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Paper Citation Record · LEDGER

Agents Are All You Need for LLM Unlearning

As of 10 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 3 inbound Pith citation observations for arXiv:2502.00406.

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

pith.paper-citation-record.v1
2502.00406 v2

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:14:53.773835Z

measured 53 of 53 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:58:51.628600Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T19:42:36.167843Z

Reference resolution

50 of 50 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved44
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 73ca1e57-ce3e-4135-a47e-4a8cd85c654d · outbound

This paper cites Phi-4 Technical Report.

Agents Are All You Need for LLM Unlearning Phi-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-09T19:14:53.161357Z digest=sha256:cdf807f7eb0004c4a2950af09e931d136e7fb30b1a83f48c6c8dd3ab4db0a14a

Observation 697a1c6b-8916-44af-9c49-39c0a9307c6e · outbound

This paper cites Qwen Technical Report.

Agents Are All You Need for LLM Unlearning Qwen Technical Report

Reference 4

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source=pdf_text observed=2026-08-09T19:14:53.242538Z digest=sha256:438171d7fc2e2cae84b68d5960c1e09c6660cd885a0882904a5b2180b21b439e

Observation 80bb09f6-82ba-429a-a1a3-db5b40ec17e1 · outbound

This paper cites Language Models are Few-Shot Learners.

Agents Are All You Need for LLM Unlearning Language Models are Few-Shot Learners

Reference 5

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source=pdf_text observed=2026-08-09T19:14:53.245422Z digest=sha256:f1c0d7f62510cce27c03a99fa582464c6a8fcab908cae0ead400580706bbeb3d

Observation 459a3ca5-7c14-4fae-a174-ba13850b0e30 · outbound

This paper cites ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate.

Agents Are All You Need for LLM Unlearning ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate

Reference 7

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source=pdf_text observed=2026-08-09T19:14:53.253246Z digest=sha256:acddb23993f65ed56e9823021920311b58386ea2e4b495d9752d5c09aeb8b5e3

Observation fd9efe78-0e13-47c1-9139-f480535c00e7 · outbound

This paper cites Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal Transport.

Agents Are All You Need for LLM Unlearning Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal Transport

Reference 8

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source=pdf_text observed=2026-08-09T19:14:53.256517Z digest=sha256:036defc17fddc19a98e4e865b7b2bcb1fc532262cbe8e76770ad304242122697

Observation d4da03d3-2819-4841-8be7-58c05f293e89 · outbound

This paper cites Who's Harry Potter? Approximate Unlearning in LLMs.

Agents Are All You Need for LLM Unlearning Who's Harry Potter? Approximate Unlearning in LLMs

Reference 9

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source=pdf_text observed=2026-08-09T19:14:53.259874Z digest=sha256:c3dbc903195deec37872681d25d1575b8b2f5321474778e37dd4a0481a4378af

Observation b0dc0990-d8a3-46b7-88cb-9ab153025538 · outbound

This paper cites SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation.

Agents Are All You Need for LLM Unlearning SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation

Reference 10

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source=pdf_text observed=2026-08-09T19:14:53.263583Z digest=sha256:dadcde8ca9fe853101d4abd58f5e6a47ef472f71b481e7bc5d7fedae0c0825fb

Observation 2274bd20-2e82-44ec-97e7-f49a15c8fae4 · outbound

This paper cites LLM Agents can Autonomously Hack Websites.

Agents Are All You Need for LLM Unlearning LLM Agents can Autonomously Hack Websites

Reference 11

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source=pdf_text observed=2026-08-09T19:14:53.267105Z digest=sha256:c00622d6ee24a2e9519486a9c86c0eb39be9da6aba0bee8867b2fb8d00686b7a

Observation 5e091109-17eb-48bb-8eb0-f5a0890ecadd · outbound

This paper cites Fast Machine Unlearning Without Retraining Through Selective Synaptic Dampening.

