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Paper Citation Record · LEDGER

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models

As of 15 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 2 inbound Pith citation observations for arXiv:2601.13433.

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

pith.paper-citation-record.v1
2601.13433 v4

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T09:37:10.268308Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:24:51.073476Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T03:47:15.264706Z

Reference resolution

38 of 38 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5d21b7cb-1dac-4395-ba9a-d8826d8c2876 · outbound

This paper cites Phi-4-reasoning Technical Report.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Phi-4-reasoning Technical Report

Reference 1

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source=arxiv_source observed=2026-08-03T09:37:05.721179Z digest=sha256:35568ceab667ccff19767dd37dd792899db421dc963c8dc20ab18813e0d814d9

Observation d25f8aac-fb6b-4df2-bb02-a13ca5181a34 · outbound

This paper cites Phi-4 Technical Report.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Phi-4 Technical Report

Reference 2

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source=arxiv_source observed=2026-08-03T09:37:05.815260Z digest=sha256:16ec660b3be2dc6fc8b0d3e191113cd385f38d8432df050b9d81b29082926eec

Observation da8ebb37-a938-470f-8463-3187cd46c6d5 · outbound

This paper cites Do Large Language Models Discriminate in Hiring Decisions on the Basis of Race, Ethnicity, and Gender?.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Do Large Language Models Discriminate in Hiring Decisions on the Basis of Race, Ethnicity, and Gender?

Reference 3

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source=arxiv_source observed=2026-08-03T09:37:05.953305Z digest=sha256:48f9e85d9499659ea25191bcbf7581ffd0bb4e50ffd3a2062b43db9d2bd0e709

Observation a93a7ac4-8520-4515-8179-961ec9a0f31a · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 4

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source=arxiv_source observed=2026-08-03T09:37:06.132246Z digest=sha256:712b4bf620406a34ff073c5b92511b42d226d82844044c17fb4e1473744ca445

Observation a562ccd9-5fc2-4d45-a955-d3e4caecfb2d · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 5

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source=arxiv_source observed=2026-08-03T09:37:06.240547Z digest=sha256:ceb600a399b7074534536fd361668cbf94f4f3e3c76328d2e737f11bb7d1d0ee

Observation 5641d735-1424-4009-adf0-ba2249c06512 · outbound

This paper cites Reasoning Models Don't Always Say What They Think.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Reasoning Models Don't Always Say What They Think

Reference 6

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source=arxiv_source observed=2026-08-03T09:37:06.392506Z digest=sha256:eaf462140a706aebef385ccb766f81e69bb64f11e2f8974c7bd0a3b5710f6526

Observation bcb51442-0dc3-4340-a50f-6451a75eee0e · outbound

This paper cites Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 7

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source=arxiv_source observed=2026-08-03T09:37:06.566817Z digest=sha256:96ee21a985ee53dc07695996616d7f6594f283d38cb9c540f9cad834c68993e8

Observation 54d98a2e-86a0-4610-b1ca-7311ee4804a0 · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 8

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source=arxiv_source observed=2026-08-03T09:37:06.691543Z digest=sha256:aa38160b98e69813919f04c69428faca92f9991754b20f5517fdc7f89d8ef0ce

Observation fc570ab0-0389-4a78-ae95-be940034fbc8 · outbound

This paper cites The Llama 3 Herd of Models.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models The Llama 3 Herd of Models

Reference 9

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source=arxiv_source observed=2026-08-03T09:37:06.841107Z digest=sha256:669df0421f0169a1ddeb2d1fd8f88bf23e495f27664ceee65aea2b89d318e2bf

Observation a59d28f5-8ccd-4cc4-89c8-d769d9ae1e5c · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 10

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source=arxiv_source observed=2026-08-03T09:37:06.928118Z digest=sha256:3776480389b527a4fe1530c7e0d15fed5d775615dce5a584507ce89455ec93f2

Observation 008c6eab-522e-4181-8713-264b2bb71c45 · outbound

This paper cites From CLIP to DINO: Visual Encoders Shout in Multi-modal Large Language Models.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models From CLIP to DINO: Visual Encoders Shout in Multi-modal Large Language Models

Reference 11

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source=arxiv_source observed=2026-08-03T09:37:07.017396Z digest=sha256:41ab0e1c1a5ef80ce1100a9c2a57a458862b64eb4d84727b264e0d48e4106bd6

Observation 828b5d01-0cac-4a8d-9e78-0f75baef9f86 · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 12

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source=arxiv_source observed=2026-08-03T09:37:07.176136Z digest=sha256:cdf2ae1e050c43c325589e480644786ffe11138ce6f57985e552bd06f9ca1006

Observation 2a478ea9-28e3-4ac9-a096-b53456998012 · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 13

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source=arxiv_source observed=2026-08-03T09:37:07.322523Z digest=sha256:9d893bd97b2927febb5cefb2732d9270fb2202658de5499c2eea3e8b89accff9

