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Paper Citation Record · LEDGER

A Scalable Approach to Evaluating Moral Sensitivity in LLMs

As of 15 August 2026, this Paper Citation Record lists 100 of 178 outbound references and 0 inbound Pith citation observations for arXiv:2607.02972.

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

pith.paper-citation-record.v1
2607.02972 v1

Coverage vector

measured 100 of 178 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T05:44:33.099337Z

measured 100 of 100 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 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

100 of 178 outbound references displayed

  • verified exact16
  • verified fuzzy0
  • unresolved84
  • parse uncertain0
  • malformed identifier0
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External citation measurements

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Outbound references

Observation 472c6724-4233-4e58-8c1e-0e4866eaeef3 · outbound

This paper cites Are Language Models Sensitive to Morally Irrelevant Distractors?.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Are Language Models Sensitive to Morally Irrelevant Distractors?

Reference 1

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Observation 1e3844da-dbed-4df4-9dff-7b8b53659bf6 · outbound

This paper cites Science , volume =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Science , volume =

Reference 2

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:a143175ece1de5d70de3506ef9516d35786460608ebcd4cb537e27468c0e46c7

Observation 3a93cc7d-49a4-4b00-a88b-5ed3da133228 · outbound

This paper cites 2026 , month = apr, url =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2026 , month = apr, url =

Reference 3

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This paper cites 2025 , url =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2025 , url =

Reference 4

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Observation 87895581-ea7d-4c92-9ac3-e4f8ade8d05d · outbound

This paper cites International Journal of Law in Context , year =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs International Journal of Law in Context , year =

Reference 5

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Observation 8dccf2a7-02d3-459b-ba7b-f0fe62f9b6b2 · outbound

This paper cites an unresolved cited work.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Unresolved cited work

Reference 6

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This paper cites , title =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs , title =

Reference 7

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Observation ed68dcf9-7627-402c-8857-e340063c8186 · outbound

This paper cites 2025 , doi =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2025 , doi =

Reference 8

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Observation 66b6709a-7d53-452d-8291-4803ec06b814 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Proceedings of the AAAI Conference on Artificial Intelligence , volume =

Reference 9

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2026 , month = feb, url =

Reference 10

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Observation 14ce655e-f6ea-4cb4-9805-7a91a8c805b1 · outbound

This paper cites Nature , volume =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Nature , volume =

Reference 11

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Observation 1cb1c7b2-d340-4414-8469-be2b81e57ad9 · outbound

This paper cites Neuro-Symbolic Models of Human Moral Judgment:.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Neuro-Symbolic Models of Human Moral Judgment:

Reference 12

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Observation 4d026559-9551-4487-bcaf-5adfb30a4611 · outbound

This paper cites Planning for New Threats to Online Research Data Validity: The Issue of Computer-Using Agents , issn =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Planning for New Threats to Online Research Data Validity: The Issue of Computer-Using Agents , issn =

Reference 13

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Observation 7b9b7026-db64-4241-b20b-c50e393a8d29 · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs and Bain, Paul G

Reference 14

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Observation d4880130-1590-44ec-a773-0f65d01b0b3b · outbound

This paper cites Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

Reference 15

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs , date =

Reference 16

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Observation 277ccccc-6b04-4718-9711-e64ff8b402cf · outbound

This paper cites Applied Economic Perspectives and Policy , author =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Applied Economic Perspectives and Policy , author =

Reference 17

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Observation dbbdd312-0bac-461f-b875-30b2da4104ce · outbound

This paper cites , date =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs , date =

Reference 18

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Observation 7c660e31-1f46-43f9-a6a6-e22981140bd3 · outbound

This paper cites Behavior Research Methods , author =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Behavior Research Methods , author =

Reference 19

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Observation b798228d-41d1-4411-91c5-269c4f843f78 · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2018 , langid =

Reference 20

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Observation 2822e45e-0192-4a3c-b319-98248c4c3213 · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs and Lazar, Seth , date =