Agents Are All You Need for LLM Unlearning Fast Machine Unlearning Without Retraining Through Selective Synaptic Dampening

Reference 12

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source=pdf_text observed=2026-08-09T19:14:53.270423Z digest=sha256:b88820626412305a289ff91251770a1d0f1e5e0137a368e7918603fada5907a8

Observation 1aececc8-a8d7-4922-b474-9465513b3409 · outbound

This paper cites The Llama 3 Herd of Models.

Agents Are All You Need for LLM Unlearning The Llama 3 Herd of Models

Reference 13

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source=pdf_text observed=2026-08-09T19:14:53.290678Z digest=sha256:e20a78795774759249636cb32726fe1efadc3d84fd2b005134bfe0940eacf041

Observation a635404a-a149-49ee-9327-e0304b5a9188 · outbound

This paper cites Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue.

Agents Are All You Need for LLM Unlearning Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue

Reference 14

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source=pdf_text observed=2026-08-09T19:14:53.382326Z digest=sha256:c306f85876f219381ea176b80f9024c6994ef682ae288b795ed2ea8646b9b285

Observation 5b95cae4-ac6a-4c83-8af2-7848a02177eb · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Agents Are All You Need for LLM Unlearning DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 15

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source=pdf_text observed=2026-08-09T19:14:53.483060Z digest=sha256:0bdce6b1ed4ac91e75872a662802328439ceacc0e572a7c50f168b91ff82edac

Observation 2018ba52-e5a2-4390-b4aa-44ce1e9dc078 · outbound

This paper cites Risk and Response in Large Language Models: Evaluating Key Threat Categories.

Agents Are All You Need for LLM Unlearning Risk and Response in Large Language Models: Evaluating Key Threat Categories

Reference 16

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source=pdf_text observed=2026-08-09T19:14:53.485638Z digest=sha256:1909dd2c02ce421b8822a04264109566a4b8700bcc0791f31ed404500f47b5ba

Observation ac1fdc6b-31ae-46e3-b258-982c56e5ce44 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Agents Are All You Need for LLM Unlearning LoRA: Low-Rank Adaptation of Large Language Models

Reference 18

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source=pdf_text observed=2026-08-09T19:14:53.492040Z digest=sha256:54e396827d64f53b95cd63ecdcb76f351d97dc8682b402d005f5da6788821485

Observation 4f29d603-e913-4e26-980b-a9d54e9cd7f5 · outbound

This paper cites Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy.

Agents Are All You Need for LLM Unlearning Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy

Reference 19

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source=pdf_text observed=2026-08-09T19:14:53.495399Z digest=sha256:0e6131a523c0b18f84a054a0217808a55f1d2759822b42cdbd320aef0d8bca1d

Observation 55806582-a37b-4bc8-824f-7fd18e833c1c · outbound

This paper cites Copyright Violations and Large Language Models.

Agents Are All You Need for LLM Unlearning Copyright Violations and Large Language Models

Reference 21

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source=pdf_text observed=2026-08-09T19:14:53.502562Z digest=sha256:860e3ea6672b15ecbad918c9d7aab1a3c69517a4b76c6899aa547cda65bb7c92

Observation e3967cc9-f1b6-480b-9cde-3dd1a1d62a3b · outbound

This paper cites Black-Box Forgetting.

Agents Are All You Need for LLM Unlearning Black-Box Forgetting

Reference 22

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local_arxiv, observed 2026-08-09T19:14:54.409098Z

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source=pdf_text observed=2026-08-09T19:14:53.506125Z digest=sha256:c68a2b2e5f515b10b94d7cc15b87c15650990138ead86cf485a55f6d6ef3eba4

Observation 428d67e5-a9b9-4ade-9bf1-37c8a8441d2e · outbound

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

Agents Are All You Need for LLM Unlearning The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning

Reference 23

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source=pdf_text observed=2026-08-09T19:14:53.509663Z digest=sha256:bddfcaac188da0ce9c958ef1252f052b589aa454764a196877c725ee997f1dba

Observation 3a0fb0af-2ff1-4190-a963-804e5f1565c7 · outbound

This paper cites Let's Verify Step by Step.

