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Paper Citation Record · LEDGER

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs

As of 10 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2506.14003.

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

pith.paper-citation-record.v1
2506.14003 v5

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:29:39.623798Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T06:49:12.070481Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T14:58:33.258552Z

Reference resolution

40 of 40 outbound references displayed

  • verified exact1
  • verified fuzzy9
  • unresolved29
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2e166c7c-cd2f-47c9-8fbf-6251e54a6ddc · outbound

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

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Open Problems in Machine Unlearning for AI Safety

Reference 1

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source=pdf_text observed=2026-08-07T00:29:34.908539Z digest=sha256:c74f7d4c080a470b31463402fdaa447da5b8d7beb17bd181add1ad0e86accc48

Observation 2c3329a7-35e7-4577-891e-2606deba6fef · outbound

This paper cites forget” prompt drawn from the WMDP evaluation set, which tests the model’s ability to omit specific target knowledge, and (2) a “forget- irrelevant.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs forget” prompt drawn from the WMDP evaluation set, which tests the model’s ability to omit specific target knowledge, and (2) a “forget- irrelevant

Reference 3

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Observation dd3fb1f0-9a06-4a83-8f1b-313a378b6989 · outbound

This paper cites role": "user.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs role": "user

Reference 4

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Observation 1989a63b-e8e5-433e-907b-79b61e2d7b8a · outbound

This paper cites forget” prompts, and above 98% on UltraChat for all models. Train- ing on forget-only data (Sf) likewise yields over 97% detection on “forget irrelevant.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs forget” prompts, and above 98% on UltraChat for all models. Train- ing on forget-only data (Sf) likewise yields over 97% detection on “forget irrelevant

Reference 6

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 793011d6-1741-4770-99b1-d7f53cd85e53 · outbound

This paper cites Measuring massive multitask language understanding.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Measuring massive multitask language understanding

Reference 8

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source=pdf_text observed=2026-08-07T00:29:35.721991Z digest=sha256:cfc0078ef141559f21b9c6bb93e442d2d1f4360644d21cec4cc285f9c1af8dea

Observation dc44e36b-f286-4506-bc03-3c85c88e5693 · outbound

This paper cites Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Reference 10

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source=pdf_text observed=2026-08-07T00:29:35.986007Z digest=sha256:2c6b0499cbc64e9ece56607b96c1ebd71929da76c1c096d306fb0e52f0609c12

Observation 89066222-4259-45bf-a780-2bd53ea509f4 · outbound

This paper cites Editing Models with Task Arithmetic.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Editing Models with Task Arithmetic

Reference 11

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source=pdf_text observed=2026-08-07T00:29:36.151843Z digest=sha256:6b01af7ef7c2c7f3ac1609ac0a63f6b2ea6a35c874477b2c71502d06aa82bdd6

Observation 184ca9d9-ee8e-451e-9709-a550cc453ae2 · outbound

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

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning

Reference 13

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source=pdf_text observed=2026-08-07T00:29:36.377364Z digest=sha256:36ed84c878727b16ba5de90d44e241cf0e7c3148b0b2c54215bf534dc6cd1d90

Observation 227d9c44-a5c2-40ad-9239-335234cbb5fc · outbound

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

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 14

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source=pdf_text observed=2026-08-07T00:29:36.509811Z digest=sha256:79933e570e7b93cc3e413b8cef46d991c59f8dfc10729ef4fdc9f99b924dba9a

Observation d5307c7e-ff97-4704-8c77-78e97c1551e8 · outbound

This paper cites Eight Methods to Evaluate Robust Unlearning in LLMs.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Eight Methods to Evaluate Robust Unlearning in LLMs

Reference 15

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source=pdf_text observed=2026-08-07T00:29:36.619568Z digest=sha256:ecdc5dc1056ad52184762a43f6ef186274004b34ab1ae64cccd325de654383cf

Observation 460f7658-d403-4463-8ad1-9c56b48f15c3 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 16

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source=pdf_text observed=2026-08-07T00:29:36.744747Z digest=sha256:d8773d5946241b471bf01bc54e54437675566216f59324c8058fdf82bea8d171