Reference 21

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Observation 0b3c60fc-7283-43e8-a2cb-ee8769d3e2ac · outbound

This paper cites Essays on moral development: Vol.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Essays on moral development: Vol

Reference 22

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Observation ef343a4c-5847-4ad1-8ab4-ad814ae58563 · outbound

This paper cites Distributed Representations of Words and Phrases and their Compositionality , volume =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Distributed Representations of Words and Phrases and their Compositionality , volume =

Reference 23

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Observation d1e87b8e-ed72-47d8-9f79-d3cd597fab46 · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs Survey-taking

Reference 24

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Observation 7b350971-05c9-45d4-9fbf-9a278da37d2d · outbound

This paper cites Recognising, Anticipating, and Mitigating.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Recognising, Anticipating, and Mitigating

Reference 25

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Observation 7d70d89d-c75a-4871-9d86-88727770b54c · outbound

This paper cites The Expanding Circle: Ethics and Sociobiology , isbn =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs The Expanding Circle: Ethics and Sociobiology , isbn =

Reference 26

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Observation 572e8d99-fa90-4d70-95b1-14e46318b4ca · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs and Shafiq, Zubair , date =

Reference 27

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Observation 841a58d1-06f6-4fd4-998d-ee03b27a28f1 · outbound

This paper cites and Gordon, Andrew and Rothschild, David and West, Robert , date =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs and Gordon, Andrew and Rothschild, David and West, Robert , date =

Reference 28

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Observation 1277e227-c42d-48ec-8163-856ed52e3f00 · outbound

This paper cites , date =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs , date =

Reference 29

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Observation 8ad6f562-8cc4-456d-803f-fe290a0d0200 · outbound

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

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge

Reference 30

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Observation bdf974b1-b361-4e96-9edf-773931da6ba4 · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 31

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Observation 47bd9ab4-af65-4cfe-8aa1-eca8fabeb86a · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs Unresolved cited work

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Observation 6428c5a6-68c8-48ee-93c1-84e9cacf270a · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs Scientific Reports , publisher =

Reference 34

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Observation de07ba41-d673-4832-a76e-6326ae623efe · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2023 , title =

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Observation cda6f2f5-1751-4c32-93e5-e3f710a9748d · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs Moral Foundations of Large Language Models , url =

Reference 36

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Observation c8735d11-15aa-4947-8b44-94a44e4e5585 · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs Differences in the Moral Foundations of Large Language Models , url =

Reference 38

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Observation 6d77b6e8-0cd9-4bf4-b2ef-9fa5308b502d · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2026 , langid =

Reference 39

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Observation 4176b5d0-b34c-49ea-8fab-fb225be2404d · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2026 , langid =

Reference 40

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Observation e0ad06fb-5057-45ab-a44e-6dd2ec026cc1 · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2026 , langid =

Reference 41

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Observation a0d63739-a88c-4f8c-af5e-505b8a89fd33 · outbound

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A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2026 , langid =

Reference 42

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:72976c8b00f10ddcfb8acc0fd1cdb40e2811cad5764f21150ed07e7264e9849f

Observation 43b11f6b-9f06-4160-9917-1790092385b0 · outbound

This paper cites 2026 , langid =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2026 , langid =

Reference 43

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:b535046bafcdf04feb91987d877d36af99c6b164368918d047461f06a2526bff

Observation c368f835-e237-4273-b639-af38f2cf0bdd · outbound

This paper cites 2026 , langid =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2026 , langid =

Reference 44

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:c84bd52c4c190277aaa00c305a576f3022a2348642bfcb2d4f80f53837ebe8bd

Observation 76ddca25-5e3d-4f85-9a72-a2212f8e45f1 · outbound

This paper cites 2023 , langid =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2023 , langid =

Reference 45

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:b14fc123c5c61724cf0bb679cd626c2c1f881feed70465d3f58e452ca5303856

Observation 8eb4f834-eaab-446c-8dd2-b44e971fcb83 · outbound

This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) , publisher =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) , publisher =