Agents Are All You Need for LLM Unlearning Let's Verify Step by Step

Reference 24

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source=pdf_text observed=2026-08-09T19:14:53.512881Z digest=sha256:d0faa1d22cbff173570ae18c713b647d7bbdb7d66a1cc71f555fc5e48c9b3d46

Observation a211bf3b-75b7-42ee-b05f-fc00526cfa38 · outbound

This paper cites TOFU: A Task of Fictitious Unlearning for LLMs.

Agents Are All You Need for LLM Unlearning TOFU: A Task of Fictitious Unlearning for LLMs

Reference 26

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source=pdf_text observed=2026-08-09T19:14:53.647422Z digest=sha256:59d57cd47f68bb86e9e5622be77cdd825c8789139af1d0d876a4b5671342de4a

Observation 2c41d5a4-730b-4c3a-8a68-191552b8341d · outbound

This paper cites PRP: Propagating Universal Perturbations to Attack Large Language Model Guard-Rails.

Agents Are All You Need for LLM Unlearning PRP: Propagating Universal Perturbations to Attack Large Language Model Guard-Rails

Reference 27

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source=pdf_text observed=2026-08-09T19:14:53.691478Z digest=sha256:50df0f01fe69b0f3ea135b6a67fe3abb42ed44de1f7b4344afe34b9bb2877412

Observation 9a9efc22-efc0-474e-8654-fb0db30ac74e · outbound

This paper cites 3 12 Seth Neel, Aaron Roth, and Saeed Sharifi-Malvajerdi.

Agents Are All You Need for LLM Unlearning 3 12 Seth Neel, Aaron Roth, and Saeed Sharifi-Malvajerdi

Reference 29

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source=pdf_text observed=2026-08-09T19:14:53.698712Z digest=sha256:b70f4e08c3c2f23d0b7ea3ed21de0e0aaba8827610d918a61d58a52f334ba0fb

Observation 4b20c1e0-aa67-4f89-8ba7-c5849a1762ed · outbound

This paper cites Descent-to-Delete: Gradient-Based Methods for Machine Unlearning.

Agents Are All You Need for LLM Unlearning Descent-to-Delete: Gradient-Based Methods for Machine Unlearning

Reference 30

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source=pdf_text observed=2026-08-09T19:14:53.702008Z digest=sha256:e5c992c88e2b8ffa7a239d9e04f56cf5b8b31963856924241d7f3800ae96ec69

Observation 5d520179-86f4-4f8f-ae9f-e00c90236449 · outbound

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

Agents Are All You Need for LLM Unlearning In-Context Unlearning: Language Models as Few Shot Unlearners

Reference 31

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source=pdf_text observed=2026-08-09T19:14:53.705924Z digest=sha256:41ba2437c7bc2cb35d8031722a4fbb76c3c05816740c87abcb09ff0ccc2c411f

Observation 41a1fa52-d708-4f25-817a-bc453e68e948 · outbound

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

Agents Are All You Need for LLM Unlearning Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 32

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source=pdf_text observed=2026-08-09T19:14:53.709757Z digest=sha256:b98e69aeb65cdc85d7fbacf4d699a7fa6ea648fc9abb527f85fade70593298a9

Observation da36e0d7-812a-4822-b9ab-cf67e46b317f · outbound

This paper cites Tricking LLMs into Disobedience: Formalizing, Analyzing, and Detecting Jailbreaks.

Agents Are All You Need for LLM Unlearning Tricking LLMs into Disobedience: Formalizing, Analyzing, and Detecting Jailbreaks

Reference 33

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source=pdf_text observed=2026-08-09T19:14:53.713226Z digest=sha256:d79e754027bf7a7f9f11151a4edc07bbf16001dbf50ca112264246a608a711c0

Observation 5d2df703-41cf-46eb-b373-a70eab7856fa · outbound

This paper cites SNAP: Self-Supervised Neural Maps for Visual Positioning and Semantic Understanding.