Observation ee6b2ef6-51bd-4f47-b7f5-282c25a242f8 · outbound

This paper cites CROW: Eliminating Backdoors from Large Language Models via Internal Consistency Regularization.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs CROW: Eliminating Backdoors from Large Language Models via Internal Consistency Regularization

Reference 17

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source=pdf_text observed=2026-08-07T00:29:36.902929Z digest=sha256:8c720a9da47464f6ae691585a6a18acd8c3696a4086825eec3b22801b73b7331

Observation ecf25c02-d2ed-4477-9458-caec2a189a76 · outbound

This paper cites A Survey of Machine Unlearning.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs A Survey of Machine Unlearning

Reference 18

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source=pdf_text observed=2026-08-07T00:29:37.032784Z digest=sha256:b1f8845a51fabf4135df0390f1142c05bfd2cf966dcd0f5fbd15b9bc0f40a3d3

Observation b61e6a1c-0077-476d-bce7-59d4c0fce241 · outbound

This paper cites Model provenance testing for large language models.arXiv preprint arXiv:2502.00706,.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Model provenance testing for large language models.arXiv preprint arXiv:2502.00706,

Reference 19

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source=pdf_text observed=2026-08-07T00:29:37.134690Z digest=sha256:39eb0a5985eb2d56d5481ed33b77714c12045100dcbb752c20b0015bf16d1e14

Observation 76f97e4d-ae80-4bf4-8bf3-10acbdb965c3 · outbound

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

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs In-Context Unlearning: Language Models as Few Shot Unlearners

Reference 20

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source=pdf_text observed=2026-08-07T00:29:37.230777Z digest=sha256:1a750269d99a147b2c2d3a8974e842a9e9ec6b63f56e4acb9e30ff1b71312988

Observation 62674cbd-d081-4dbe-a09c-6a3eb37f1cc3 · outbound

This paper cites The Frontier of Data Erasure: Machine Unlearning for Large Language Models.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs The Frontier of Data Erasure: Machine Unlearning for Large Language Models

Reference 21

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source=pdf_text observed=2026-08-07T00:29:37.309383Z digest=sha256:2bfc8d9d5bffd1cdcc427256720c85f60442a7443b5353668c727a5dc6b06dcc

Observation bfda0d67-4b66-49d4-b861-afc01e3400c4 · outbound

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

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs MUSE: Machine Unlearning Six-Way Evaluation for Language Models

Reference 24

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source=pdf_text observed=2026-08-07T00:29:37.694372Z digest=sha256:26eaf0fd63b92e98ebb668a17446b527cd1c8cfe7418b36ecdf387f6f77f4e81

Observation 3226a965-a5fc-43dc-855c-d6711c3185b1 · outbound

This paper cites Knowledge Unlearning for LLMs: Tasks, Methods, and Challenges.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Knowledge Unlearning for LLMs: Tasks, Methods, and Challenges

Reference 25

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source=pdf_text observed=2026-08-07T00:29:37.808176Z digest=sha256:f8568d841dc028cf45fe147b3b87bb7b0b78f3b8ed925610a6257742b999c3c1

Observation 1d8eb44b-b832-49ee-bc2e-2abce6cb8c85 · outbound

This paper cites Idiosyncrasies in Large Language Models.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Idiosyncrasies in Large Language Models

Reference 26

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Observation 4a980508-a89a-4402-8d49-0425f275fd78 · outbound

This paper cites Guardrail Baselines for Unlearning in LLMs.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Guardrail Baselines for Unlearning in LLMs

Reference 27

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source=pdf_text observed=2026-08-07T00:29:38.082423Z digest=sha256:5fcaf2498df4d1726d9c9cbf98c3679db83ba43ff6cfd7aad40a8cdb292b8010

Observation ca03ba4b-f4a9-4beb-878b-9f21d076d794 · outbound

This paper cites Unrolling sgd: Under- standing factors influencing machine unlearning.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Unrolling sgd: Under- standing factors influencing machine unlearning

