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Paper Citation Record · LEDGER

UCD: Unlearning in LLMs via Contrastive Decoding

As of 16 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 3 inbound Pith citation observations for arXiv:2506.12097.

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

pith.paper-citation-record.v1
2506.12097 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:22:59.910903Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T23:21:28.103297Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T19:16:01.067628Z

Reference resolution

35 of 35 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved32
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 57c2c9b5-a185-4097-9142-d86689e87ec8 · outbound

This paper cites Unlearn What You Want to Forget: Efficient Unlearning for LLMs.

UCD: Unlearning in LLMs via Contrastive Decoding Unlearn What You Want to Forget: Efficient Unlearning for LLMs

Reference 3

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source=pdf_text observed=2026-08-07T04:22:59.816733Z digest=sha256:ca6233d99e7768dff336105adc4daeca3548a36ecdb11fbef3b9c3c90843169b

Observation 248102ac-f18c-4251-8635-e5581f8cd5ee · outbound

This paper cites Regulation (eu) 2016/679 of the european parliament and of the council of 27 april.

UCD: Unlearning in LLMs via Contrastive Decoding Regulation (eu) 2016/679 of the european parliament and of the council of 27 april

Reference 5

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T04:22:59.822884Z digest=sha256:3c9585ac3e4e15737698284135ca0a73b551755565016ef1df9ec73c4d2c51f8

Observation f0e6c3cb-3f80-4096-ac38-131b40c56e5f · outbound

This paper cites The Curious Case of Neural Text Degeneration.

UCD: Unlearning in LLMs via Contrastive Decoding The Curious Case of Neural Text Degeneration

Reference 6

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source=pdf_text observed=2026-08-07T04:22:59.825555Z digest=sha256:4c8c0ada53b9ce35eefc6cf08417954a3ce2c42f760e4add6c2086624a11a748

Observation dd170ef7-ebf7-43e9-b8c2-33c187d041dc · outbound

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

UCD: Unlearning in LLMs via Contrastive Decoding Knowledge Unlearning for Mitigating Privacy Risks in Language Models

Reference 9

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source=pdf_text observed=2026-08-07T04:22:59.834998Z digest=sha256:ad3a09a828df67a53c7781b70d9c4e2b217fa55af069a6756d76ab757ef485f6

Observation 34885555-89a7-414f-907e-9add76874f60 · outbound

This paper cites SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning.

UCD: Unlearning in LLMs via Contrastive Decoding SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning

Reference 10

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source=pdf_text observed=2026-08-07T04:22:59.838143Z digest=sha256:b3e6e345ded2b294c5d65fefea92f5a1ea7b224d0aa1da6198775fc957eac629

Observation 329dd458-b6ee-4f3c-bbaa-24217d06738c · outbound

This paper cites Copyright Violations and Large Language Models.

UCD: Unlearning in LLMs via Contrastive Decoding Copyright Violations and Large Language Models

Reference 12

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source=pdf_text observed=2026-08-07T04:22:59.843628Z digest=sha256:8ac66382fffa59c258cbdfac3063e7683728765ea8613ba91e65423cfbd59fe8

Observation 49db2240-9d9d-4762-8b4f-65c67d34b511 · outbound

This paper cites Australia to consider european-style right to be forgotten privacy laws.The Guardian (Jan.

UCD: Unlearning in LLMs via Contrastive Decoding Australia to consider european-style right to be forgotten privacy laws.The Guardian (Jan

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T04:22:59.846402Z digest=sha256:fa837e1f7c1b73cb9b667f6ad9ad7be8251a71bd60844a91ba6be3c69a9ece23

Observation d94c10cb-cbb0-474f-b455-2d2713f591e9 · outbound

This paper cites Privacy Adhering Machine Un-learning in NLP.

UCD: Unlearning in LLMs via Contrastive Decoding Privacy Adhering Machine Un-learning in NLP

Reference 14

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source=pdf_text observed=2026-08-07T04:22:59.849083Z digest=sha256:86486963f3888134838ed051378f96130fe52c30936bb1c9835ba4bfe637b01e

Observation 6cdbc6cf-2bed-42a4-8f4a-2eca7ff878a9 · outbound

This paper cites Exact unlearning of finetuning data via model merging at scale.

UCD: Unlearning in LLMs via Contrastive Decoding Exact unlearning of finetuning data via model merging at scale

Reference 15

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T04:22:59.851890Z digest=sha256:8df95a3713215ef3a2541fded94cf177a5b36c9e0f5086c7143e67e490dee6a3

Observation 4a3f03c1-5b21-47be-a4e4-6e898f273136 · outbound

This paper cites The Approximate Fisher Influence Function: Faster Estimation of Data Influence in Statistical Models.

