Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-02T10:25:19.889401Z
Paper Citation Record · LEDGER
As of 13 August 2026, this Paper Citation Record lists 100 of 122 outbound references and 0 inbound Pith citation observations for arXiv:2607.16227.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-02T10:25:19.889401Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
100 of 122 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation fa46251d-ef93-4909-97f0-a9ae46ffb811 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Maity and Manob Jyoti Saikia
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Observation 99563142-e008-46ba-8b00-0bba84d8af40 · outbound
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Observation 264ac16a-b9c0-40a2-89c2-190168f8b4fd · outbound
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Reference 3
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Observation 9726b673-973b-4067-8483-1e4700456697 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats A systematic review of transformer-based pre-trained language models through self-supervised learn- ing.Information, 14(3):187, 2023
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Observation a53d861e-38a5-4a9b-bf3d-ec66583f76b9 · outbound
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Reference 5
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Observation b1838a58-0193-48a8-9018-848370290388 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Quantifying memorization across neural language models
Reference 6
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Observation 201ba6aa-6fc0-4f95-90fe-3753c1027d00 · outbound
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Reference 7
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Observation 6e7bef13-ae7f-44c4-b255-9e1f1577c779 · outbound
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Reference 8
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Observation 4d64e373-59ba-4182-affd-487640e9f4c7 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Jailbroken: How does llm safety training fail? InNeurIPS, 2023
Reference 9
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Observation 3fc5e5ad-2f53-4a2f-a4cd-03b78848db95 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Unresolved cited work
Reference 10
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Observation 6248d9bf-5e1a-4d89-9664-7cc0eaf7cc74 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Unresolved cited work
Reference 11
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Observation 3ce297a2-006e-43d7-a57c-5abe72b29b25 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Lizzo and L
Reference 12
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Observation 7bc9d295-4123-482e-9ad4-7381521f811d · outbound
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Reference 13
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Observation d60f8e9f-370d-4195-a3d9-387f7e5420c1 · outbound
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Reference 14
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Observation d9cb1325-11a4-4da7-9076-30b40e272c23 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Unresolved cited work
Reference 15
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Observation e8ba21e2-4735-4456-be66-79f0bee97cf9 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Unresolved cited work
Reference 16
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Observation a498fe1d-7d4e-4558-ba08-a6476dfeae32 · outbound
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Reference 17
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Observation 3dc9de48-3a19-42d2-b9df-5fce5f7955ab · outbound
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Reference 18
Source-reported events for the cited work
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Observation 6f77eb21-b3fe-436c-8139-20ad45edfd8f · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Towards making systems forget with machine unlearning
Reference 19
Source-reported events for the cited work
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Observation 426e7665-c258-4fe7-99ff-4cbd53808ff6 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Unresolved cited work
Reference 20
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Observation cf7d06db-0d6e-485a-b07d-5cd5d7123559 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 21
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Observation 0c5a9169-df54-4aa1-a754-0e5fab6a8214 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Magesh, F
Reference 22
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Observation cfdac604-f989-43ee-aa32-80f20d9d578c · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Adversar- ial machine learning: A taxonomy and terminology of attacks and mitigations
Reference 23
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Observation 13aa35f1-e700-429f-b442-32b1607dbc7a · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Universal and Transferable Adversarial Attacks on Aligned Language Models
Reference 24
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Observation dfbf620b-bf45-46e6-a81d-0f64d33252ab · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Schwinn, D
Reference 25
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Observation c6fdc2fb-c971-4325-9a7b-17772c5ae30b · outbound
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Reference 26
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Observation ecd9c4aa-cc7d-493f-ab91-c9fc95f46bbc · outbound
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Reference 27
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Unavailable: canonical work link unavailable.
Observation 5db8cabb-2a25-4a57-93bc-650ffbe55c64 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats The EU proposal for a general data protection regulation and the roots of the right to be forgotten.Computer Law and Security Review, 29(3):229–235, 2013
Reference 28
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Observation 82d90913-3c15-4dcd-a027-79802318485c · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Unresolved cited work
Reference 29
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Observation 111f8706-fa3b-45f5-88ea-8d71ed22fe16 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Do large language models understand us?Daedalus, 151(2):183–197, 2022
Reference 30
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Observation 4b7b1dc6-829e-4338-a4dd-1082e471fe19 · outbound
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Reference 31
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Observation 751579c0-37f7-47cb-9971-80ee7772ebb0 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Moffatt v
Reference 32
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Observation 7926a3e7-342c-4cd9-b8f7-a7b3e6ff8a89 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Bert: Pre-training of deep bidirectional transformers for language understanding
Reference 33
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Observation bd2498da-d34b-4aa3-9a3c-223c17f4b185 · outbound
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Reference 34
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Observation aada7cfc-2310-4689-978d-c76866032130 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Improving language understanding by generative pre-training, 2018
Reference 35
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Observation 4d2d9695-e579-4cfb-b8a3-b903bd7025c9 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Language models are few-shot learners
Reference 36
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Observation b27776a1-0f93-489b-b9f5-46ab07706f31 · outbound
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Reference 37
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Observation 6db1812b-8cf2-4358-a160-f0f24f0e5c36 · outbound
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Reference 38
