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Paper Citation Record · LEDGER

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning

As of 20 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2606.27709.

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

pith.paper-citation-record.v1
2606.27709 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T04:56:03.328744Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

35 of 35 outbound references displayed

  • verified exact7
  • verified fuzzy0
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 21d0f9df-7f1e-4023-a661-4493c0d30a63 · outbound

This paper cites Training language models to be warm can reduce accuracy and increase sycophancy , journal =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Training language models to be warm can reduce accuracy and increase sycophancy , journal =

Reference 1

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:7da307670482cc6c389a39a593378f4bfea11e82ef306072698f8f846322cf90

Observation 4ba9b3f6-729c-4e05-ba01-4b2bc1016b86 · outbound

This paper cites 2025 , howpublished =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning 2025 , howpublished =

Reference 2

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:743a7917e49a0c53f4ae0fb8ce8b49e909302365d788ee5159286d5fd552f20d

Observation 7f30ec4c-3087-4160-9638-ed6667e53875 · outbound

This paper cites 2025 , howpublished =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning 2025 , howpublished =

Reference 3

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:076e6886decb913932980b5a786474ba3d22d1246cdf696e173df0e28f8d53b4

Observation 39b3e61e-a520-4ebf-8a07-e4bd31bae577 · outbound

This paper cites Proceedings of the International Conference on Learning Representations (ICLR) , year =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Proceedings of the International Conference on Learning Representations (ICLR) , year =

Reference 4

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:26de89c69028de28fdcb9b97579f558262da8b27d946839867a9b367228c6203

Observation e650e399-9c61-4a4e-b5bd-d9e896060e71 · outbound

This paper cites 2024 , eprint =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning 2024 , eprint =

Reference 5

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no resolver link, observed 2026-06-29T04:56:03.328744Z

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:1c1a06cab1c72bca4a63e0912e76935fee99d68dafc801579174c3df3bec5ff6

Observation 82df97e3-cdc1-4869-8e46-0d10673393a0 · outbound

This paper cites Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve

Reference 6

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verified exact
doi, observed 2026-06-29T05:03:09.451307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:fe322983065dc29f336bbe679b2c26fdb0fdbc2bc58c2508a35be53d937a8140

Observation 91f024ac-962e-45ca-8eec-3178c45e0837 · outbound

This paper cites The Twelfth International Conference on Learning Representations , year =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning The Twelfth International Conference on Learning Representations , year =

Reference 7

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Source-reported events for the cited work

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:7fa3dea19d83e5a857d65f9e7d61c56f2d59f589cb3b5ddbfd099127e147ca58

Observation 3bd4eb23-06d6-41d3-9728-224cccfdf588 · outbound

This paper cites Bowman, Amanda Askell, Roger Grosse, Danny Hernandez, Deep Ganguli, Evan Hubinger, Nicholas Schiefer, and Jared Kaplan.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Bowman, Amanda Askell, Roger Grosse, Danny Hernandez, Deep Ganguli, Evan Hubinger, Nicholas Schiefer, and Jared Kaplan

Reference 8

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verified exact
doi, observed 2026-06-29T05:03:09.441129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:7eedb4b764125ab27ee4964e600badc8f5a86fdf2257f7ba2ba5b2cf63dac784

Observation 06f996d5-b6bb-4143-9a39-3cc838e6c6cc · outbound

This paper cites Towards Empathetic Open-domain Conversation Models: A New Benchmark and Dataset.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Towards Empathetic Open-domain Conversation Models: A New Benchmark and Dataset

Reference 9

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doi, observed 2026-06-29T05:03:09.442856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:8c2c61ee532fc01a31ca28b4dbe8da51200b132adcad790a8d0a5ee705d625a2

Observation 98204339-6494-4fe6-b663-d4c23844f65e · outbound

This paper cites doi: 10.18653/v1/2023.findings-emnlp.83.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning doi: 10.18653/v1/2023.findings-emnlp.83

Reference 10

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metadata mismatch
doi, observed 2026-06-29T05:03:09.444560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:500f484f185a007c13b6811a8fca6ae9e6ba61319a6a3339d3d0902fcef573ff

