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Paper Citation Record · LEDGER

A Scalable Approach to Evaluating Moral Sensitivity in LLMs

As of 22 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 2026-08-22T06:32:14.747728+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
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

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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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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Observation 606366d7-f4c7-45ba-ac5f-5801adc4fcd6 · outbound

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

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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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Observation 50d4a5f3-db6f-4f37-a1f5-19dfa3525ac1 · outbound

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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

This paper cites and Bain, Paul G.

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

This paper cites and Lazar, Seth , date =.

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

This paper cites Differences in the Moral Foundations of Large Language Models , url =.

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=sha256:916e79003082e4b930a003f8917dffe10b13972d219aec3b5dc1e11306e054f9

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:ba470c4b96dd67a62f2474d02abf1d44802d5f45b99bed1fdddab8c3be41e55b

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=sha256:7724df40e17cbf9b465dba23eaa8a5c2c1ec01aec6286f0b42b95992779a0b05

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=sha256:3648564477aa575f74f35745d66401916e4df64a7766c0b7bc4ffc48b3f66765

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:b215749dad0408b4f31258826d64eb06f70a17f3c7737ba6929f45e7657432a6

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:c73c5da629315ae296e410b3884dae8be8a2a91b23951848cdbdc94cb6ef7b52

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=sha256:9c6ce46503f35240963c192905bd2bb19a3bb6c5204967ff15c4e51d4783d895

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:cdcbf9de20fc040804a55d260f471823ef17643e9fcbcea3cf0318c68af66138

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:bc7bd7a9dd30c4236f9607c6f6a6553e437a01a988b13266bd60796fb2e288c1

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=sha256:2809168142d3490866d26437b79b0a714a7b00ed9205f49a9f3366551eb01156

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=sha256:645b90920b4ce7001b513ca452483258d00df99f148cfc989449f04b7f6013c7

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:b85452fa8868f6b2d99c916c839ea9241a10304193dc6c7aff9e4ddb600d6309

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:a3ced18989d8d98bbdd7dcc7c8d38670db49ed17a940c0a7730d17e5f1cc8f07

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:bc9f26d024cb7a7561c9ccc79edb431a6b265dece2f24025d9fb341055867ee6

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:fd973119e28af19ea5089f591c7940864d98e50c0a7d5a49fc87b00dd196a34e

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=sha256:7f81ed2cbbca342cd0e29110bc8e02c83b8049322583021931f5c626fe225723

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:d27f8393ba54ad380a061f8dfb1120ee365b020f266d59dde3dc8429d17f2e4a

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=sha256:7338a8dd921eeea2cf81559af8670461e49a131a138dd33b7146390d7d3c9399

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=sha256:7d2f23fb15f043860915f154b18308191a740b3662168f35bf3b6941185a806e

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=sha256:64a25e4ca49b5da568daff4a1f196b9a383e942e7d216a1e5886fa9c026716a3

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:adaa561125a976b6656c00191cb8b93d471579e22df7d6ee256654bde73c9302

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=sha256:465b8b46b830837e8235841dc9a09ff43a5ba32a35abe8f1ce82311d9c7c74a8

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:feac8fd7af3b0f34713cb3ea4953420365d61576925c5bd0edaae1b90646a7cc

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:b1a6ee44452522475d7cecc12392467b25a7be8fd79474cf503472567618d8ce

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:db3cad478335946bc0c24126607ce6f6e53273a5609ed728e162f42108271a51

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:ccaefb0798363f4be7dc1604ce7366bb8b29cfedd9dbb7b4e30983becbe76aa1

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:f9caaf00c8561910a1ffd07d6ce91b3846852c0d361af250eedf09795c2dda5f

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=sha256:4628aee8fc2e2df2b6ecad806748fe6e75d709b5433abc6cae7e5e84a3e15ae1

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=sha256:1f65c8ef5039ab0248c283a8c6612ea3278ec1842a274c2276a87f5843d8a5eb

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:1fa0d29fa5c76235a9769803b4a1005bd419c2ef1df6a3b0289b405ee2fbb61d