Reference 28

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T00:29:38.219481Z digest=sha256:4002510e768d49ed5779ff7fa272e716b3ad15f5015196cf2cad136b4b04ad56

Observation b8f92201-9df0-41e5-b5c7-682ff5e2ce5a · outbound

This paper cites DEPN: Detecting and Editing Privacy Neurons in Pretrained Language Models.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs DEPN: Detecting and Editing Privacy Neurons in Pretrained Language Models

Reference 29

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Observation d69a16c0-9918-470e-9886-5a606ecd8bb0 · outbound

This paper cites A fingerprint for large language models.arXiv preprint arXiv:2407.01235,.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs A fingerprint for large language models.arXiv preprint arXiv:2407.01235,

Reference 30

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source=pdf_text observed=2026-08-07T00:29:38.434169Z digest=sha256:04289672f3e20c56a93cdd737915c73128347e2736715e12f6bb96e79dbb1b78

Observation 2c16152a-b312-42e4-8753-b8f9fd2674e6 · outbound

This paper cites Large Language Model Unlearning.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Large Language Model Unlearning

Reference 31

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source=pdf_text observed=2026-08-07T00:29:38.583685Z digest=sha256:7aed594648047b517d0584413bfc1aa078a57841f18b07d8fbdbe48986abab2c

Observation f92521d0-e0ff-4d44-a7d4-d11acdee325a · outbound

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

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning

Reference 32

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source=pdf_text observed=2026-08-07T00:29:38.744476Z digest=sha256:30888b2f9c5cd12e1dc7f506dcdfed3450839a3e9c8de55206c6f853004ae9fd

Observation 16809980-21cd-4dd3-9019-f24c9e0465d7 · outbound

This paper cites UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models

Reference 33

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Observation 29553f39-d40b-40ab-af98-ef6484dea201 · outbound

This paper cites Tamm: Triadapter multi-modal learning for 3d shape understanding.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Tamm: Triadapter multi-modal learning for 3d shape understanding

Reference 34

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source=pdf_text observed=2026-08-07T00:29:38.990301Z digest=sha256:83e7e463e63a4cc7d4b177a9d814511d902ea5f8a470582c8ed53fac3e164043

Observation 02f12c69-a25c-4bd4-b596-31d97e29e1de · outbound

This paper cites Independence Tests for Language Models.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Independence Tests for Language Models

Reference 35

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Observation b8b2b163-85ed-4645-b42d-4a6d30712853 · outbound

This paper cites 5, we present the supervised UMAP projections of the final activations from different models inFig.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs 5, we present the supervised UMAP projections of the final activations from different models inFig

Reference 39

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Observation bd601793-c55b-4756-bc88-b516081fcb56 · outbound

This paper cites Both evaluations report the accuracy on four-choice question answering.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Both evaluations report the accuracy on four-choice question answering

Reference 2003

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source=pdf_text observed=2026-08-07T00:29:39.204815Z digest=sha256:ff648f6d3cfbd454e303b94bdbe5bb63c4043bd04f76b1b72e6532afb34b56a1

Observation 4ab2cb67-5ceb-4a61-b78a-855c2da85004 · outbound

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

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Unlearn What You Want to Forget: Efficient Unlearning for LLMs

Reference 2015

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source=pdf_text observed=2026-08-07T00:29:35.001839Z digest=sha256:db104c7e717deaedaf91fadceb23073a3bdf44438e05c1420a01f279ff1144b3

Observation 97e4c419-62ee-44b0-8b9d-d8bd9b56035e · outbound

This paper cites An Approach to Technical AGI Safety and Security.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs An Approach to Technical AGI Safety and Security

Reference 2016

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source=pdf_text observed=2026-08-07T00:29:37.550916Z digest=sha256:ec3cb66d0e0301f331468f998a3a1ab9b9351d45dd3d497372b79b753fa300be

Observation 01e30e16-c906-4588-a0c1-b81ac63f55c6 · outbound

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

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Knowledge Unlearning for Mitigating Privacy Risks in Language Models

