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Paper Citation Record · LEDGER

Rater State Bias in RLHF Preference Data: An Audit Framework

As of 15 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2607.16195.

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

pith.paper-citation-record.v1
2607.16195 v2

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T16:22:43.961967Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

64 of 64 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved57
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 084d44c5-e294-425d-915c-b488beef04f5 · outbound

This paper cites Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei.

Rater State Bias in RLHF Preference Data: An Audit Framework Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei

Reference 1

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source=pdf_text observed=2026-08-02T16:22:43.816602Z digest=sha256:aa7bdb431b72f183053aa5e47185619f3f0de5e303833095d4f97015aa5dc997

Observation 1c17dd9a-bd2e-41fd-87eb-f00f3d48659c · outbound

This paper cites Training language models to follow instructions with human feedback.

Rater State Bias in RLHF Preference Data: An Audit Framework Training language models to follow instructions with human feedback

Reference 2

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source=pdf_text observed=2026-08-02T16:22:43.819806Z digest=sha256:8128793a70f4a36ee8307bd27b2d6bab69d576d3f7dcfb685c72b20619b9bf5e

Observation 838797b2-39b5-4fe3-af65-0c8c3157c4f1 · outbound

This paper cites an unresolved cited work.

Rater State Bias in RLHF Preference Data: An Audit Framework Unresolved cited work

Reference 3

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source=pdf_text observed=2026-08-02T16:22:43.822119Z digest=sha256:0e894a02cce6d1498a06a9ce27c3eda66123aa589ff9360729f7467081cb6135

Observation 05089b5a-d15f-4c47-87c2-df4a91aa4dbe · outbound

This paper cites NLPo- sitionality: Characterizing design biases of datasets and models.

Rater State Bias in RLHF Preference Data: An Audit Framework NLPo- sitionality: Characterizing design biases of datasets and models

Reference 4

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source=pdf_text observed=2026-08-02T16:22:43.824952Z digest=sha256:8f322682cd7e3716cdbb7f63483e185f9c6bc8d8772d820445c975385be129b6

Observation f2fcf41c-f25e-4192-b40e-8a250c190a85 · outbound

This paper cites Gordon, Michelle S.

Rater State Bias in RLHF Preference Data: An Audit Framework Gordon, Michelle S

Reference 5

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source=pdf_text observed=2026-08-02T16:22:43.827349Z digest=sha256:ed22f99f0e270e5a97cfa27c43ad525e872b4c5237470267d9583e0f4706c8c5

Observation f04f14b4-3fa5-4eb9-b1b6-72a142774208 · outbound

This paper cites Truth is a lie: Crowd truth and the seven myths of human annotation.AI Magazine, 36(1):15–24, 2015.

Rater State Bias in RLHF Preference Data: An Audit Framework Truth is a lie: Crowd truth and the seven myths of human annotation.AI Magazine, 36(1):15–24, 2015

Reference 6

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source=pdf_text observed=2026-08-02T16:22:43.831944Z digest=sha256:47b6acde45828bad4c9c253ba14822c62a088a37182302cfe22c25299221bba5

Observation 3af34338-b788-4208-91ed-1e8d1ecf0d8f · outbound

This paper cites The “problem” of human label variation: On ground truth in data, modeling and evaluation.

Rater State Bias in RLHF Preference Data: An Audit Framework The “problem” of human label variation: On ground truth in data, modeling and evaluation

Reference 7

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source=pdf_text observed=2026-08-02T16:22:43.834517Z digest=sha256:a5d3ac6f85a4d48ea672e295696b608c2b0da31c376016d23acf95493466c5c2

Observation ede7f414-bae7-4ff3-af50-907bebd9e89e · outbound

This paper cites Dealing with dis- agreements: Looking beyond the majority vote in subjective annotations.Transactions of the Association for Computational Linguistics, 10:92–110, 2022.