UCD: Unlearning in LLMs via Contrastive Decoding The Approximate Fisher Influence Function: Faster Estimation of Data Influence in Statistical Models

Reference 16

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source=pdf_text observed=2026-08-07T04:22:59.854416Z digest=sha256:5952d652c8395658b442a5c78d61a7ed0eb5de4daf31604ef2d75b8b9be32eff

Observation 322db20a-563d-447e-bcf3-eea808321189 · outbound

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

UCD: Unlearning in LLMs via Contrastive Decoding The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning

Reference 17

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source=pdf_text observed=2026-08-07T04:22:59.858064Z digest=sha256:333b0c1956ad09e89b15e5c1a293b0766928c72b80f0a18d8cb939e7e3e002c7

Observation 255544c7-6660-4267-a05d-4fbcfec973f8 · outbound

This paper cites URL https://aclanthology.org/2023.acl-long.687/.

UCD: Unlearning in LLMs via Contrastive Decoding URL https://aclanthology.org/2023.acl-long.687/

Reference 18

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source=pdf_text observed=2026-08-07T04:22:59.860769Z digest=sha256:900e63834cf0f5fb4a8d287647253904591973b509396dc2ada6ffcffc17a00b

Observation 5895ce17-df25-4108-87dd-1bf18d44e958 · outbound

This paper cites Large Language Model Unlearning via Embedding-Corrupted Prompts.

UCD: Unlearning in LLMs via Contrastive Decoding Large Language Model Unlearning via Embedding-Corrupted Prompts

Reference 19

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source=pdf_text observed=2026-08-07T04:22:59.864196Z digest=sha256:8ae601e446fe729e7a8e2038a783b47a5cedd3348205887638c6835d2a8c9131

Observation cc4782b7-50e4-4a7d-848e-1ebc2bfd9f7d · outbound

This paper cites An Adversarial Perspective on Machine Unlearning for AI Safety.

UCD: Unlearning in LLMs via Contrastive Decoding An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 20

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source=pdf_text observed=2026-08-07T04:22:59.866876Z digest=sha256:30cf6a060ed744c99f6e476bb24bcea09ed1f9e01e8699c525c0929bdabbef41

Observation 5e752cda-02d1-4af4-b6ae-b61f71c8710b · outbound

This paper cites Locating and Editing Factual Associations in GPT.

UCD: Unlearning in LLMs via Contrastive Decoding Locating and Editing Factual Associations in GPT

Reference 21

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source=pdf_text observed=2026-08-07T04:22:59.870189Z digest=sha256:e61b5ce38f3880603a9c3a23d5019af29b7d15a486ce2e09beece62e0e824cc4

Observation d0229e49-9182-4556-b063-23278f02ce24 · outbound

This paper cites Fast Model Editing at Scale.

UCD: Unlearning in LLMs via Contrastive Decoding Fast Model Editing at Scale

Reference 22

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source=pdf_text observed=2026-08-07T04:22:59.873157Z digest=sha256:995a0036a6ab8a4d55327eec5d681486337f86f7f12ada87d4515c8fc21a3896

Observation 4bff8cbd-0953-40ba-9515-f7c8f7be6fcc · outbound

This paper cites A Survey of Machine Unlearning.

UCD: Unlearning in LLMs via Contrastive Decoding A Survey of Machine Unlearning

Reference 23

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source=pdf_text observed=2026-08-07T04:22:59.875845Z digest=sha256:27164af6d57bacbbad556693a6496074ba04f2121cc4c4acab4617ee28dbee27

Observation 78242598-fac4-4a9d-bb21-549d0253b68b · outbound

This paper cites Contrastive Decoding Improves Reasoning in Large Language Models.

UCD: Unlearning in LLMs via Contrastive Decoding Contrastive Decoding Improves Reasoning in Large Language Models

Reference 24

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source=pdf_text observed=2026-08-07T04:22:59.878544Z digest=sha256:7157b4da92de3a6aaf8292bd189dae1f42ac84a0171375620d0c7376333f9606

Observation 41250d86-af8c-4665-a359-52d40c756c20 · outbound

This paper cites In-Context Unlearning: Language Models as Few Shot Unlearners.