Agents Are All You Need for LLM Unlearning SNAP: Self-Supervised Neural Maps for Visual Positioning and Semantic Understanding

Reference 34

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local_arxiv, observed 2026-08-09T19:14:54.268517Z

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source=pdf_text observed=2026-08-09T19:14:53.716757Z digest=sha256:7434c8ff6ee9cbfcbd8b36c382575c655aa14d5432f85fcfb7148d816019cb3d

Observation 3d848e5d-3895-4631-9e7a-b58f4573cde8 · outbound

This paper cites Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation.

Agents Are All You Need for LLM Unlearning Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation

Reference 35

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source=pdf_text observed=2026-08-09T19:14:53.721398Z digest=sha256:d0db593687e8bd83139c92ede19301528c997718f9f0ce741d4f296473b3bab9

Observation a3201ef9-3f6f-415c-92f0-79164b48e087 · outbound

This paper cites "Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models.

Agents Are All You Need for LLM Unlearning "Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models

Reference 36

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source=pdf_text observed=2026-08-09T19:14:53.725058Z digest=sha256:3d437eee05bd3bf5fde34ff131c1fa6a77edf5d276a95dd5d0bb6130d547b365

Observation 6a2e52a1-6cd6-461a-9aea-2266498ff86d · outbound

This paper cites UnStar: Unlearning with Self-Taught Anti-Sample Reasoning for LLMs.

Agents Are All You Need for LLM Unlearning UnStar: Unlearning with Self-Taught Anti-Sample Reasoning for LLMs

Reference 37

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source=pdf_text observed=2026-08-09T19:14:53.728446Z digest=sha256:a4f466746c0fd4c721997d5a33d6a1db01e0f7ea861f85f06ca78bd02816a23a

Observation 764866da-c3d0-4d9c-8759-3e0493d42aec · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Agents Are All You Need for LLM Unlearning Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 38

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source=pdf_text observed=2026-08-09T19:14:53.731945Z digest=sha256:18a6ffdd5832d8d82776af497259806d2c23ff0f2ee30dfcf680a982e0987ea7

Observation 5ae4c724-bab8-4352-8f65-4e9c73bd9c60 · outbound

This paper cites Beyond Memorization: Violating Privacy Via Inference with Large Language Models.

Agents Are All You Need for LLM Unlearning Beyond Memorization: Violating Privacy Via Inference with Large Language Models

Reference 39

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source=pdf_text observed=2026-08-09T19:14:53.735213Z digest=sha256:adef7176c17ef2ff3374507e8289cc434fc22e25c2d2f48224fbb2a0172f2044

Observation cee042cb-3cdd-4ec0-afd3-8cc37c92f238 · outbound

This paper cites doi: 10.1109/tnnls.2023.3266233.

Agents Are All You Need for LLM Unlearning doi: 10.1109/tnnls.2023.3266233

Reference 40

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source=pdf_text observed=2026-08-09T19:14:53.737916Z digest=sha256:828c4ce15b075e06dd04afef438635e26629df691ea32e1c0e17c8728d934092

Observation ac1bc579-95c5-4336-a130-99c3b9f04a8a · outbound

This paper cites Guardrail Baselines for Unlearning in LLMs.

Agents Are All You Need for LLM Unlearning Guardrail Baselines for Unlearning in LLMs

Reference 41

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source=pdf_text observed=2026-08-09T19:14:53.740648Z digest=sha256:ba27578bd9107bd54f872bf6e95c0baf07268bca1c095d85098b4986dfd7cf9b

Observation 69591d45-a7c3-47cb-92d9-4c63d0fc518b · outbound

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

Agents Are All You Need for LLM Unlearning Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 42

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source=pdf_text observed=2026-08-09T19:14:53.743261Z digest=sha256:d27e08877bad92d08f3aca276c12d3443cc394044173ee985352e20377c6ce5d

Observation cf6c9090-5d42-4bf4-aa3b-edff5c3d10a5 · outbound

This paper cites KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment.