Reference 2018

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source=pdf_text observed=2026-08-07T00:29:36.258693Z digest=sha256:cd076a6dda97ec1f7675b6edf88e7e3d5e4d442a50f23df183747a5197ad45cf

Observation 781ad25d-09ba-40a5-bdc5-5cd665d73c2d · outbound

This paper cites Jogging the memory of unlearned models through targeted relearning attacks.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Jogging the memory of unlearned models through targeted relearning attacks

Reference 2019

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raw_fallback, observed 2026-08-07T00:29:42.589838Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T00:29:35.857573Z digest=sha256:31406b337bc0aa5e9570b6d7cea2adc7a6ad6f7d2077d2e943dd0f5d858fa4a7

Observation c7711d74-f07c-4d67-bf4b-5ea719eee5f4 · outbound

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

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Regulation (eu) 2016/679 of the european parliament and of the council

Reference 2020

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raw_fallback, observed 2026-08-07T00:29:42.316310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T00:29:37.443872Z digest=sha256:b14184eaa2b5233e4c262cf512f297adce90c8c745c660634ba6a2839eaa2eab

Observation ce3262ff-1568-4f5b-a3fd-c9a5b5b2350a · outbound

This paper cites Simplicity prevails: Rethinking negative preference optimization for llm unlearning.arXiv preprint arXiv:2410.07163,.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Simplicity prevails: Rethinking negative preference optimization for llm unlearning.arXiv preprint arXiv:2410.07163,

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-07T00:29:35.574913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:29:35.574913Z digest=sha256:9f3bdc33e54c393a747308a8b50553adc590a9f38eb9a095fba0de2e5bc665a0

Observation b4d24ac3-df92-400a-94eb-00c1b892ea1d · outbound

This paper cites Safety Mirage: How Spurious Correlations Undermine VLM Safety Fine-Tuning and Can Be Mitigated by Machine Unlearning.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Safety Mirage: How Spurious Correlations Undermine VLM Safety Fine-Tuning and Can Be Mitigated by Machine Unlearning

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-07T00:29:35.246287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:29:35.246287Z digest=sha256:302aea6ec3df800f0ff49ab3b6c39a008738ab97a834f49a6e6a990d70768269

Observation b2982730-17ba-4a00-8b4f-223e125321b1 · outbound

This paper cites When machine unlearning jeopardizes privacy.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs When machine unlearning jeopardizes privacy

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:29:42.812670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T00:29:35.112978Z digest=sha256:338f4064e81979cbbc56deee405ac7b24c1f8f132f1af2f726f68030b96e7961

Observation 59a716f1-489a-4f4e-beec-8765cfeb6d3f · outbound

This paper cites Do Unlearning Methods Remove Information from Language Model Weights?.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Do Unlearning Methods Remove Information from Language Model Weights?

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T00:29:35.464938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:29:35.464938Z digest=sha256:370807cc75bf428f1b18aa7f52e6908ecf5d06c4d13d07b78c318d1492453441

Observation ee45d036-973b-475c-969f-30a03eb3a631 · outbound

This paper cites Machine unlearning doesn’t do what you think: Lessons for generative ai policy, research, and practice.arXiv preprint arXiv:2412.06966,.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Machine unlearning doesn’t do what you think: Lessons for generative ai policy, research, and practice.arXiv preprint arXiv:2412.06966,

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-07T00:29:35.364619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:29:35.364619Z digest=sha256:fb96f9a7a10c9a730cabf86a9719bb5561d62fa1440a293ba1cf2d2f94f9bcac

Pith citing papers

Observation c903e360-09e4-4201-a40d-c44c1eb6dbf9 · inbound

SENTINEL: Failure-Driven Reinforcement Learning for Training Tool-Using Language Model Agents cites this paper.

SENTINEL: Failure-Driven Reinforcement Learning for Training Tool-Using Language Model Agents Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs

Reference 40

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T14:58:33.259815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-27T06:49:12.070481Z digest=sha256:e1115d7605072cb5349c140c41fcc96b679ce1085b4e669bd3aa4aa8fd69d905