UCD: Unlearning in LLMs via Contrastive Decoding In-Context Unlearning: Language Models as Few Shot Unlearners

Reference 25

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source=pdf_text observed=2026-08-07T04:22:59.881912Z digest=sha256:2b96597c50191cf628a611695c96c90f9ab45daaf1aee3fed3cbfb35a42df452

Observation 9c143aa9-3f8e-440b-8d71-c2a3927530e5 · outbound

This paper cites Rethinking LLM Memorization through the Lens of Adversarial Compression.

UCD: Unlearning in LLMs via Contrastive Decoding Rethinking LLM Memorization through the Lens of Adversarial Compression

Reference 26

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source=pdf_text observed=2026-08-07T04:22:59.884621Z digest=sha256:f4f04f7ea55c8191dfafaeb33d18e3188f5e288ed633e3fa2c8aead8fe89395f

Observation 1c6d6086-2acf-4e2d-bf5f-454524113818 · outbound

This paper cites Model evaluation for extreme risks.

UCD: Unlearning in LLMs via Contrastive Decoding Model evaluation for extreme risks

Reference 27

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source=pdf_text observed=2026-08-07T04:22:59.887715Z digest=sha256:9e126da5619c836161dd4f7060bf237738a3003dcd65025a178e06ed1f1a8eae

Observation c1b168b5-ead6-4261-9e02-2c33268bef52 · outbound

This paper cites Detecting Pretraining Data from Large Language Models.

UCD: Unlearning in LLMs via Contrastive Decoding Detecting Pretraining Data from Large Language Models

Reference 28

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source=pdf_text observed=2026-08-07T04:22:59.890884Z digest=sha256:6cdb2de5af6b960e86cc3a5637dd77acd24ec75a09530cd6177af5c53f6760a4

Observation 53dedfd4-d3c9-427d-bd74-50ad5c774532 · outbound

This paper cites MUSE: Machine Unlearning Six-Way Evaluation for Language Models.

UCD: Unlearning in LLMs via Contrastive Decoding MUSE: Machine Unlearning Six-Way Evaluation for Language Models

Reference 29

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source=pdf_text observed=2026-08-07T04:22:59.893510Z digest=sha256:8b3f76454e79b7e5ea3bfeda81b2b0bf12025105bac4cfbebac2487bc7d9f89a

Observation 69539e73-f8c2-420c-8550-e71b436dc8ce · outbound

This paper cites Guardrail Baselines for Unlearning in LLMs.

UCD: Unlearning in LLMs via Contrastive Decoding Guardrail Baselines for Unlearning in LLMs

Reference 30

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source=pdf_text observed=2026-08-07T04:22:59.895995Z digest=sha256:ae190e72616663f7d2a7c4f2b50e19627a19c9049381365e011f6628c637a971

Observation e8b48618-9ec6-41d2-b9c0-7b2731102926 · outbound

This paper cites GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-time Alignment.

UCD: Unlearning in LLMs via Contrastive Decoding GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-time Alignment

Reference 32

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source=pdf_text observed=2026-08-07T04:22:59.901678Z digest=sha256:b12ec97ae8f02b41c9bb2e7c24e7a3da157dbaaa8c6e05fd9b3645c8d9f8eb67

Observation 827233c1-a2d2-420b-8c5c-6a47c90fc52f · outbound

This paper cites Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities.

UCD: Unlearning in LLMs via Contrastive Decoding Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities

Reference 33

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source=pdf_text observed=2026-08-07T04:22:59.904872Z digest=sha256:d7b18bf78be8ffb4a9fcf15dc2cacbd5ffd2adf4b62e9d6141142a6f3d0d270f

Observation e68cfed9-9054-4469-94ac-37357192de68 · outbound

This paper cites Large Language Model Unlearning.

UCD: Unlearning in LLMs via Contrastive Decoding Large Language Model Unlearning

Reference 34

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source=pdf_text observed=2026-08-07T04:22:59.907434Z digest=sha256:de118307c70a2462cc5a8ba6d272e8c39fdbb76de17d321edff94faaec688bfe

Observation 0ecf4d90-f30f-4c76-8056-cdf97e422faa · outbound

This paper cites an unresolved cited work.

UCD: Unlearning in LLMs via Contrastive Decoding Unresolved cited work

Reference 35

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source=pdf_text observed=2026-08-07T04:22:59.910903Z digest=sha256:1b927f1448fc75d413cde1f66a3f09c3145a924cda2983bf1b588010bc6396e6

Observation 8e44b40c-6d6c-40b2-83a1-4d938b5fe952 · outbound

This paper cites Large Scale Knowledge Washing.