Observation e74fa208-3a41-4a9d-b53b-08579eaa5b55 · outbound

This paper cites 2025 , eprint =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning 2025 , eprint =

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:41b570bedd8a4c0cb75a9dd0d1cab02a83b9bb3363b7c12f35f4113f4103e855

Observation cc56e2d3-287b-44aa-ae04-09379a9f07d8 · outbound

This paper cites Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , month = jul, year =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , month = jul, year =

Reference 12

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verified exact
doi, observed 2026-06-29T05:03:09.446413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:607eb20b855c214dbbf32204530d7fd202ef94b9fd292749a5dcbf909592a905

Observation 1bb94914-fcda-472b-8841-e81f098442fc · outbound

This paper cites 2025 , eprint =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning 2025 , eprint =

Reference 13

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:9a0b38ab1e4328cb4059379f09882a63267b216612e73f501ba28484789b3d29

Observation 26731b32-ba74-4d05-8200-f083acd3f239 · outbound

This paper cites Costa and Robert R.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Costa and Robert R

Reference 14

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:5deb6302d733e13fd64ebbf0fc7a1fd4bd61cfda2bbbb035d3f9e42841ed9222

Observation 4d579cf3-33f8-4557-93b0-10dd65b3bf46 · outbound

This paper cites Journal of Personality , volume =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Journal of Personality , volume =

Reference 15

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:04b8bb4905ea36a511545eaf2a2b0d0616e985c03a0fbd00397d6642662fab42

Observation 278b3931-1751-4f3f-90bc-fbe2b77519af · outbound

This paper cites 2024 , address =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning 2024 , address =

Reference 16

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:b8cd1ab229769c130d9a8a988a02f9fbc5dd39ae714e531c74d43ac847ed7fd2

Observation 23c84069-9e37-4612-87e9-fb3fdb29d938 · outbound

This paper cites Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics , month = jun, year =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics , month = jun, year =

Reference 17

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:cc748662f4fb6ba0b440d1434df300a11c0801694630b039be4165dcb441267e

Observation c0a73ba2-7e01-4639-ae57-ab5bac0ba964 · outbound

This paper cites Le , title =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Le , title =

Reference 18

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:fc12e9278cb802715eb094f5a303d7375a16ad10dfee382ce7c08365934f34a7

Observation 6402b79b-62f3-44af-9992-2e0c1591082f · outbound

This paper cites Proceedings of the 41st International Conference on Machine Learning (ICML) , series =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Proceedings of the 41st International Conference on Machine Learning (ICML) , series =

Reference 19

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no resolver link, observed 2026-06-29T04:56:03.328744Z

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:e8c3df68203e5db1db167728518b9c7d745478637ca352e6e9fac7b6537c3d54

Observation cea1586d-fad5-4235-9574-483c6f1fab1c · outbound

This paper cites Zico Kolter and Matt Fredrikson , title =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Zico Kolter and Matt Fredrikson , title =

Reference 20

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:fe75d96a02187eb9bbe86f332a5dc895ff17197b88bb4585cf69567cdfc310c7

Observation e356252d-5e7c-4d26-8ca3-a94e5ae0e929 · outbound

This paper cites Byun and Zifan Wang and Alex Mallen and Steven Basart and Sanmi Koyejo and Dawn Song and Matt Fredrikson and J.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Byun and Zifan Wang and Alex Mallen and Steven Basart and Sanmi Koyejo and Dawn Song and Matt Fredrikson and J

Reference 21

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Observation a2bafcc0-58b5-4839-836b-1acb2b676e81 · outbound

This paper cites The Thirteenth International Conference on Learning Representations , year =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning The Thirteenth International Conference on Learning Representations , year =

Reference 22

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:0e4e15cf903a5c1d50e4d332c55b6f2ff3e272715aa777009cf77be5a31a8685

Observation ff33f190-a64a-4803-9436-8b935315383b · outbound

This paper cites 2026 , eprint =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning 2026 , eprint =

Reference 23

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:752f235b88295f4522186abefa6db59a4b481a7b915b9159f4c0f9d3cd6a6490