Rater State Bias in RLHF Preference Data: An Audit Framework Dealing with dis- agreements: Looking beyond the majority vote in subjective annotations.Transactions of the Association for Computational Linguistics, 10:92–110, 2022

Reference 8

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source=pdf_text observed=2026-08-02T16:22:43.836967Z digest=sha256:8cd5a28479f3fd22742305cbbe2ecea9b89ae7235f022bae7403a6c8fd2748b5

Observation 62355181-bc2b-4d37-a12e-3c4338c7388f · outbound

This paper cites Gray and Siddharth Suri.Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass.

Rater State Bias in RLHF Preference Data: An Audit Framework Gray and Siddharth Suri.Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass

Reference 9

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source=pdf_text observed=2026-08-02T16:22:43.839738Z digest=sha256:341c9cb153fd6701cf027a240f4893683edbc370c55764017c5de13e7ec4506a

Observation 73966c39-c097-414d-9490-5d97e5ca70b9 · outbound

This paper cites Roberts.Behind the Screen: Content Moderation in the Shadows of Social Media.

Rater State Bias in RLHF Preference Data: An Audit Framework Roberts.Behind the Screen: Content Moderation in the Shadows of Social Media

Reference 10

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source=pdf_text observed=2026-08-02T16:22:43.841881Z digest=sha256:a0aa351aa64c1de6564c4724a395c187144c248ee780a3b70be689842153de6b

Observation ca714fd2-f0c1-409a-84ec-3fdd7dd4b881 · outbound

This paper cites Incorporating worker perspectives into MTurk annotation practices for NLP.

Rater State Bias in RLHF Preference Data: An Audit Framework Incorporating worker perspectives into MTurk annotation practices for NLP

Reference 11

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source=pdf_text observed=2026-08-02T16:22:43.843986Z digest=sha256:eafa8673996216fd344bfafe0c790300898372d8b14fe5eff627c38976e82a62

Observation 16e0434f-9546-4ef5-87ca-280826a39a01 · outbound

This paper cites Analyzing dataset anno- tation quality management in the wild.Computational Linguistics, 50(3):817–866, September.

Rater State Bias in RLHF Preference Data: An Audit Framework Analyzing dataset anno- tation quality management in the wild.Computational Linguistics, 50(3):817–866, September

Reference 12

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source=pdf_text observed=2026-08-02T16:22:43.846420Z digest=sha256:3b45adb255bed0405d08552ef9653b2356c965d6483cfb5d076ae1242a7356b4

Observation c4a97cfa-2167-448e-95a6-de2396d1b732 · outbound

This paper cites Discovering Language Model Behaviors with Model-Written Evaluations.

Rater State Bias in RLHF Preference Data: An Audit Framework Discovering Language Model Behaviors with Model-Written Evaluations

Reference 13

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source=pdf_text observed=2026-08-02T16:22:43.850952Z digest=sha256:cbe5ed0f9b442922bea9e4399aeadcaa9b015add77f323bd1c8905a16782198e

Observation 04bb209c-e75c-4d06-a5ca-91007072748d · outbound

This paper cites Towards Understanding Sycophancy in Language Models.

Rater State Bias in RLHF Preference Data: An Audit Framework Towards Understanding Sycophancy in Language Models

Reference 14

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source=pdf_text observed=2026-08-02T16:22:43.853514Z digest=sha256:e9e8a7d9733d63aad80d5fd701bc961f2285fe68f3b4182bb14e0cde0795622d

Observation 078accd6-2358-4db9-8db6-8aaa86422955 · outbound

This paper cites Procaccia.

Rater State Bias in RLHF Preference Data: An Audit Framework Procaccia

Reference 15

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source=pdf_text observed=2026-08-02T16:22:43.856125Z digest=sha256:b6ff3b5b2202f39e2e2ec8c3a52d36925a4a9900f6e8a3d7f34ccbe5d71360db

Observation 9f172cd5-dace-4aed-9541-6d3a8c27824b · outbound

This paper cites A survey on intersectional fairness in machine learning: Notions, mitigation, and challenges.