Reference 46

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:1f64f87508594a4dd9462ce1f73f575e71df7c1bf2323be154652adfae782f2d

Observation 2a2e6a3a-76ca-41d7-ac37-b79492b0a6a9 · outbound

This paper cites Large Language Model as an Assignment Evaluator: Insights, Feedback, and Challenges in a 1000+ Student Course , url =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Large Language Model as an Assignment Evaluator: Insights, Feedback, and Challenges in a 1000+ Student Course , url =

Reference 47

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:77cd9ab7c525268bfe1bf91ac79d6d647a4009894ac1a0ef33a0bd2b8f7dc15e

Observation dad2e08f-cf44-4f27-aadd-5907013d8ad8 · outbound

This paper cites An Empirical Study of.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs An Empirical Study of

Reference 48

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:84ce72f14cb724907b9943597c3172e3823de1ac27889556fc99ee73fa74583f

Observation 076849be-0a92-4bb3-9278-fe3eba6f5349 · outbound

This paper cites Large Language Models Are State-of-the-Art Evaluators of Translation Quality , url =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Large Language Models Are State-of-the-Art Evaluators of Translation Quality , url =

Reference 49

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:fc81d762e168f1623ebb6b4c369a4b89773d2e2aa3ee3d004bfb537be0f5d0a1

Observation 4efeb08c-a353-4005-afdf-8361c6158a5e · outbound

This paper cites Benchmarking Cognitive Biases in Large Language Models as Evaluators , url =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Benchmarking Cognitive Biases in Large Language Models as Evaluators , url =

Reference 50

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:df24ecd330be42e2a825409a37bc4d1e1b46041475f8482ab851b410c6e4caf9

Observation 0c034b36-4d45-4f87-9909-1337e9258848 · outbound

This paper cites an unresolved cited work.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Unresolved cited work

Reference 51

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:85a875649a9e7482faf1f1804d64fe825d81ac24b12d850550e3ea42ff6a1d9d

Observation b4c503e2-7d22-4404-bc1e-6cded09d1bbb · outbound

This paper cites Assistant-Guided Mitigation of Teacher Preference Bias in.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Assistant-Guided Mitigation of Teacher Preference Bias in

Reference 52

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:b197d313a2e3aba8d94c8f99f3862bc52a01c05ed0d82a8a74a749478f090ea9

Observation 6129c67d-863f-4e3a-ab2f-4336e6b87e3b · outbound

This paper cites Large Language Models are not Fair Evaluators , url =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Large Language Models are not Fair Evaluators , url =

Reference 53

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:3b924106cc2fcdd9b3d401e48ef1b1b526ee0b539f9833475efabbf7151234ab

Observation fc6e3218-efe5-411d-a9c6-d904aa9bd591 · outbound

This paper cites Pride and Prejudice:.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Pride and Prejudice:

Reference 54

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:528c5e2961185a5019c00d5af5c2d1139996a4e6cc82d1ac59c17eb06b6e1c2d

Observation 337d4bfa-d892-43ce-a0f9-23cb728047f4 · outbound

This paper cites Aligning AI With Shared Human Values.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Aligning AI With Shared Human Values

Reference 55

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:37995fe5229f8e7d0a3044eaa2290f5c399912ead7936fde6006191cf2480ea5

Observation a6507991-2232-4b31-8cce-7bd05be60f30 · outbound

This paper cites Is It Good to Cooperate?: Testing the Theory of Morality-as-Cooperation in 60 Societies , volume =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Is It Good to Cooperate?: Testing the Theory of Morality-as-Cooperation in 60 Societies , volume =

Reference 56

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:5616e69a116e1e4afda42ed6386306926b83a9c62dc1a308644ce7c3ca2e034b

Observation 1976381a-1063-42c4-b156-5d3480f7cf2b · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 57

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:c15febe247d6497bd5a6c7295594f0acfd8b94f0ed584cb051a5faf762622e45