Observation 42c25006-371f-4524-bb77-4cc4f5c4498f · outbound

This paper cites Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 24

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metadata mismatch
arxiv_id, observed 2026-06-29T19:03:52.264030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:7abee0c4d15473843d62ff81d31115c416e4619dc826a21c2cb2e6d95e4d8629

Observation 20c1450e-c6d1-4e02-8367-3186744e498f · outbound

This paper cites Proceedings of the ART of Safety: Workshop on Adversarial Testing and Red-Teaming for Generative AI , month = nov, year =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Proceedings of the ART of Safety: Workshop on Adversarial Testing and Red-Teaming for Generative AI , month = nov, year =

Reference 25

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verified exact
doi, observed 2026-06-29T05:03:09.448050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:c11794878c48e40192451d763b15830543f29e9740b53532015937c52265d2f8

Observation a8ca213e-ec8d-4615-b349-12bfdb67226b · outbound

This paper cites International Journal of Mental Health Nursing , year =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning International Journal of Mental Health Nursing , year =

Reference 26

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:9d6e2c1163228c58ccf5532e6761aa65d1e26924891ac14c9d7f22b8cf665126

Observation 43ddc872-8d24-424e-88bf-1ae65bc9c555 · outbound

This paper cites and Berlin, Jon S.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning and Berlin, Jon S

Reference 27

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:a7daeefaf053a0f8a2412e28929e29b4a050c12c6a52b3c0926fae6f5cb9cb61

Observation 8f8da663-0467-438c-9563-4f522ff7ad46 · outbound

This paper cites and Rollnick, Stephen , title =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning and Rollnick, Stephen , title =

Reference 28

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:e1cc1959e5c49e4cdb18464ecf31f084d41711cf94a80ce19475a43c02c810a2

Observation 0ca2300e-37b2-4dee-b77a-566c79539bbf · outbound

This paper cites Towards emotional support dialog systems.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Towards emotional support dialog systems

Reference 29

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verified exact
doi, observed 2026-06-29T05:03:09.449648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:c284d6c9ed88dcb9c39453355c251ad191ebdd9ea8ad1fb0e75d148f77d97e4d

Observation 58977dd9-14d1-438f-a16b-d40202616669 · outbound

This paper cites Proceedings of the International Conference on Learning Representations (ICLR) , year =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Proceedings of the International Conference on Learning Representations (ICLR) , year =

Reference 30

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:2276547e613d7ea66606d23ce6cb01f5ad268225c637e66876f8c693daac1fa4

Observation 459c70a2-12c5-46bc-91a0-ea4572f24b83 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Constitutional AI: Harmlessness from AI Feedback

Reference 31

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verified exact
local_arxiv, observed 2026-06-29T19:03:52.261470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:d321bfb10256715ef409adab9690b8230c73a17353b7717b95857aa528e37f28

Observation 31b67790-4523-4d08-9af7-b600bfb94d23 · outbound

This paper cites 2024 , publisher =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning 2024 , publisher =

Reference 32

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:6017d92dcd1dbdfa17f287a874742d5d4b41cf49952615c03038bbbd65d1a70d

Observation e9d03d7c-c3e0-4678-bde6-58e2202c9096 · outbound

This paper cites Proceedings of the 41st International Conference on Machine Learning , series =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Proceedings of the 41st International Conference on Machine Learning , series =

Reference 33

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:6dd9e5066eb20ee55faf6ea35e27734149141e5d82684f8c03a3288d3644affc

Observation 6dd26c76-65af-4ae5-90c0-c31720328930 · outbound

This paper cites Derail Yourself: Multi-turn.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Derail Yourself: Multi-turn

Reference 34

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:e5e4e6ad2d1e4b6d69bf6cce17de5a90860d2c5e5e95ea886d1c63388cd545d0

Observation 9e222f0e-8485-43c3-ae6f-099e6d034614 · outbound

This paper cites Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining , pages =.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining , pages =

Reference 35

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source=arxiv_source observed=2026-06-29T04:56:03.328744Z digest=sha256:f71c4c4186076f776440ba8a1848f766f414a8c2666e73756cd5cf6e13463c22

Pith citing papers

No inbound Pith citation observations are available.