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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=sha256:587454b72625db04ef9d7a79580dd004f27c109cd9b065dd786f5dac79f4ce6e

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:f3fe8e82db9a3787b1d9988de64abe3e651698e17f70ce67f8934d7376869eee

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=sha256:39e1f4d11c310bea26b2c37f8cf5f53925de65b2602ef90e59c71b86476b55a5

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=sha256:00d0debe6bb70cefd9465dddf10e520efed393e0a03bd7baa2ab7cae36335a10

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=sha256:226a9b0022dcc27871a53028177d2d8a3ddffad113dfbaa169f9947720525bd5

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=sha256:389c14bb11e9154919cf93744008ea832dcf4cb5a2d256bb917e063c5047eea5

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=sha256:01f9fd1bddc9d6b4d5aee159d866ee3eed81fc15fd6a895f135ec3372f43fba3

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:ccd07197a857d0a9f2e18d5f635206860acca18f2bb36adddb89a4da8a2ca516

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=sha256:75d1712d89f86527ffbff5d4c3c45eccb465c5b815ef84ab614ef9638e5a2a7c

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:a286d85cbdf3adeb636cf3ad3115309ff35531269766114432330f82da078a57

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=sha256:1b4ef06862412d44e084b8d4e2481f0df3b953a1de0901c2b8e01aeb3a9e1eeb

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=sha256:93f9e21d654aaca7106d60fd3c01693f2ed2a0b4178d11fa6150604fb641a68a

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=sha256:4a71d04189a6d9fcf5d3c0eb5dfd80f06b541460a0559f2dc3a8a8b06fb17c50

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=sha256:1aca755c702f2f47b4eea6bf54ac9e0c14d506aed29133f96ff1f91632595ef9

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=sha256:2593374bd3f974a47616f51d5d1b887389992223a46ad6dc79a018cff7e4235a

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=sha256:0805a3b74ba3d73e3005c6885db848a21aac1f9a2c5ae2aa1cb8650bd56d1659

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:f1409f9615c790d4783cd509967d0a817b077b71ef49f6f8e37fb47b3d2e430c

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=sha256:029543b79501342c08e0c7bf060f53be30ac3b375307d889f5f6dd2b75e0abb8

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=sha256:8109e9cc1420c0d6c3c35b4700caade7958c46a662f23d1a0cf0a1639b14976c

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=sha256:5b7edc37c0627ecc76eb1c976b8b84e4c3ffbcf40f8c6274ba835471e28d3c64

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=sha256:125219bfc7adfb11d01bdec8277cde7c3f70ed975855fddba956bf7aa2c7fc59

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:a693b20bfe2f213d7037c238c2e6973c677f1facefed0b52921639e4cdf63c0d

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:ce00bea5588fc2c85f6f89f6651c4e198514814d732f1fd30b5d89b9d3e3426c

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:e59f498dab4b72e1b37f615e32c7375d83f4db529dbb04711f3577573d0d0f2e

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=sha256:097526c42c82e008e1e9bd80cd74e6df36bf6215f7bb2d7918397cc7aff5ff49

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=sha256:9dd00b581015d48c788a3309be6665ea45444413c182f080d0baaea59510494f

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:e620b76f205d10cc463b15b0d5f9b5dada3d8cc106fe58d71e291fd4c0cb4681

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=sha256:68f7c2fc4d50d3fe51e70750b053e0b2cf0dd0be4693c0eca79c2e6fcddc177b

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:e059e00e34a38986095c97b730f4b4dc9c4866eeb31ab78d6df17a8bcdb8c555

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:b55afef6532c3760c744a6c575fc17ed2c3d60af1eae15ccae49d5204cbdb4ff

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=sha256:59b3546ef12882de898aa1ef72136c7275417554715fb464743b0fb5771f88cd

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=sha256:1f4d7c5db10940cd898b6fed7555d79b3aaed11e30483ea971cf3ab96dccc17c

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=sha256:00b58793aabff08a91aeb859e700607d97e5bfee72b018820ba8018d86a970dd

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=sha256:1b6de0110778b2960f976d6f98415329636dd088db8e29113cb03c2cd1977e40

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:e2c2ecb33274ebb4ff6ee1bda3a3ebb1b31beb4270608e7de73dacd576a1afe0

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=sha256:2066ed424166414e9e31fdd180fe91a16148e668fd4c4fa9bb1ac07df9fda260

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=sha256:14da6c32a7da5f8e47d3812f1502d592cb797e40679df7619120cd8d1483c5ab

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

Resolution
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.

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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

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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:c744275688c5b75186e440e3dda7a07db28758fd4fe7761df8a93472860fb94a

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=sha256:7b8fcef2eb13318393de54cecc204ae0f015dbb420cb0567254ab043c02e8870

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=sha256:75a575b14f7b50e3e20fc33d4e14faad292f38c39bf7ff9130a48a687ccbb314

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:c059a0b22fef8a8959e37cbe9c36411050e1ad4f64b99ecb85d8d86604ce836c

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:c88acecd16ea44e1424bb338b163672be87cb8ffef7dabd4cf0d29a6e4d0dec0

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=sha256:8a9c28ef96b893ce8ac1e2e8d8f9d2ee861de682c5c2da43cd6f17a65b587952

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=sha256:524a07dcf2762d47a6c0c8cd6c6734cade941e414c4f1f23ec06b32f907dd5ab

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:fb324ff24a782e1fb0c4493fb1d1fbba43920c4182e3882558a2eb4573a076e3

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=sha256:50b2930c840a4dc384638b5844279671b3f652f479108dcd8bf3f7de22a31ec3

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=sha256:6f632367a1010d9545c63da589e8d160975201668c24678873ae9ad6d71e0a68

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

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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:d43e82392b8ba7317c1e467a5c49a617d4e09268afc5f93d4851bc50ab72ed7b

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=sha256:7c61cffe5d15014c7db1d3126d18a0af753df549b3bdaaf1a7c92e59631a7aae

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=sha256:073c1147e5cb2d9c028499a879e01fe484c2b939f9b04fa1cfffad59418aafcc

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=sha256:0ad51e27951c61f5aee9dbd92e823955c854bc1b66a7ce60eb0b61def5e0394a

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=sha256:4b6464ccef0055b76b5fa0f52a049a1003eb2abbefd6057674dd345132b76372