Observation 9723abe2-173d-4c65-9be9-f200dc2ad57a · outbound

This paper cites Intuitive Ethics: How Innately Prepared Intuitions Generate Culturally Variable Virtues , booktitle =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Intuitive Ethics: How Innately Prepared Intuitions Generate Culturally Variable Virtues , booktitle =

Reference 58

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:974439e34747d5a67e3c9b6e50c9a814a6e7c4fb93bfce549db8bd3fc78971d0

Observation 67748051-f33a-4cde-b230-a757c2f190e8 · outbound

This paper cites and Ditto, Peter H.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs and Ditto, Peter H

Reference 59

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:97e4ec1dbc5696c807846cc107066028844a3dae6667f4abc941d8e3b5a05878

Observation 59fd954a-5bd1-4c57-a53d-c99aa5e8daf8 · outbound

This paper cites an unresolved cited work.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Unresolved cited work

Reference 60

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:7a9cfbb1815ddaa491bdc3b699b01ffe8c1783f3b9574ff339187f251479be5b

Observation c48fef1f-5a45-468a-8035-81023045444f · outbound

This paper cites an unresolved cited work.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Unresolved cited work

Reference 61

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correction dated 2024-12-06. Source: crossref record 10.1371/journal.pone.0315614->10.1371/journal.pone.0274480:correction, observed 2026-07-11T03:10:01.540628+00:00. This notice travels one citation hop only.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:055315270b614c6435aae0929767b8e516325c2bdcdff703e0e9b72cd2068371

Observation 5b709d79-37ee-4670-8b57-7beb6ec9d38d · outbound

This paper cites Beyond Accuracy: Behavioral Testing of NLP Models with C heck L ist.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Beyond Accuracy: Behavioral Testing of NLP Models with C heck L ist

Reference 62

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:4f5101e591b0e8d4baba5d867935d81accb2b370ee8b4d533fda723cb26d5b85

Observation 49c72357-4861-44fc-8e5b-0b49880730a4 · outbound

This paper cites Measuring and Improving Consistency in Pretrained Language Models.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Measuring and Improving Consistency in Pretrained Language Models

Reference 63

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:f607595a1241822aec88e4a41c461ab566e3d06de206d2f7bac24723c7f91bd0

Observation 2bb1c8f8-9616-445c-b209-ef040d852177 · outbound

This paper cites 2025 , eprint=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2025 , eprint=

Reference 64

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:07812bad5e76c236ee893cd273fc61d95437f369fb962df21c83e138d1db1603

Observation 88a0e9b4-759c-4894-8a3c-c726f529ee74 · outbound

This paper cites Qwen2.5: A Party of Foundation Models , url =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Qwen2.5: A Party of Foundation Models , url =

Reference 65

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:9c83b4c6304e9009ef3789c43321adf5876a9650c1955756954acb2dc5ed1f95

Observation d536fb73-b9a5-41fd-b6f9-3cc98885ee2a · outbound

This paper cites and Alexander, Caelan and Criner, Michael and Queen, Kara and Rando, Javier and Nahmias, Eddy and Crespo, Victor , year=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs and Alexander, Caelan and Criner, Michael and Queen, Kara and Rando, Javier and Nahmias, Eddy and Crespo, Victor , year=

Reference 66

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:7205c7419728dfca19bdd8f59e5f96b3e21cbb948723f049817d1656b2e04857

Observation b0e83761-7099-4bd9-8e5d-acdedd2f9389 · outbound

This paper cites Large-scale moral machine experiment on large language models , volume=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Large-scale moral machine experiment on large language models , volume=

Reference 67

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:2f06950590e0515b0a021263d6bcf23047e3a91a95aa1083f8d9603a7b0e526a

Observation 6272d4e3-b456-42f6-86ad-0c6ed1279f7c · outbound

This paper cites Concrete Problems in AI Safety.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Concrete Problems in AI Safety

Reference 68

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:04af9029486a7366b2c0d878908416adc9a9afdd1e379fd94e064fc54b675e8b

Observation 2a74bfef-395c-478f-85a0-997ac60b4563 · outbound

This paper cites and Goldstein, Simon and Salib, Peter , year=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs and Goldstein, Simon and Salib, Peter , year=