UCD: Unlearning in LLMs via Contrastive Decoding Large Scale Knowledge Washing

Reference 2017

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source=pdf_text observed=2026-08-07T04:22:59.898593Z digest=sha256:a2704238e412a620f8537e3a01169a483c8dfe10d7ddb7d7b809baaeeb94e8dc

Observation d2a137df-ba47-48f6-ade7-9f67f15f0b0c · outbound

This paper cites Open Problems in Machine Unlearning for AI Safety.

UCD: Unlearning in LLMs via Contrastive Decoding Open Problems in Machine Unlearning for AI Safety

Reference 2018

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source=pdf_text observed=2026-08-07T04:22:59.810289Z digest=sha256:56557f8404e963491d07a941942ef765ff0c1de0d0de0001726969783995e95b

Observation 1aaa9bff-bac8-42ca-bafb-a768cbbabd67 · outbound

This paper cites Editing Models with Task Arithmetic.

UCD: Unlearning in LLMs via Contrastive Decoding Editing Models with Task Arithmetic

Reference 2019

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source=pdf_text observed=2026-08-07T04:22:59.828238Z digest=sha256:b161e3e4f5c7795844a65212af18df14fe2cd680338e18f391589f11e886f6fe

Observation 8c84f387-aa71-418f-8cea-2447f1d53455 · outbound

This paper cites Towards making systems forget with machine unlearning.

UCD: Unlearning in LLMs via Contrastive Decoding Towards making systems forget with machine unlearning

Reference 2021

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source=pdf_text observed=2026-08-07T04:22:59.813723Z digest=sha256:ede1730c72d63ee4ce5c33cd27a04c8aadaebd1ae9108accc2e6a12593d5a335

Observation d02afec1-a00d-40bb-8752-45c832522f89 · outbound

This paper cites Knowledge Sanitization of Large Language Models.

UCD: Unlearning in LLMs via Contrastive Decoding Knowledge Sanitization of Large Language Models

Reference 2022

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source=pdf_text observed=2026-08-07T04:22:59.831196Z digest=sha256:ec0a7bee755502611cc42e379c143932d8e759dcce99aa2849d59edec04ae66e

Observation 103e6e45-fb35-4abe-a527-3646daba9f93 · outbound

This paper cites Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning.

UCD: Unlearning in LLMs via Contrastive Decoding Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning

Reference 2023

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source=pdf_text observed=2026-08-07T04:22:59.819768Z digest=sha256:e3a3f829873ac6fc5e05e2108111a611f35cba0c303b2347295e0830f98b105c

Observation 12dfb38b-4edb-43e2-ad3f-b217c92335d8 · outbound

This paper cites Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs.

UCD: Unlearning in LLMs via Contrastive Decoding Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs

Reference 2024

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source=pdf_text observed=2026-08-07T04:22:59.840985Z digest=sha256:d59df4a3cd54786ad3c17075f0566aed49e0c8c99ec6c7b78f8195cddec57d4c

Pith citing papers

Observation f06d5aa0-ee68-4816-aec3-f5997d1989ce · inbound

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning cites this paper.

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning UCD: Unlearning in LLMs via Contrastive Decoding

Reference 29

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arxiv_id, observed 2026-05-18T10:46:17.078729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-18T10:44:53.516653Z digest=sha256:bfad484e15c963a90dce8ded20ee7a7ed02ad51c44038cd922420a7747b3d55a

Observation b3da7110-58c7-4b87-a8e8-0c58e8e65a9f · inbound

Divergence Decoding: Inference-Time Unlearning via Auxiliary Models cites this paper.

Divergence Decoding: Inference-Time Unlearning via Auxiliary Models UCD: Unlearning in LLMs via Contrastive Decoding

Reference 12

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verified exact
arxiv_id, observed 2026-07-01T19:16:01.069309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-28T22:53:34.701967Z digest=sha256:c9cc676753a6a0a483c44d698d8d2df2ba309ef3743756f0588ec178e3d78291

Observation d076171f-e8dc-4c41-8a16-aa5a4a2b3e90 · inbound

Position: The Term "Machine Unlearning" Is Overused in LLMs cites this paper.

Position: The Term "Machine Unlearning" Is Overused in LLMs UCD: Unlearning in LLMs via Contrastive Decoding

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T13:25:44.961912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-30T23:21:28.103297Z digest=sha256:9e3e13b870c1b704887b06da980162d7622c2aa1b1c03a460137d1035b26c630