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Paper Citation Record · LEDGER

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs

As of 21 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.18639.

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

pith.paper-citation-record.v1
2607.18639 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:53:38.598955Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

38 of 38 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved37
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 444dbfca-f879-4ed4-a121-ca6b4395482e · outbound

This paper cites Refusal in Language Models Is Mediated by a Single Direction.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Refusal in Language Models Is Mediated by a Single Direction

Reference 1

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source=pdf_text observed=2026-08-01T14:53:34.227426Z digest=sha256:a0092b1a37af4f6a0e85cf1900ac327c30c68dfdf432f44c5213a9048e985a6f

Observation cb80ffa3-8839-4e76-894b-dd020ab469a8 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2

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source=pdf_text observed=2026-08-01T14:53:34.361223Z digest=sha256:84c80222de295c973d15f5eac3824bb48ae2a6ae4c0e08f30368a43819b805c5

Observation cd17fe38-7a04-4712-9771-1cf485a19edb · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Constitutional AI: Harmlessness from AI Feedback

Reference 3

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source=pdf_text observed=2026-08-01T14:53:34.467584Z digest=sha256:151831293578cf6c42bb5e6d114039fe61712f752782f09f46e1a2e318e41279

Observation 80a00ca4-c2b6-487c-be80-0485d5453710 · outbound

This paper cites Enhancing model safety through pre- training data filtering.Anthropic Alignment Science Blog, 2025.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Enhancing model safety through pre- training data filtering.Anthropic Alignment Science Blog, 2025

Reference 4

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source=pdf_text observed=2026-08-01T14:53:34.577673Z digest=sha256:2cee4fee135b4920c24c08c51ae399c4d36ecff65fc3209941fc6869629a2885

Observation 1244f305-bf11-4938-96b2-f4dc70955c44 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 5

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source=pdf_text observed=2026-08-01T14:53:34.706600Z digest=sha256:fa74604f274da456358dd9c63aff32b7fa589fcb18f32e6f247e400f5a5d7d9b

Observation 09c6a1cd-f04b-423a-921c-7674476e87e5 · outbound

This paper cites Deepseek-v4: Towards highly efficient million-token context intelligence.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Deepseek-v4: Towards highly efficient million-token context intelligence

Reference 6

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source=pdf_text observed=2026-08-01T14:53:34.814161Z digest=sha256:3ce891e79c2b1d69f958da89c0389e782ccfb76c00149f9dd80a7697d40c3c7d

Observation 68dbdcca-fd6d-4d4e-b49a-fb0196182764 · outbound

This paper cites Enhancing Chat Language Models by Scaling High-quality Instructional Conversations.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Enhancing Chat Language Models by Scaling High-quality Instructional Conversations

Reference 7

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source=pdf_text observed=2026-08-01T14:53:34.921912Z digest=sha256:c1220f530e8f93032f2a7d4b44996e925a82e2548faba57f25f9f5c193a96b11

Observation b9df7b92-6c97-427e-8d6d-04a38ef312cd · outbound

This paper cites Simplicity prevails: Rethinking negative preference optimization for LLM unlearning,.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Simplicity prevails: Rethinking negative preference optimization for LLM unlearning,

Reference 8

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source=pdf_text observed=2026-08-01T14:53:35.010601Z digest=sha256:c57ce775ac7a93620f2d27a4a64536501f0ca210b3d99f04d185ad597bb50a5c

Observation c24c9987-d7be-40cb-9926-9c66b537912b · outbound

This paper cites Knowledge Unlearning for Mitigating Privacy Risks in Language Models.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Knowledge Unlearning for Mitigating Privacy Risks in Language Models

Reference 9

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source=pdf_text observed=2026-08-01T14:53:35.176942Z digest=sha256:950cb88c7eb031c681330a545f2ae397004f7b3398ba06bc22325a5693b63f5a

Observation ec717d17-c815-4534-9e02-8c88cda9c970 · outbound

This paper cites Pretraining language models with human preferences.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Pretraining language models with human preferences

Reference 10

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source=pdf_text observed=2026-08-01T14:53:35.273327Z digest=sha256:c24f1062237e31e82eeca0afc565ebbb6a5d5025e1fc6579ee802ff1b01fcf76

Observation e0b15acf-3aab-4fff-a4fe-63fb8b27140c · outbound

This paper cites When Bad Data Leads to Good Models.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs When Bad Data Leads to Good Models

Reference 11

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source=pdf_text observed=2026-08-01T14:53:35.432279Z digest=sha256:fd7c714db964de13f05ff6a0dfe3d54c06ac25916802b689bae83d638a49a3be

Observation 584cac2e-0329-4c0b-8cc7-002e18f935de · outbound

This paper cites The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning

Reference 12

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source=pdf_text observed=2026-08-01T14:53:35.534123Z digest=sha256:2364a1e82ca822f59abf3b23e2c7e2f6711270503a7df58f0e507eccdc6bd0e4

Observation 8a8e1ad1-08c7-4e3e-bc27-0c003420b32e · outbound

This paper cites A pretrainer’s guide to training data: Measuring the effects of data age, domain coverage, quality, and toxicity, 2024.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs A pretrainer’s guide to training data: Measuring the effects of data age, domain coverage, quality, and toxicity, 2024