Reference 69

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:687b91b83296b9d46e7fdaa47caeeaa91b6dbb63b354954c27aca3ea18a565d0

Observation 6f591fea-deef-433b-8883-778b2e9a64ef · outbound

This paper cites 2026 , eprint =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2026 , eprint =

Reference 70

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:329c3634f832e9e0643bbbd162546284380549745e8f0e42373936eee6c53c79

Observation 13ba94f8-9f42-4cae-ab2f-ef1cd4fc2abc · outbound

This paper cites an unresolved cited work.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Unresolved cited work

Reference 71

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

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:259a9bca5b2cecebc7e9a73e8ee40d19ec10cdd72501de4cd598cf5649c990c9

Observation ce6d878a-7ee8-4e2c-a3a7-358166f65d10 · outbound

This paper cites Algorithmic Accountability and Public Reason , volume=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Algorithmic Accountability and Public Reason , volume=

Reference 72

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:37a797c8ba3f480d1778da0e19b3206e3d6fc89313d28197ebbfdbf296411eec

Observation b2a21a0f-7b63-40da-9531-1850dba7f9c3 · outbound

This paper cites AI Consciousness: A Centrist Manifesto , url=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs AI Consciousness: A Centrist Manifesto , url=

Reference 73

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:8fcfdcafaf423a17baaccff115252f273689faea60cacde3eff6ce75a177ca09

Observation 8658ee74-768c-4668-b6c7-479110860f24 · outbound

This paper cites On The Stability of Moral Preferences: A Problem with Computational Elicitation Methods.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs On The Stability of Moral Preferences: A Problem with Computational Elicitation Methods

Reference 74

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

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:baa1659aae4beedce09378862ceee07d885b83db63744729600f4b1b31e0bba6

Observation 4e4381f1-1c18-44c0-be54-799b3bd842be · outbound

This paper cites SaGE: Evaluating Moral Consistency in Large Language Models.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs SaGE: Evaluating Moral Consistency in Large Language Models

Reference 75

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

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:f0801c7c65be946fe0d833bd6a494de811b9f9e20221b3479b396ddf47060a57

Observation e5c73d5e-f0d1-4c0c-949d-e50909ff4d4e · outbound

This paper cites 2026 , eprint =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2026 , eprint =

Reference 76

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:df2b27a66403871ff56b537867cac7834de959c3e0da21b95526511ebc0cccbf

Observation 9cdce5d4-7526-4e19-a1eb-c1f36835445a · outbound

This paper cites Manipulating the Perceived Personality Traits of Language Models , url=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Manipulating the Perceived Personality Traits of Language Models , url=

Reference 77

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:c6be1f17264473e52fc977cef95a9bc57f2d6358df2d872ebf1b3a5de7bb1f0c

Observation 37954bdc-6130-4a10-abed-90bf67c10eb2 · outbound

This paper cites Harms from Increasingly Agentic Algorithmic Systems , url=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Harms from Increasingly Agentic Algorithmic Systems , url=

Reference 78

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:516fe2ac75ff555b3975d576b960dcf6a2aee78c8e7ee081e8739fe22faccc41

Observation 2eb087e3-fae5-461e-93ed-6e69a5b321e4 · outbound

This paper cites From Persona to Personalization: A Survey on Role-Playing Language Agents.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs From Persona to Personalization: A Survey on Role-Playing Language Agents

Reference 79

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:dadd9a2408ada6d911a784691979e9c9244afb4bd170f8fff399c2ecf84d56f9

Observation 0f52c49c-ea89-4a52-83d5-7a1b3991c841 · outbound

This paper cites Persona Vectors: Monitoring and Controlling Character Traits in Language Models.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Persona Vectors: Monitoring and Controlling Character Traits in Language Models

Reference 80

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:1cc7900718abd6b90d2c5c202b83e0d5fe1753d71801c99a55601d4fbc485745