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:b6d8a32f9efda2f28e1d5dfaf835d5e8e84918fff45d01f0b8a8fd1c962e5703

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:c62e733b3654d37ac46e7a8bea15ac3ca9b5e43b18afb947f912cc2357c8ee7d

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:d4ea7d7b9b0975a12d7338b989041b34fba586e311339079584b19b8a4b673d6

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:85ebf9b8fc1bc43485ba1c939a053c9f1c70aec57fb7ad7e22634c5fad26824c

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:dae787d110267289cc3e942432864bd8b2fb08bbcb881361653f3d4a525afa82

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=sha256:803f925598dfaad8340aeb3a4e3e84c47e638a2ab87f2bd2715d6200235af96c

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:a231244bfa2a68458425379acefb27bc51886092fa0afbc9509b6f4a85af99bd

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=sha256:119edae34008ff543993f9c81829ce0bb96d5b9d47081cad3c3ad8ea68d6657d

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=sha256:1c7d52301e4c43e626d635d2f03c37fb11fa26369af11682bd4068582e2a6e76

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-reported events for the cited work

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:658e21a8267b67838a67cc672648db07cc2c076a0acdca0e5c0a8684c1513aa9

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-reported events for the cited work

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:6470053adcc5cd84f1eb9084782fd0360e9657a3da14e44ca008bd8421a1508c

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-reported events for the cited work

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:69847022f62f1c34c014938f39172b9e6b43ac32e1833ec4934b189a00632b47

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-reported events for the cited work

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:7f7aac4801021f2b7b8efcb48ceb32e9564fd2a885f090c8d800a67a2c9f8ffe

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=sha256:74cbc8d50dfe28e084a8d67040e0b39a7f78072108cd660ac716d146e4418a94

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:d9ec33d2ddb63238f3f7ad124e7ab4b49657ef9a9e153c528ebd5b44316050fa

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-reported events for the cited work

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:2090eda99dd74c136a3dcb4a234f216c917797fbd7d2f6b4a3e0f62b3d72c03b

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:104f09c2a1053ae40f0a77bb64ae8c3b5036c2d531462342d00b51de263d3e7c

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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doi, observed 2026-07-12T05:48:31.640112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:2d2e331d80e997463336c95ed94bfcf835da51e9a8cafc86192245a0b1319acb

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-reported events for the cited work

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:1d59cc6eab7b0272481e54403a45e398a19bd3b390855378560aec2544d60734

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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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:64f607a797aa30daf2dfbbd0fc5506144a70e6a3c514aa168342370a948029ca

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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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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:6cb43d41a21e51d6deeacfb700896ba66027ec6942dec45c589766e5326d8f3f

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-reported events for the cited work

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source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:4cba5a68b5af3aa02d6ec317934b93d98e91cc5cbcf11e39c39c8cee3f8dfa0b

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:a50a519c8230fc599caab20bf6c1e84ed94d7d769bc73a27a39c7572f1fe10c9

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=sha256:8e325e6ef4992fd834d0477fe185a2db1924f1c8eab9ba125d320843339f902c

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=sha256:0b98b6543fb0fc9dc1c96ede1c2d533fae1acf557e0768f7c3df046c9fe0263e

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:b80cc324d8d97e8998565dc8c6c6b3622a3aea0aadaace9d6b8887c3fbe4eace

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=sha256:18046d1435f313776fb25463913a46003c3eeb76a0263a2aaedcbdb2b6a7f5ac

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:b28693b8833fa9537186e4a5a0ca7896b23dbafc8a172341b5e6bdbca62da0d0

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:d373b9f957437128c95386ece923eb9eec15a8ef0b360e9109e18ca95d98d23b

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-12T05:44:33.099337Z digest=sha256:630a178c1442863e20219090bdf6b82ed63417e5494c97dad8021267eecaf793

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:d3689098d4b7a3dd43319f2849677bacbc1f2974f4d4c1d408b66a0d5ea7ab4c

Pith citing papers

No inbound Pith citation observations are available.