Observation 7d8a8bdd-0d05-4b4b-9b2b-e88884ae5224 · outbound

This paper cites Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems

Reference 14

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source=arxiv_source observed=2026-08-03T09:37:07.474668Z digest=sha256:410367d80882fdc10deac6635b3a0f56bdb871be62d97485bf3abf0b32562ab0

Observation fdfd1823-96fa-44c3-b56b-4baea6f51c1c · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 15

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source=arxiv_source observed=2026-08-03T09:37:07.695826Z digest=sha256:327e607f6fa2544f0bd95800f140ded7820e5bcdc4004a4301dabc6787fe0f1a

Observation b2892783-8bf5-4429-920f-fad8e68a0593 · outbound

This paper cites Olmo 3.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Olmo 3

Reference 16

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source=arxiv_source observed=2026-08-03T09:37:07.869083Z digest=sha256:9815009bbd8af2d67e4bc997992bc536139be1e5ac9658aa1ccaf0667cf55d64

Observation af88da1e-413b-435d-b512-d5909a498a6a · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 17

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source=arxiv_source observed=2026-08-03T09:37:07.934903Z digest=sha256:876dc25a85b624157032d1b1c3794d620f58314a277a12fc6ae2e830828ca352

Observation aee57abf-77a0-4a71-87b4-ee5e7a8def81 · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 18

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no resolver link, observed 2026-08-03T09:37:07.991857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T09:37:07.991857Z digest=sha256:b0d5e4b8f51d7e3e3cdb2e78e9368b5b51b63df21e2d82048b172a0533a63a0b

Observation d73d22e9-a44b-4c13-8df2-da658442d323 · outbound

This paper cites Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions

Reference 19

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no resolver link, observed 2026-08-03T09:37:08.086610Z

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source=arxiv_source observed=2026-08-03T09:37:08.086610Z digest=sha256:f589bc3f73e0c46efdd1da11fa4973599deef5701feea78a365ac178dd027dc6

Observation 6bbee2ad-36c6-4927-a5dc-b5e987e1e7e1 · outbound

This paper cites Verbosity bias in preference labeling by large language models.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Verbosity bias in preference labeling by large language models

Reference 20

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no resolver link, observed 2026-08-03T09:37:08.239661Z

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source=arxiv_source observed=2026-08-03T09:37:08.239661Z digest=sha256:2e6d63fbe7564f3a4c910f40f4b44c7803abd3f6dbc9f13248851865d485d3cb

Observation bfb08858-2f46-4e35-a843-d7861f6d9c5e · outbound

This paper cites Towards Understanding Sycophancy in Language Models.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Towards Understanding Sycophancy in Language Models

Reference 21

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source=arxiv_source observed=2026-08-03T09:37:08.296310Z digest=sha256:5cd77f50a0895b58a4cde994113551b11033bb6079c47e2419342a0252c938ef

Observation e1ddddc1-d160-4b58-aa76-7d2f4a6ad91f · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 22

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source=arxiv_source observed=2026-08-03T09:37:08.369775Z digest=sha256:9e7117e3112e7735c649d63b5ea2d85e5d5b17148600917ccd5e98a35929bd37

Observation 38983a24-e179-4153-8a2b-fa45c3f81008 · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 23

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no resolver link, observed 2026-08-03T09:37:08.407954Z

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source=arxiv_source observed=2026-08-03T09:37:08.407954Z digest=sha256:53ddaa02e3cf240f149d34e3831fd112fff07e8e01ae914491a25190169f1ff9

Observation b48bf7b3-6bfe-46e6-826d-b581ba9b9b08 · outbound

This paper cites Gemma 3 Technical Report.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Gemma 3 Technical Report

Reference 24

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source=arxiv_source observed=2026-08-03T09:37:08.567620Z digest=sha256:3d485699d573f7fd813fefa21d044313cfd3d77fa7984b5c60ba6088dc22c0d1

Observation f20a5797-2078-41c2-9241-cfec20f54c54 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Gemma 2: Improving Open Language Models at a Practical Size

Reference 25

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source=arxiv_source observed=2026-08-03T09:37:08.686734Z digest=sha256:9d260256401c1e1086a12f4cf4673ff857668c9947d7003678f188e5d555cf60

Observation b83146c7-8f8f-4959-82c6-287babfd3ac7 · outbound

This paper cites Qwen2 Technical Report.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Qwen2 Technical Report

Reference 26

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no resolver link, observed 2026-08-03T09:37:08.844267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T09:37:08.844267Z digest=sha256:d9f40b6cc730b2b8c407f09aba740e7692d89351f110b3fb900f3ddd95269a46

Observation 2641fbc3-a5aa-4fd9-9aa8-9011efd32b1c · outbound

This paper cites Steering Language Models With Activation Engineering.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Steering Language Models With Activation Engineering

Reference 27

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T09:37:08.958290Z digest=sha256:2ae5fc8f337b2c9b05b28073e6a9b1219ee1df1f7a1c96a095a4f8eb6ee10d90

Observation cf282eea-e072-4f2a-bb97-d9409f8d0270 · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 28