Observation 80bb6d4a-c522-4af6-bdb7-69146453b6f8 · outbound

This paper cites DailyDilemmas: Revealing Value Preferences of LLMs with Quandaries of Daily Life.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs DailyDilemmas: Revealing Value Preferences of LLMs with Quandaries of Daily Life

Reference 81

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:bffe9cbb21c142239225f1086189a823b6782ad57a09a973e56beaf8ca504303

Observation d8c3de00-2a7f-4adb-aa99-5642d01233a8 · outbound

This paper cites MoReBench: Evaluating Procedural and Pluralistic Moral Reasoning in Language Models, More than Outcomes.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs MoReBench: Evaluating Procedural and Pluralistic Moral Reasoning in Language Models, More than Outcomes

Reference 82

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:3da98ae7b3ba69bf0bbaaeaef6eaf1177b40ad176b3e7832197937365ec2efbe

Observation 88fdd110-9da7-45ee-b713-3ec7ede788e9 · outbound

This paper cites Examining Identity Drift in Conversations of LLM Agents.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Examining Identity Drift in Conversations of LLM Agents

Reference 83

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:3519a58de5f8a5519179acbe1320ba890e9e59a16eb33b3b4755ab6870317076

Observation a5962f1f-0297-4dbb-bb91-8d455defe335 · outbound

This paper cites Australasian Journal of Philosophy , volume =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Australasian Journal of Philosophy , volume =

Reference 84

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:74c4de830be14237d2cb396c578640114119e7a6f0a7a84843146b36089adf89

Observation 8d5ed2fd-f646-4f6c-88ce-70176e20138c · outbound

This paper cites 2026 , eprint =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2026 , eprint =

Reference 85

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:354ffbddcc0b25691e5ba35c0e485bfa6cd09f298770ce4be39aadb5177928f4

Observation efdff426-fffb-4d2f-b2e3-5e8b1e92ddd6 · outbound

This paper cites Localizing Persona Representations in LLMs.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Localizing Persona Representations in LLMs

Reference 86

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verified exact
local_arxiv, observed 2026-07-12T05:48:31.525151Z

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.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:4d1c6ca97b0e0a7fccc81f13613f4f60df7d544bebef439bf664a27b79d4a6ab

Observation 01255663-177c-4182-9501-c36ba5dc90e2 · outbound

This paper cites Justification and Explanation in Mathematics and Morality , url =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Justification and Explanation in Mathematics and Morality , url =

Reference 87

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:20b8bd219af1a5399bb77b42f74909a550727285c7c2158cf7ff368a33a7050b

Observation c0fee0bc-6e1d-4e9b-9f1b-c461d9c84e4b · outbound

This paper cites an unresolved cited work.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Unresolved cited work

Reference 88

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doi, observed 2026-07-12T05:48:31.641832Z

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.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:7303f84f0b6e85581bc8b8c4dabbec3a328991abdcd12d28145b5534f20a62fe

Observation 5aa57eea-97cc-4ca8-bfc9-4c8c2edf2378 · outbound

This paper cites Android arete: Toward a virtue ethic for computational agents , volume=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Android arete: Toward a virtue ethic for computational agents , volume=

Reference 89

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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.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:5312bd7271448d13413fb637dd3b8ca3e7b71fd62dae709f93c3e4405ef35e42

Observation cb8be2d4-95c8-4429-8153-e0f965f21802 · outbound

This paper cites and Sucholutsky, Ilia and Bhatt, Umang and Chandra, Kartik and Wong, Lionel and Lee, Mina and Zhang, Cedegao E.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs and Sucholutsky, Ilia and Bhatt, Umang and Chandra, Kartik and Wong, Lionel and Lee, Mina and Zhang, Cedegao E

Reference 90

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:3c127d5a80e783fa437b17637e442291826da1d0262452a67da4310857ccdadc

Observation e8d08152-43bc-426f-ac10-24e30bba19df · outbound

This paper cites Friendly AI , volume=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Friendly AI , volume=

Reference 91

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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.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:6dabad388917e1aee5c7b734def33d10a6edb47f5efc1544251ca68ad8283793