Reference 13

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source=pdf_text observed=2026-08-01T14:53:35.702950Z digest=sha256:504f6f0e102ca645ff24d60dde32f8b9559ccab14e3362a3d9f7a4b5f1d19536

Observation e448b515-4511-4777-bb21-809a7b8125b4 · outbound

This paper cites Natural emergent misalignment from reward hacking in production RL, 2025.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Natural emergent misalignment from reward hacking in production RL, 2025

Reference 14

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source=pdf_text observed=2026-08-01T14:53:35.832281Z digest=sha256:6d7c4adc4eed7770a209cc0eb093443d629f34c7cba5cf538c40696d6ce32853

Observation 7e02ffd9-b228-4c99-b640-ac15bb012e33 · outbound

This paper cites Safety pretraining: Toward the next generation of safe AI, 2025.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Safety pretraining: Toward the next generation of safe AI, 2025

Reference 15

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source=pdf_text observed=2026-08-01T14:53:35.966930Z digest=sha256:ba867eb2c075744d302efd8ca483c552b2d0943397d71611748a08c9c1fdda53

Observation 49c94a80-fe4f-4cee-af5e-f75bb70bbad1 · outbound

This paper cites Mouton, Caleb Lucas, and Ella Guest.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Mouton, Caleb Lucas, and Ella Guest

Reference 16

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source=pdf_text observed=2026-08-01T14:53:36.088747Z digest=sha256:0322694865541dfde825f3a70f46f99c9f126aacafeda9f7b9eb50d4e5159755

Observation d3628455-8d5c-4e4c-9b7e-5a9c7b204b64 · outbound

This paper cites Interpreting GPT: the logit lens.LessWrong, 2020.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Interpreting GPT: the logit lens.LessWrong, 2020

Reference 17

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source=pdf_text observed=2026-08-01T14:53:36.152750Z digest=sha256:791b887bc8cefdfdfbd901cb1da4fc1308988ce0835498f059c19f5a066f8966

Observation a8845198-a3b4-43f7-95b2-86dbada39a28 · outbound

This paper cites Real-time detection of hallucinated entities in long-form generation, 2025.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Real-time detection of hallucinated entities in long-form generation, 2025

Reference 18

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source=pdf_text observed=2026-08-01T14:53:36.227610Z digest=sha256:66f82097b6976051b079573e386e966d3697444767faa483975b1cfb2da3e0aa

Observation 6fb618c0-7040-458e-8428-80261a9a637b · outbound

This paper cites Deep ignorance: Filtering pretraining data builds tamper-resistant safeguards into open-weight LLMs.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Deep ignorance: Filtering pretraining data builds tamper-resistant safeguards into open-weight LLMs

Reference 19

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source=pdf_text observed=2026-08-01T14:53:36.361261Z digest=sha256:5606e159d362ec43f89e257af73255017ca74f780a9f045da04d29f5f6f920d5

Observation 0f0dba82-0e16-40ae-8abc-47ba4135b2c8 · outbound

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

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Training language models to follow instructions with human feedback

Reference 20

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source=pdf_text observed=2026-08-01T14:53:36.485307Z digest=sha256:b1702d2e36fca03ed350208de5e4c93952eba061f94fd995bac9bc8d80c70690

Observation c57ee244-f289-4452-b72c-afbc95ba04e7 · outbound

This paper cites Cambridge University Press, 2nd edition, 2009.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Cambridge University Press, 2nd edition, 2009

Reference 21

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source=pdf_text observed=2026-08-01T14:53:36.586451Z digest=sha256:85b5872e137d5eeb50affc14a3e1292c54ce1525b9528ca5454f19b697f3a874

Observation 7c1ff182-4433-4943-b305-afe7a589cf53 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 22

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source=pdf_text observed=2026-08-01T14:53:36.784511Z digest=sha256:d331052fdc32c6bac900f163b8ea2c6c0bd6dd4df523bbd0c7ad5b5086c73b5d

Observation 2faad02f-4cb5-42a8-98fc-905c9c277096 · outbound

This paper cites Shaping capabilities with token-level data filtering, 2026.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Shaping capabilities with token-level data filtering, 2026

Reference 23

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source=pdf_text observed=2026-08-01T14:53:36.919268Z digest=sha256:7afb5826e59a2edc87a347dd804655b6b66cc0a898104a9704e3831e2be63d03

Observation d362c5d2-bd84-473f-b4c7-ccc9c490fedd · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 24

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source=pdf_text observed=2026-08-01T14:53:37.000099Z digest=sha256:85cca4c9e200289179746d1e78977222dbe61e0597c097b098fe5a5aada006d4

Observation c386292e-083b-429b-92eb-6f107a78bb9a · outbound

This paper cites Conditionalization confounds inoculation prompting re- sults.LessWrong, 2026.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Conditionalization confounds inoculation prompting re- sults.LessWrong, 2026

Reference 25

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source=pdf_text observed=2026-08-01T14:53:37.138703Z digest=sha256:2a1cad4e71b2e0f309cccde7ed9a18b720a98bed77881c2cbe7591f25e0ef464

