated messages can persuade humans on policy issues.Nature Communications, 16(1):6037,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Llm-generated messages can persuade humans on policy issues.Nature Communications, 16(1):6037,

Reference 2017

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Observation d74352b9-a457-4a18-b2d9-0f622195751b · outbound

This paper cites Ethical and social risks of harm from Language Models.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Ethical and social risks of harm from Language Models

Reference 2018

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Observation e82371e2-3bf4-40a9-85bf-34197feac12b · outbound

This paper cites Towards trustworthy LLMs: A review on debiasing and dehallucinating in large language models.Artificial Intel- ligence Review, 57(9):243, August.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Towards trustworthy LLMs: A review on debiasing and dehallucinating in large language models.Artificial Intel- ligence Review, 57(9):243, August

Reference 2020

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Observation b3a68041-dd99-4096-9d82-eee6ed3084a5 · outbound

This paper cites Uncovering political bias in large lan- guage models using parliamentary voting records.arXiv preprint arXiv:2601.08785,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Uncovering political bias in large lan- guage models using parliamentary voting records.arXiv preprint arXiv:2601.08785,

Reference 2021

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Observation 49f2b837-1bdf-443c-b4ba-d0c7d930b995 · outbound

This paper cites Evaluating the persuasive influence of political microtargeting with large language mod- els.Proceedings of the National Academy of Sciences, 121(24):e2403116121,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Evaluating the persuasive influence of political microtargeting with large language mod- els.Proceedings of the National Academy of Sciences, 121(24):e2403116121,

Reference 2023

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Observation 5009a2b1-ca84-4d43-bc46-946b22c7e800 · outbound

This paper cites On the dangers of stochastic parrots: Can language models be too big? InProceedings of the 2021 ACM conference on fairness, accountability, and transparency, pages 610– 623,.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering On the dangers of stochastic parrots: Can language models be too big? InProceedings of the 2021 ACM conference on fairness, accountability, and transparency, pages 610– 623,

Reference 2024

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source=pdf_text observed=2026-08-02T12:28:23.095543Z digest=sha256:49245b2585216a809a953e1c66b975bda57c163d01d91d7bd2010ab54eb6c832

Observation 7f1e5a6d-fcaa-46ea-b3c3-0bd618962578 · outbound

This paper cites Measuring Political Bias in Large Language Models: What Is Said and How It Is Said.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering Measuring Political Bias in Large Language Models: What Is Said and How It Is Said

Reference 2025

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T12:28:22.925263Z digest=sha256:7d7fc99863f0ff71093784fdad5d23ce451e86e412b56f4d077fe4b919f4c911

Observation f5018958-f8d9-435b-a2ca-c989c573c39c · outbound

This paper cites The echo chamber effect on social media.ResearchGate, February.

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering The echo chamber effect on social media.ResearchGate, February

Reference 2026

Resolution
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no resolver link, observed 2026-08-02T12:28:23.280397Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-02T12:28:23.280397Z digest=sha256:32cd551821f9cdc5d1e364b2f7b05b11dd58d20563eedd353a4ab922e7ecfb06

Pith citing papers

No inbound Pith citation observations are available.