Rater State Bias in RLHF Preference Data: An Audit Framework A survey on intersectional fairness in machine learning: Notions, mitigation, and challenges

Reference 16

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source=pdf_text observed=2026-08-02T16:22:43.858377Z digest=sha256:abec6bdc768cc5715aefb991e2cfdea762ecafac160d7a10c25ce95a0365ff4d

Observation d3c5f64d-7351-4b6b-9c7d-d17dcc66250c · outbound

This paper cites Scaling laws for reward model overopti- mization.

Rater State Bias in RLHF Preference Data: An Audit Framework Scaling laws for reward model overopti- mization

Reference 17

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source=pdf_text observed=2026-08-02T16:22:43.860923Z digest=sha256:328cc0ae5865c6610aa7674a46481e6c49b50c8a4ca647bcb49f8ac451d52f8c

Observation c101aeed-a13c-4375-bc23-474edfb88b27 · outbound

This paper cites Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms.

Rater State Bias in RLHF Preference Data: An Audit Framework Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms

Reference 18

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source=pdf_text observed=2026-08-02T16:22:43.863555Z digest=sha256:68ff2096a9cd3fb98d8aee4cbad31842901009ba5e1a8bd340c90e3442343490

Observation 5cbb23cb-9415-4682-84ef-57d145869c67 · outbound

This paper cites Men also like shopping: Reducing gender bias amplification using corpus-level constraints.

Rater State Bias in RLHF Preference Data: An Audit Framework Men also like shopping: Reducing gender bias amplification using corpus-level constraints

Reference 19

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source=pdf_text observed=2026-08-02T16:22:43.866634Z digest=sha256:fa9bcc15385013dba904378bcd05f987f34cd1fc07eb9b3712b2667519c0c646

Observation 3c450bc8-9232-4ac7-a061-45d7681b9cdc · outbound

This paper cites Directional bias amplification.

Rater State Bias in RLHF Preference Data: An Audit Framework Directional bias amplification

Reference 20

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source=pdf_text observed=2026-08-02T16:22:43.868680Z digest=sha256:2f8f50d8888c02d6fbd00a0a06be8f17ac33e211cf504d74ad297d6174f798f2

Observation b3acaeac-c525-4fc9-b1c8-b8a5b32a3757 · outbound

This paper cites A Systematic Study of Bias Amplification.

Rater State Bias in RLHF Preference Data: An Audit Framework A Systematic Study of Bias Amplification

Reference 21

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source=pdf_text observed=2026-08-02T16:22:43.870674Z digest=sha256:2302c9ddc84e771825ff90a3db777b3bdc6367bff645454ef1432f79b40ccfa6

Observation e7af49f6-515f-4ccc-bb2a-a0271021b1e9 · outbound

This paper cites An Effective Theory of Bias Amplification.

Rater State Bias in RLHF Preference Data: An Audit Framework An Effective Theory of Bias Amplification

Reference 22

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source=pdf_text observed=2026-08-02T16:22:43.873098Z digest=sha256:c452555fdbcb6a92b2c958667cce9947e28dedbde48cda69f450470ff6ad3d18

Observation cc998d77-1e6c-40d0-aebb-6d64d9e6efa7 · outbound

This paper cites Pennebaker, Ryan L.

Rater State Bias in RLHF Preference Data: An Audit Framework Pennebaker, Ryan L

Reference 23

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Observation 6ba803b2-bf2d-49ab-8c4c-55a19c48fd0b · outbound

This paper cites an unresolved cited work.

Rater State Bias in RLHF Preference Data: An Audit Framework Unresolved cited work

Reference 24

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source=pdf_text observed=2026-08-02T16:22:43.877484Z digest=sha256:7925187741e2deab3f9e6df4c5d8377d266a53389ed00b5e77ec285ecedb14c5

Observation d28a753e-9ab8-4a50-b1b4-29f3107b9943 · outbound

This paper cites Mohammad and Peter D.