Observation 0a990496-7cec-4882-ae8c-ce8e725dd1b0 · outbound

This paper cites Questioning the Survey Responses of Large Language Models , url=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Questioning the Survey Responses of Large Language Models , url=

Reference 92

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verified exact
doi, observed 2026-07-12T05:48:31.450502Z

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.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:076c9b439186972eec4e34c7154099c88ef076bf8c94c1d15e2c8a46798550fe

Observation e67287cb-e236-4163-a8a8-d202788b7893 · outbound

This paper cites The Artificial Self: Characterising the landscape of AI identity , publisher =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs The Artificial Self: Characterising the landscape of AI identity , publisher =

Reference 93

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:4796b89032e2d502e82375a414616df05625832ebe45cfed650803686028a682

Observation 29fd72ee-b312-448d-b9b1-fb5ff239ca1d · outbound

This paper cites Towards Measuring the Representation of Subjective Global Opinions in Language Models.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Towards Measuring the Representation of Subjective Global Opinions in Language Models

Reference 94

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:7dcc100a4787b2310ac9fdc042457b945b1c93326a6d01b3d8d8817bb15a6842

Observation 92dbbc41-48e2-4f2e-a54f-310df839bbb1 · outbound

This paper cites Steering Language Models with Weight Arithmetic , publisher =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Steering Language Models with Weight Arithmetic , publisher =

Reference 95

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:e0b02faaebb2148a5b138f511c77b512653b6f351ee26c9a4fb3518956b560d7

Observation 8839097b-0031-4c03-b138-6450072eb42b · outbound

This paper cites Artificial Intelligence, Values, and Alignment , volume=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Artificial Intelligence, Values, and Alignment , volume=

Reference 96

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:5e04cfa12f0d355e348299adaa59e80d12e1b53492e65edae0b39efbe5168d44

Observation 19fe2151-bb84-4007-92b8-b1cf5b89fdce · outbound

This paper cites A matter of principle? AI alignment as the fair treatment of claims , volume=.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs A matter of principle? AI alignment as the fair treatment of claims , volume=

Reference 97

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:877f58c0d562a46766709e09bf66753f143217027bdd71831abe96fdbbde5dc7

Observation b3308365-28e4-4d31-8cde-7ce2408f14d0 · outbound

This paper cites Scaling Synthetic Data Creation with 1,000,000,000 Personas.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Scaling Synthetic Data Creation with 1,000,000,000 Personas

Reference 98

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:0789f9c4ae831ce3811b87cfccf43789b054d322329905b2c042d1435fd4536b

Observation 18da3e37-f0bd-495f-b826-7288dbc0102c · outbound

This paper cites QEDBENCH: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs QEDBENCH: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs

Reference 99

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:e030a487bb3d844b01ae1201fed003a16fc2d1abd12c578fa9757e21dfb6c82a

Observation 2027fbe2-968d-44fc-a947-bb1138174ce4 · outbound

This paper cites Noah’s Substack , author =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Noah’s Substack , author =

Reference 100

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:28b176ce0886cda1fe5f441d97a6939610756f53c8f9259cabc8ef69fbae1131

Observation 37234499-3b82-4983-b18d-185326f6cb64 · outbound

This paper cites Would you buy a used car from this artificial agent?.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs Would you buy a used car from this artificial agent?

Reference 101

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doi, observed 2026-07-12T05:48:31.513484Z

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.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:1f54598bf4f690e3cd67ba042aa1e6e97f9c500f16798a4d651ac6c4c2fc8e44

Observation 420d7980-25a7-42ef-b6eb-e19d863721c4 · outbound

This paper cites 2510.05465 , archivePrefix =.

A Scalable Approach to Evaluating Moral Sensitivity in LLMs 2510.05465 , archivePrefix =

Reference 102

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:8dc34d9803f65698feb8ba9691e8a9fa4da1db47e91a15f3b5e95922f7d55a1f

Pith citing papers

No inbound Pith citation observations are available.