Agents Are All You Need for LLM Unlearning KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment

Reference 44

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source=pdf_text observed=2026-08-09T19:14:53.750909Z digest=sha256:edaa8753cf9f1b80cd9e585028e8abea7c3552f9d147cdff83c97c9efa526b9c

Observation 2041b23a-09ec-48f0-9f83-8356c94a836b · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Agents Are All You Need for LLM Unlearning Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 45

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source=pdf_text observed=2026-08-09T19:14:53.754602Z digest=sha256:511f7d1f88b2a429098170aeef35ee5155ec80c2bd89e98b0e26702ab716f3d6

Observation cd391a8c-b209-4c38-9b87-59e4f199c4dc · outbound

This paper cites doi: 10.1109/tetci.2024.3379240.

Agents Are All You Need for LLM Unlearning doi: 10.1109/tetci.2024.3379240

Reference 46

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metadata mismatch
raw_fallback, observed 2026-08-09T19:14:53.881461Z

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=2026-08-09T19:14:53.758083Z digest=sha256:9379e731040e753c466fa02194d20a62f720d48cfc17a8e828585247037cc1d4

Observation 000271d4-ba5e-485d-a81c-e51c9b5a2a1e · outbound

This paper cites Large Language Model Unlearning.

Agents Are All You Need for LLM Unlearning Large Language Model Unlearning

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-09T19:14:53.761354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:14:53.761354Z digest=sha256:101733faabb58069ee5c25d665112af1f7731fd75bf2def3c7ecc9240ea89b18

Observation 86629995-19d2-47c0-8c7a-3600172e3381 · outbound

This paper cites true way.

Agents Are All You Need for LLM Unlearning true way

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:14:54.603384Z

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=2026-08-09T19:14:53.764662Z digest=sha256:be665b9443b6f5682d0726a7c910e96a1b964d2d8b94a1a616fc7bab3d603c69

Observation 1edc386f-a7c2-4681-bb40-8b8c21f97458 · outbound

This paper cites How was Victor Krum’s Yule Ball experience?.

Agents Are All You Need for LLM Unlearning How was Victor Krum’s Yule Ball experience?

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:14:54.594158Z

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=2026-08-09T19:14:53.769203Z digest=sha256:49c18c96f4696d9702c3d3cff30be04c2f79984c3036ad4e4b011899e31ff0b2

Observation 29466268-d47b-4b9d-92f6-7f6e69c974ab · outbound

This paper cites negative instructions.

Agents Are All You Need for LLM Unlearning negative instructions

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T19:14:54.582490Z

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=2026-08-09T19:14:53.773835Z digest=sha256:2608b46a7487412401f81e1d8a37d7c5d55fb240d89625aa944f8521236ee24a

Observation 42baef5a-05cd-448c-9e8e-652166e089e0 · outbound

This paper cites URL https://www.sciencedirect.com/science/article/pii/S0079742108605368.

Agents Are All You Need for LLM Unlearning URL https://www.sciencedirect.com/science/article/pii/S0079742108605368

Reference 1989

Resolution
unresolved
no resolver link, observed 2026-08-09T19:14:53.695282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:14:53.695282Z digest=sha256:bdb6b78c2288890c4cf7d5cbd9ae0ca60f0847a9d654a3eceadb415b0dc48ed6

Observation b8cb0262-9add-4128-b307-67be9ee8f7f2 · outbound

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

Agents Are All You Need for LLM Unlearning Large Language Model Unlearning via Embedding-Corrupted Prompts

Reference 2004

Resolution
unresolved
no resolver link, observed 2026-08-09T19:14:53.551618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:14:53.551618Z digest=sha256:bdcd9cd1d40736d70416c78c2712153fe62f89665812f1d7f7d0dd2ddac8de95

Observation 9b4c9078-a502-4a8d-9618-6ae5006dbf8c · outbound

This paper cites an unresolved cited work.