Rater State Bias in RLHF Preference Data: An Audit Framework Mohammad and Peter D

Reference 25

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source=pdf_text observed=2026-08-02T16:22:43.879812Z digest=sha256:bcd4c2dd207f22633f4021c3a01c17344d0b7d11b9680245b36278a9a5b79105

Observation 1ac62b7a-f5b9-4304-ba0b-b953f8eb2701 · outbound

This paper cites GoEmotions: A dataset of fine-grained emotions.

Rater State Bias in RLHF Preference Data: An Audit Framework GoEmotions: A dataset of fine-grained emotions

Reference 26

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source=pdf_text observed=2026-08-02T16:22:43.882036Z digest=sha256:36380d2db7accc7ad6e860754baf6b24224766ad7c499af23be73642577bc76b

Observation d645810e-e238-4cd2-8dbf-618fd1560f92 · outbound

This paper cites Towards empa- thetic open-domain conversation models: A new benchmark and dataset.

Rater State Bias in RLHF Preference Data: An Audit Framework Towards empa- thetic open-domain conversation models: A new benchmark and dataset

Reference 27

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source=pdf_text observed=2026-08-02T16:22:43.884189Z digest=sha256:613396bac01f67152082c44fbd69307820fe46b687dc8c0ff0f799c6e4cac461

Observation 2eae4f2c-d52f-4b5c-b74b-ce42caaec621 · outbound

This paper cites Basic Books, 1969.

Rater State Bias in RLHF Preference Data: An Audit Framework Basic Books, 1969

Reference 28

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source=pdf_text observed=2026-08-02T16:22:43.886207Z digest=sha256:5791c4a65f64f16962ef4ab91cf231184519809839e3dfc705e7279ec3c5d2b4

Observation f5954eb4-91f9-4d6b-b93b-14cd742ed739 · outbound

This paper cites Shaver, and Daphna Pereg.

Rater State Bias in RLHF Preference Data: An Audit Framework Shaver, and Daphna Pereg

Reference 29

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-02T16:22:43.888483Z digest=sha256:cb88a9eb6f3dd4fed016e37e61c928480547b20e69b6f2fb3f8810ef1fb28f8f

Observation 3a301433-c54e-4fb8-9c35-6a262111ec4c · outbound

This paper cites an unresolved cited work.

Rater State Bias in RLHF Preference Data: An Audit Framework Unresolved cited work

Reference 30

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source=pdf_text observed=2026-08-02T16:22:43.890793Z digest=sha256:9f29cc097f90260b7788987cac73c8ed3071c4fc9e43dff8790eae444b2bca22

Observation 55d6efff-048b-40a1-bdf3-f149476a9b01 · outbound

This paper cites an unresolved cited work.

Rater State Bias in RLHF Preference Data: An Audit Framework Unresolved cited work

Reference 31

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source=pdf_text observed=2026-08-02T16:22:43.892636Z digest=sha256:9db1df344970094d41e7d40e4a2903222aa1ea0bd953a6f2aa59636888d52d73

Observation c16e0f71-701a-4044-9096-e9ae3a974496 · outbound

This paper cites an unresolved cited work.

Rater State Bias in RLHF Preference Data: An Audit Framework Unresolved cited work

Reference 32

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source=pdf_text observed=2026-08-02T16:22:43.894564Z digest=sha256:a94df3fcd4bab4e69c427399d3f46543770856f45b498fb1950acdac920ad8ae

Observation 614d75bf-8c0c-48a2-a645-8bffe771d031 · outbound

This paper cites Truax and Robert R.

Rater State Bias in RLHF Preference Data: An Audit Framework Truax and Robert R

Reference 33

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source=pdf_text observed=2026-08-02T16:22:43.896701Z digest=sha256:b1be8f696b03268ec323f11dfae26d5254b5bd07c74ea64e128fbeead1f331b4

Observation 0305f818-b175-4cd4-920e-e8efeb7aebd0 · outbound

This paper cites Stern.The Interpersonal World of the Infant.