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no resolver link, observed 2026-08-03T09:37:09.135025Z

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source=arxiv_source observed=2026-08-03T09:37:09.135025Z digest=sha256:0511711bb4a06bee97ecbec0d7b6bf3602f016a0ea79704bacaad0ab28f8cbde

Observation 38f9930e-ce24-4312-8ac3-6a5e0fb3a48c · outbound

This paper cites Assessing Judging Bias in Large Reasoning Models: An Empirical Study.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Assessing Judging Bias in Large Reasoning Models: An Empirical Study

Reference 29

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T09:37:09.271466Z digest=sha256:50ad4b4b660b1d263bbecac08873097580a06d1c5f2087b677fc678023c8f07a

Observation 18624f8d-24fa-4347-b73c-342b4cd619be · outbound

This paper cites Simple synthetic data reduces sycophancy in large language models.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Simple synthetic data reduces sycophancy in large language models

Reference 30

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no resolver link, observed 2026-08-03T09:37:09.460051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T09:37:09.460051Z digest=sha256:df9249ddda8a6ba7f6b75edb3505480eef1fc29080d21826a4bdfdca81138fca

Observation 5b2b1bf0-7fb1-4fc5-a63d-3b1c6b8b978f · outbound

This paper cites Style Over Substance: Evaluation Biases for Large Language Models.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Style Over Substance: Evaluation Biases for Large Language Models

Reference 31

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T09:37:09.585094Z digest=sha256:4991eaaaf4a51aa5cd6204ba26586bf7b03777a1905a1d83b5885d1dbc32d4d1

Observation 04ff5307-4338-4ad4-a4ee-86988089c31a · outbound

This paper cites Qwen3 Technical Report.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Qwen3 Technical Report

Reference 32

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no resolver link, observed 2026-08-03T09:37:09.722754Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T09:37:09.722754Z digest=sha256:2862f0ee18081ac4bd8f83ae368da76199300ec6c7024d9eae8da3bd2ff5a470

Observation fad0bd94-75a1-4d9b-bd36-f5637a0f72cb · outbound

This paper cites Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge

Reference 33

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source=arxiv_source observed=2026-08-03T09:37:09.843449Z digest=sha256:e33d45fe3218197900ee97b0876fef439698bc84a6773ab628fdbe97a41ccd9c

Observation f64a22ed-58c7-4ca5-9b12-47bd4f1f9816 · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 34

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no resolver link, observed 2026-08-03T09:37:09.968224Z

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source=arxiv_source observed=2026-08-03T09:37:09.968224Z digest=sha256:510dcc57f84e276b11d7bde8c00c9d21cb5ca46d0a4112155febba5d6f5b13e5

Observation 4542a1b9-ea1f-4901-a382-47291d9feae4 · outbound

This paper cites an unresolved cited work.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Unresolved cited work

Reference 35

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source=arxiv_source observed=2026-08-03T09:37:10.041583Z digest=sha256:2ffb659028cd279478be2fcbd447588f608055e437a73c6473a47498a9db5b69

Observation 42e358d4-3d0a-4716-a5e5-03a89b7b2023 · outbound

This paper cites Representation Engineering: A Top-Down Approach to AI Transparency.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models Representation Engineering: A Top-Down Approach to AI Transparency

Reference 36

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source=arxiv_source observed=2026-08-03T09:37:10.113421Z digest=sha256:ceb22dfca8a4f7ccd2461ec5ff6a6c9b926b2d6ef0adcd81df8f8b4ed89e6ef2

Observation b3139033-1357-4853-b13b-d0c8cf47b5ce · outbound

This paper cites online" 'onlinestring :=.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models online" 'onlinestring :=

Reference 37

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source=arxiv_source observed=2026-08-03T09:37:10.202453Z digest=sha256:f78d82804849c5b3dcd741edb0dafb3198fa9b630c19251f616f3d8155e25b60

Observation 674cff39-3170-4387-aab2-cd27fa122f93 · outbound

This paper cites write newline.

Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models write newline

Reference 38

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source=arxiv_source observed=2026-08-03T09:37:10.268308Z digest=sha256:f67c266ba1ca1bd6b02f95536fed99818166bc431dfcd720035ee02cfd548db8

Pith citing papers

Observation 9a964381-7d4a-42a1-9c44-59012879f808 · inbound

Fragile Thoughts: How Large Language Models Handle Chain-of-Thought Perturbations cites this paper.

Fragile Thoughts: How Large Language Models Handle Chain-of-Thought Perturbations Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-28T02:04:13.719836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation de35ca0b-7e3e-46df-966c-24d164b8c7e3 · inbound

Automating and Scaling Behavioral Scientific Research on AI Agents cites this paper.

Automating and Scaling Behavioral Scientific Research on AI Agents Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models

Reference 2026

Resolution
unresolved
no resolver link, observed 2026-08-14T04:24:51.073476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:24:51.073476Z digest=sha256:b758c89319c6d3004bd17bc150df0b4963bdb6dfc998d76aa8a8bcbbd736bbc8