Agents Are All You Need for LLM Unlearning Unresolved cited work

Reference 2016

Resolution
unresolved
raw_fallback, observed 2026-08-09T19:14:54.612457Z

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=2026-08-09T19:14:53.746670Z digest=sha256:fe8585a12f48b521e7f4e93de9e44a7aee704647efb22720c554ab9686b90255

Observation 7639f963-bf00-4670-9164-f826a042eb2e · outbound

This paper cites Better Fine-Tuning by Reducing Representational Collapse.

Agents Are All You Need for LLM Unlearning Better Fine-Tuning by Reducing Representational Collapse

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-09T19:14:53.236155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:14:53.236155Z digest=sha256:ac30dd29ee6919acc8d5d2fd52dab62ec26df34d81152a823a2c100998c5bbb3

Observation d3c2483a-fc3a-433b-8fc9-503706d8d51c · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Agents Are All You Need for LLM Unlearning Measuring Massive Multitask Language Understanding

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-09T19:14:53.488634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:14:53.488634Z digest=sha256:d212356c76d4a745320ed5ee857bffafd1d8e09257f5b23374f048e98a50832a

Observation 93902d24-9b48-4c8b-bc08-47adab52fab8 · outbound

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

Agents Are All You Need for LLM Unlearning SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-09T19:14:53.498926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:14:53.498926Z digest=sha256:27bfdfdb1668c57b2fc255f33f8425748ba7aab2c7f206bbc361af7bf4ab33e2

Observation 72569569-2940-487a-8035-cae8fd308039 · outbound

This paper cites The Falcon Series of Open Language Models.

Agents Are All You Need for LLM Unlearning The Falcon Series of Open Language Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-09T19:14:53.239588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:14:53.239588Z digest=sha256:1c23fd1fdffdb9b37ecab2a9efd120ad48b2411b80a7055ba332fec12e5ee554

Observation ca558b9c-711f-413b-be17-fce39c764a68 · outbound

This paper cites InternLM2 Technical Report.

Agents Are All You Need for LLM Unlearning InternLM2 Technical Report

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-09T19:14:53.249130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:14:53.249130Z digest=sha256:ae4d774656cc8b34e147ea36305bedc3f5713532952c7139f5d43d7a35603fd4

Pith citing papers

Observation 181ab00f-b161-4a09-9534-ffd81d1b815d · inbound

SoK: Machine Unlearning for Large Language Models cites this paper.

SoK: Machine Unlearning for Large Language Models Agents Are All You Need for LLM Unlearning

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T04:58:51.628600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:51.628600Z digest=sha256:31d2bd878e0f0e489024e761215034f740e271332ea314637a208ee0ebc687a1

Observation 3cc72244-9c60-41b7-b302-d3a0fe37abb0 · inbound

The Realignment Problem: When Right becomes Wrong in LLMs cites this paper.

The Realignment Problem: When Right becomes Wrong in LLMs Agents Are All You Need for LLM Unlearning

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:30:35.773950Z

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=2026-05-18T01:28:29.056145Z digest=sha256:e6bda360147185b9e47bdbe5aa04102f6babdb9b1e4f41c684a7035217af56a1

Observation 1a34d933-c4a2-4687-9cec-37070a764b17 · inbound

"I Strongly Suspect This Website Is a Scam": Benchmarking PII Leakage and Detection without Defense in Autonomous Web Agents cites this paper.

"I Strongly Suspect This Website Is a Scam": Benchmarking PII Leakage and Detection without Defense in Autonomous Web Agents Agents Are All You Need for LLM Unlearning

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T19:42:36.169252Z

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=2026-06-28T18:53:41.420255Z digest=sha256:b3ff794967bcc5edf096ea65083563cd2feda7fd5d9ab3ae9f30eada95dfdb30