Rater State Bias in RLHF Preference Data: An Audit Framework Stern.The Interpersonal World of the Infant

Reference 34

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source=pdf_text observed=2026-08-02T16:22:43.898531Z digest=sha256:ee725593b0b85b4121f90573036f98686b7a0f34707e66eca3549939495b1622

Observation dd600a0b-a0c2-4a1b-8a81-991827375c16 · outbound

This paper cites Feeney and Nancy L.

Rater State Bias in RLHF Preference Data: An Audit Framework Feeney and Nancy L

Reference 35

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source=pdf_text observed=2026-08-02T16:22:43.900468Z digest=sha256:daae510b0882fd6090115d70257a5b22b1183c641820319396a83342dd55bbf4

Observation 3ae04b27-e69d-4d16-a4b7-8963835c34c1 · outbound

This paper cites an unresolved cited work.

Rater State Bias in RLHF Preference Data: An Audit Framework Unresolved cited work

Reference 36

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source=pdf_text observed=2026-08-02T16:22:43.902232Z digest=sha256:af705b35c0a87bf4fbbdfe2b7a0c6cc8052cee4441f3ab1ce2a845dbe0c0d832

Observation 40e6dc80-0923-4c83-b7cf-0f3015506024 · outbound

This paper cites Exclusive: OpenAI used kenyan workers on less than$2 per hour to make ChatGPT less toxic, January 2023.

Rater State Bias in RLHF Preference Data: An Audit Framework Exclusive: OpenAI used kenyan workers on less than$2 per hour to make ChatGPT less toxic, January 2023

Reference 37

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source=pdf_text observed=2026-08-02T16:22:43.904650Z digest=sha256:da1c7f698a90065f02aeb8cffd3cf79e46caad6bc42a9d102940dccb074a34f6

Observation d0b5ea29-34c7-4473-8085-db6cc0910a2f · outbound

This paper cites Kenyan workers with AI jobs thought they had tickets to the future until the grim reality set in, November 2024.

Rater State Bias in RLHF Preference Data: An Audit Framework Kenyan workers with AI jobs thought they had tickets to the future until the grim reality set in, November 2024

Reference 38

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source=pdf_text observed=2026-08-02T16:22:43.906587Z digest=sha256:0f8fe23cf894a78ee74253495440e5ff8a0b38bc8e8ca6f2c2cd185c0294f6c4

Observation 40a1e518-2b40-495d-9109-a8d025d86529 · outbound

This paper cites SF tech startup Scale AI, worth$13.8b, accused of widespread wage theft, December 2024.

Rater State Bias in RLHF Preference Data: An Audit Framework SF tech startup Scale AI, worth$13.8b, accused of widespread wage theft, December 2024

Reference 39

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source=pdf_text observed=2026-08-02T16:22:43.908326Z digest=sha256:cb22731f1768fa224b4886903b56476aaccefbc3ca677d69740dded6731b9f0e

Observation a11c5c7b-5d03-4788-adaa-6879185f201c · outbound

This paper cites What is an intracluster correlation coef- ficient? crucial concepts for primary care researchers.The Annals of Family Medicine, 2(3): 204–208, 2004.

Rater State Bias in RLHF Preference Data: An Audit Framework What is an intracluster correlation coef- ficient? crucial concepts for primary care researchers.The Annals of Family Medicine, 2(3): 204–208, 2004

Reference 40

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source=pdf_text observed=2026-08-02T16:22:43.910334Z digest=sha256:739a072e28977e2a56827b090856f071292a6c17c91093b2f5dfa6d52b2ff548

Observation 98a5743c-b42c-43f1-8743-80cc040278d4 · outbound

This paper cites John Wiley & Sons, New York, 1965.