Observation 050a5240-0bdd-45b7-998a-1447bef44979 · outbound

This paper cites XSTest: A test suite for identifying exaggerated safety behaviours in large language models.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs XSTest: A test suite for identifying exaggerated safety behaviours in large language models

Reference 26

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source=pdf_text observed=2026-08-01T14:53:37.313903Z digest=sha256:3b969077726863c51c46c69870d6cc230f068e8ba27bc6c15d92eff12c563c68

Observation 989254db-67d1-4205-bb50-07a495d6c18e · outbound

This paper cites Believe it or not: How deeply do LLMs believe implanted facts?, 2025.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Believe it or not: How deeply do LLMs believe implanted facts?, 2025

Reference 27

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source=pdf_text observed=2026-08-01T14:53:37.584937Z digest=sha256:997453e4fa209aef59e812890dbacd0536f19fde0e88d4740f598631d4921f4f

Observation 63132adf-9a33-44f3-b25a-dd1434dbb749 · outbound

This paper cites CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge

Reference 28

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source=pdf_text observed=2026-08-01T14:53:37.662023Z digest=sha256:78f6ab041d60601eef47a6edd8d4a4cb708e8074e954de71fa7c6c71e205d72f

Observation db844b0a-5742-4963-875d-c57907349149 · outbound

This paper cites XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models

Reference 29

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source=pdf_text observed=2026-08-01T14:53:37.460437Z digest=sha256:99e96a733fd73c8268d058d9303c550893644f1e6b411a37764f800dd544eedd

Observation 1e336ee7-f367-44f9-b29f-4aeba1f5364f · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 30

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source=pdf_text observed=2026-08-01T14:53:38.039459Z digest=sha256:1d40699e7ab7c0747889e5229cc316088469deb164e540d575e3498fa84a6c4a

Observation b3d3fa3a-80ba-4c38-999c-129bbe549623 · outbound

This paper cites Inoculation prompting: Instructing LLMs to misbehave at train-time improves test-time alignment, 2025.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Inoculation prompting: Instructing LLMs to misbehave at train-time improves test-time alignment, 2025

Reference 31

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source=pdf_text observed=2026-08-01T14:53:38.174577Z digest=sha256:aab7f005e563564385a0ebdce1f9e618031219a8a958c2cde59f037a5ca525d0

Observation 5fd31803-2c7a-474f-995a-7a50544ca50d · outbound

This paper cites Inoculation prompting: Eliciting traits from LLMs during training can suppress them at test-time,.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Inoculation prompting: Eliciting traits from LLMs during training can suppress them at test-time,

Reference 32

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source=pdf_text observed=2026-08-01T14:53:37.800194Z digest=sha256:ab81557dad27efe80a3a8d5e495ab5e3423c57224ef004c74e0d6903c4860868

Observation 3c6167c6-8280-4ade-8adf-9ea50608b08a · outbound

This paper cites Backtracking Improves Generation Safety.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Backtracking Improves Generation Safety

Reference 33

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source=pdf_text observed=2026-08-01T14:53:38.598955Z digest=sha256:cd003be3100041bcdccf6d54541b3e16d9e2f406f018c2109990cfc351dc0d1f

Observation f2bc8321-2376-417b-962f-2cf4a28326a9 · outbound

This paper cites Negative preference optimization: From catastrophic collapse to effective unlearning,.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Negative preference optimization: From catastrophic collapse to effective unlearning,

Reference 36

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source=pdf_text observed=2026-08-01T14:53:38.309348Z digest=sha256:cbc155994b0341b0575c5c161bcac83401029520e3d4af4a52c437f0677dee8a

Observation 01bbc548-db08-44e9-adcc-13cd1ed490d2 · outbound

This paper cites Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning

Reference 37

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source=pdf_text observed=2026-08-01T14:53:38.441310Z digest=sha256:39bab43adff433736ecdbd6d8a66a4e3dd7411ccfe3459eabcdde021ac5d098a

Observation 9e353af1-7d29-4645-9bee-5683ee82a53d · outbound

This paper cites Pretraining Language Models with Human Preferences.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Pretraining Language Models with Human Preferences

Reference 2023

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Observation 2973579c-f06a-452d-b117-139cdebdeb78 · outbound

This paper cites an unresolved cited work.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Unresolved cited work

Reference 2024

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:53:35.111220Z digest=sha256:d3e740ed624fd75f55be089f385f5835220c7c1f55fcdc341e055e68c9b4ee7c

Observation a3252bb0-ab43-4ed0-b646-43438f7c088b · outbound

This paper cites an unresolved cited work.

Mark, Don't Erase: Token Inoculation for Dual-Use Knowledge in LLMs Unresolved cited work

Reference 2025

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no resolver link, observed 2026-08-01T14:53:37.897211Z

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source=pdf_text observed=2026-08-01T14:53:37.897211Z digest=sha256:5aec0f24825bf8a2b5b34b9500af821d687a29b95d2aa74a3c63640567dc67c3

Pith citing papers

No inbound Pith citation observations are available.