Rater State Bias in RLHF Preference Data: An Audit Framework John Wiley & Sons, New York, 1965

Reference 41

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source=pdf_text observed=2026-08-02T16:22:43.912329Z digest=sha256:96df54abf21d19726e64e89eae3108be37210959c53a76772a32562d33d4a405

Observation 569fea05-c1c7-4857-b135-3cafd5cc7d03 · outbound

This paper cites Thompson, Douglas H.

Rater State Bias in RLHF Preference Data: An Audit Framework Thompson, Douglas H

Reference 42

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-02T16:22:43.914130Z digest=sha256:0f33b9c679c1e40daa77fd1043188a2d3f77847f4d17a528b1e428214e72a012

Observation 9be8f67b-cfee-4408-b03c-c889f152c5f3 · outbound

This paper cites an unresolved cited work.

Rater State Bias in RLHF Preference Data: An Audit Framework Unresolved cited work

Reference 43

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-02T16:22:43.916499Z digest=sha256:b59188088999641f299bc734c65a09b811acf901dd6b63464c6f089c97a64d1a

Observation 114e80ec-929d-4fed-a94a-67ab4e386bdb · outbound

This paper cites Deep Learning is Robust to Massive Label Noise.

Rater State Bias in RLHF Preference Data: An Audit Framework Deep Learning is Robust to Massive Label Noise

Reference 44

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-02T16:22:43.918789Z digest=sha256:832d111ba9882e4c3aa9c88851f669d23346bf4526b36a9f08ec1513e87adac3

Observation cdbb0533-4d06-45b9-a71c-49bbbe02b012 · outbound

This paper cites Dhillon, Pradeep K.

Rater State Bias in RLHF Preference Data: An Audit Framework Dhillon, Pradeep K

Reference 45

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source=pdf_text observed=2026-08-02T16:22:43.921124Z digest=sha256:e5959efaa70ef6279f963d8bb4724c1f51a2cc6f9d64714add0315e6cc1054b9

Observation 17c0234a-babc-4955-955f-17dc5c3ba8c0 · outbound

This paper cites Learning from noisy labels with deep neural networks: A survey.IEEE Transactions on Neural Networks and Learning Systems, 34(11):8135–8153, 2023.

Rater State Bias in RLHF Preference Data: An Audit Framework Learning from noisy labels with deep neural networks: A survey.IEEE Transactions on Neural Networks and Learning Systems, 34(11):8135–8153, 2023

Reference 46

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source=pdf_text observed=2026-08-02T16:22:43.925958Z digest=sha256:ded483e54415c357353aaee1654941d4353766ac217ddebf545fdd8d4654eebe

Observation 48634d05-a5de-47f4-b151-7d97aea37079 · outbound

This paper cites Bharucha, Sukrit Venkatagiri, Martin J.

Rater State Bias in RLHF Preference Data: An Audit Framework Bharucha, Sukrit Venkatagiri, Martin J

Reference 47

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source=pdf_text observed=2026-08-02T16:22:43.928812Z digest=sha256:c04112ea5ba05134d941fe499b44cdf6fb0c369e8ba6f06064b235176a92121f

Observation 3968aab4-6931-43d4-849c-0a64d71f3c9f · outbound

This paper cites ‘it’s destroyed me completely’: Kenyan moderators decry toll of training of AI models, August 2023.

Rater State Bias in RLHF Preference Data: An Audit Framework ‘it’s destroyed me completely’: Kenyan moderators decry toll of training of AI models, August 2023

Reference 48

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source=pdf_text observed=2026-08-02T16:22:43.931017Z digest=sha256:c9ebd50705a70bc29f9aaf9a728fc389de048fd743cb7c300a55ee4636c6b844

Observation 10d13d61-9499-4106-b0c6-668458e87668 · outbound

This paper cites Kim, David K.

Rater State Bias in RLHF Preference Data: An Audit Framework Kim, David K

Reference 49

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source=pdf_text observed=2026-08-02T16:22:43.933129Z digest=sha256:f574783fd464597580d7d3dee33671a1ace4531f053190755464bd2eb5aaa8ea

Observation 6abdc2c6-cd85-4d17-bbf5-44bc97196052 · outbound

This paper cites an unresolved cited work.

Rater State Bias in RLHF Preference Data: An Audit Framework Unresolved cited work

Reference 50

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-02T16:22:43.935320Z digest=sha256:24c09125a3b0988d257b15cf4251516a49c585956303bfcf505070f33d199c62

Observation f10761a4-5f7c-4bfb-be2e-3ee7c97c3056 · outbound

This paper cites On the universality and cultural specificity of emotion recognition: A meta-analysis.Psychological Bulletin, 128(2):203–235, 2002.

Rater State Bias in RLHF Preference Data: An Audit Framework On the universality and cultural specificity of emotion recognition: A meta-analysis.Psychological Bulletin, 128(2):203–235, 2002

Reference 51

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source=pdf_text observed=2026-08-02T16:22:43.937699Z digest=sha256:6f83bee3442ee5a0a018279f920b8f7f44b00408f864544ce31c45b4f3cfd478

Observation 15230fa5-cbcd-4983-a875-d9061c5145c1 · outbound

This paper cites Heine, and Ara Norenzayan.

Rater State Bias in RLHF Preference Data: An Audit Framework Heine, and Ara Norenzayan

Reference 52

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source=pdf_text observed=2026-08-02T16:22:43.940104Z digest=sha256:ce4f993f88b238a5cdac678a8a33fdd462e8f54936377c81592d84d2d624c420

Observation 1a07ba85-303a-4629-8c93-00e17026092e · outbound

This paper cites The GPT-4o shock: Emotional attachment to AI models and its impact on regulatory acceptance: A cross-cultural analysis of the immediate transition from GPT-4o to GPT-5, 2025.

Rater State Bias in RLHF Preference Data: An Audit Framework The GPT-4o shock: Emotional attachment to AI models and its impact on regulatory acceptance: A cross-cultural analysis of the immediate transition from GPT-4o to GPT-5, 2025

Reference 53

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source=pdf_text observed=2026-08-02T16:22:43.942251Z digest=sha256:650dc924720a8c77626ee89bbeaad76417ea3094f8d297b201c7d281d328e712

Observation b0284220-2b6c-419a-abdd-99d935bda08a · outbound

This paper cites The backlash over OpenAI’s decision to retire GPT-4o shows how danger- ous AI companions can be, February 2026.

Rater State Bias in RLHF Preference Data: An Audit Framework The backlash over OpenAI’s decision to retire GPT-4o shows how danger- ous AI companions can be, February 2026

Reference 54

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source=pdf_text observed=2026-08-02T16:22:43.944311Z digest=sha256:c0bd86e4f8a102e3b8f21db20592d9e08e383c7e36fcde3f064e77329459e4d3

Observation fd27ff06-3ae9-4c25-a211-9066c38ee42d · outbound

This paper cites Barsalou.

Rater State Bias in RLHF Preference Data: An Audit Framework Barsalou

Reference 55

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source=pdf_text observed=2026-08-02T16:22:43.946319Z digest=sha256:ea7bef49c76ae737cb5ddda22b9b817778a0c8927e74d10b85626be2cba910ca

Observation 0887bbb8-331d-40bb-b304-c7a76969be59 · outbound

This paper cites Feelings-as-information theory.

Rater State Bias in RLHF Preference Data: An Audit Framework Feelings-as-information theory

Reference 56

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source=pdf_text observed=2026-08-02T16:22:43.948415Z digest=sha256:d3591a95462491cab6f55165a15a5735317a85e73d096b0d994b00a99bfa7942

Observation 4564dc3c-3a6d-4949-9d12-f2e1694c0d0a · outbound

This paper cites When human-AI interactions become parasocial.

Rater State Bias in RLHF Preference Data: An Audit Framework When human-AI interactions become parasocial

Reference 57

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source=pdf_text observed=2026-08-02T16:22:43.950760Z digest=sha256:057a56dc18d94804ef6950bafbf5f08005e49f3d7e87b10066e60a67edb511aa

Observation c05c9c1a-cba9-4649-9876-235b98f50186 · outbound

This paper cites Continuum, 2005.

Rater State Bias in RLHF Preference Data: An Audit Framework Continuum, 2005

Reference 58

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source=pdf_text observed=2026-08-02T16:22:43.953334Z digest=sha256:8007200e1a7b08d44692a36bedd85e1011988f36de30279c7328d72d26c3526d

Observation c838e419-26ba-472c-87e3-c20d242c2968 · outbound

This paper cites Dailydialog: A manually labelled multi-turn dialogue dataset.

Rater State Bias in RLHF Preference Data: An Audit Framework Dailydialog: A manually labelled multi-turn dialogue dataset

Reference 59

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source=pdf_text observed=2026-08-02T16:22:43.955314Z digest=sha256:53c84243ee3fffafe90dcf656710de71356659862f28a986dd8d0f341bd961c9

Observation 2791cd16-ca4a-49e8-b3a7-033d30f686f5 · outbound

This paper cites How AI and Human Behaviors Shape Psychosocial Effects of Extended Chatbot Use: A Longitudinal Randomized Controlled Study.

Rater State Bias in RLHF Preference Data: An Audit Framework How AI and Human Behaviors Shape Psychosocial Effects of Extended Chatbot Use: A Longitudinal Randomized Controlled Study

Reference 60

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source=pdf_text observed=2026-08-02T16:22:43.958241Z digest=sha256:fcf3ee6e9598859f3743b53f007c3939b6fea90c1aebcdc9947aab6bc7200785

Observation f1882e12-ff35-475b-8e79-8631ca515a65 · outbound

This paper cites Investigating Affective Use and Emotional Well-being on ChatGPT.

Rater State Bias in RLHF Preference Data: An Audit Framework Investigating Affective Use and Emotional Well-being on ChatGPT

Reference 61

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source=pdf_text observed=2026-08-02T16:22:43.961967Z digest=sha256:b97fe94f749eebcdfdd346418bbeb3f58ba54d9718378e0c6aeb06c1e9a2cdce

Observation 9b537275-6c1e-4f81-9ce2-38c3dd86324a · outbound

This paper cites an unresolved cited work.

Rater State Bias in RLHF Preference Data: An Audit Framework Unresolved cited work

Reference 2013

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source=pdf_text observed=2026-08-02T16:22:43.923727Z digest=sha256:8fd6437e0ae6c6e313afa8d47524c5237851530cef5a949c1f8cdc204cc7b7f7

Observation 4823dbd9-dc98-4276-bcbc-c8982578e3bd · outbound

This paper cites an unresolved cited work.

Rater State Bias in RLHF Preference Data: An Audit Framework Unresolved cited work

Reference 2022

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source=pdf_text observed=2026-08-02T16:22:43.829641Z digest=sha256:18042f24ab9cddcfd6553551fe81f229af50ca49f6267dd4a22426ed219d15c7

Observation fa7504ad-88c7-413b-b7bc-d3c5fde75226 · outbound

This paper cites URL https://aclanthology.org/2024.cl-3.1/.

Rater State Bias in RLHF Preference Data: An Audit Framework URL https://aclanthology.org/2024.cl-3.1/

Reference 2024

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no resolver link, observed 2026-08-02T16:22:43.848580Z

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source=pdf_text observed=2026-08-02T16:22:43.848580Z digest=sha256:55e6358bfa04c15d52f79a7504dcab22f22285930bec33e5cad08e2c861b0efd

Pith citing papers

No inbound Pith citation observations are available.