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Observation bf27a497-6633-4c5c-86aa-d24e2bf19f91 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Fields, K
Reference 39
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Observation cea214d8-dd63-4b8a-aa74-60c9886b4e27 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Peykani, F
Reference 40
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Observation 6de2f49b-14a6-4a01-8238-4693a832c569 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Acharya, B
Reference 41
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Observation fb00a1f1-6fb9-4dcf-985d-9621cd2cb391 · outbound
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Reference 42
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Observation a9869d85-edfb-4570-8df5-aa4b5557d938 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Locating and editing factual associations in gpt
Reference 43
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Observation 93b9e5ab-fdc2-4432-b812-2319a81e1cbd · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Trust and R
Reference 44
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Observation e1e24d3d-ead1-4f6b-9b82-80c448286845 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Machine unlearning: Solu- tions and challenges.IEEE Transactions on Emerging Topics in Computational Intelligence, 8(3):2150–2168, 2024
Reference 45
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Observation d85927f2-430c-42e5-8c1e-ae46f5a92d64 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Arcane: An efficient architecture for exact machine unlearning
Reference 46
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Observation 04a63d7b-9eec-408d-a296-c2d21e8972dd · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Roy, and Gintare Karolina Dziugaite
Reference 47
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Observation 5366dc64-99ad-49ab-9a8f-86131dbb03eb · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Unlearning vs
Reference 48
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Observation bb68027a-d157-4eed-9564-1fcfa3f8b1a4 · outbound
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Reference 49
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Observation 843d8674-213b-49be-af00-1ec75328dec1 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Certified Data Removal from Machine Learning Models
Reference 50
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Observation 49a5c638-b19c-4926-83a9-ef910dad7bc9 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Eternal sunshine of the spotless net: Selective forgetting in deep networks.IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Reference 51
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Observation fa2fba3f-dd0c-4094-adb4-2b731f103721 · outbound
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Reference 52
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Observation aa8f8cb2-fd3a-4211-87bd-b0e81d1b2b3e · outbound
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Reference 53
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Observation 6f836d51-2542-462c-958b-3e7e2c0026f6 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Unresolved cited work
Reference 54
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Observation 70008ea7-f51e-4fd7-8cd1-41e2877f7e27 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Towards fair large language model-based recommender systems without costly retraining.arXiv preprint arXiv:2601.17492, 2026
Reference 55
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Observation 5d4ab7a5-449f-4520-8964-e80ce91fdaf0 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats LLM Unlearning using Gradient Ratio-Based Influence Estimation and Noise Injection
Reference 56
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Observation c07710b4-0dcd-4441-b486-005afbd2e045 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Forget the token and pixel: Rethinking gradient ascent for concept unlearning in multimodal generative models
Reference 57
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Observation 563802c9-df03-4c4d-b061-83e10453981d · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Is gradient ascent really necessary? memorize to forget for machine unlearning
Reference 58
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Observation 4a19558f-2564-4793-b5e7-2d3393c31f4f · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Unified gradient-based machine unlearning with remain geometry enhancement
Reference 59
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Observation bf57099b-aaa5-4b11-b3fe-d05271a07453 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Mass-Editing Memory in a Transformer
Reference 60
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Observation aba463ea-85de-4889-80c2-77b9307c5b78 · outbound
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Reference 61
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Observation 91950104-b32a-4a28-b9b8-d653bfe6e33f · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Fine-grained pluggable gradient ascent for knowledge unlearning in language models
Reference 62
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Observation 35b99fae-bd69-4be6-aa11-ba0c49843be2 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Forget for get: A lightweight two-phase gradient method for knowledge editing in large language models
Reference 63
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Observation eeeaa61a-d127-42b3-a7f3-b54186256b51 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Fg- oriu: Towards better forgetting via feature-gradient orthogonality for incremental unlearning
Reference 64
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Observation 3704d76a-2997-449e-a948-0b17d83f6196 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation
Reference 65
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Observation 475cc74c-cada-4b9e-94c7-e4fc20cda888 · outbound
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Reference 66
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Observation 5a4e3884-1f33-4a8b-8d32-0899a363f21e · outbound
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Reference 67
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Observation 9a453114-d879-4c1c-ac0a-bca715c8de70 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Negative preference optimiza- tion: From catastrophic collapse to effective unlearning
Reference 68
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Observation 9a1acb01-c4e2-41f2-9327-e4c2612b94c2 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning
Reference 69
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Observation bda05b58-244c-4538-9744-957671d786a4 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Stable for- getting: Bounded parameter-efficient unlearning in foundation models, 2026
Reference 70
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Observation 56db4fd6-693c-4c94-8ba2-e40d28f4dcee · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Levi, and Volkan Cevher
Reference 71
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Observation 89dac873-f3d3-4aaa-9f4e-bea013ab3306 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Forgetting-MarI: LLM unlearning via marginal information regularization, 2026
Reference 72
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Observation 730e09b7-b3d6-477a-b39c-36454dc0b320 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Label smoothing improves gradient ascent in LLM unlearning, 2025
Reference 73
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Observation b74dff57-557c-46d1-81a1-5a50916a063a · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats GRAIL: Gradient-based adaptive unlearning for privacy and copyright in LLMs, 2025
Reference 74
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Observation 2d8fe6cd-eb2f-43d5-9a05-5488eac40143 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats CATNIP: LLM unlearning via calibrated and tokenized nega- tive preference alignment, 2026
Reference 75
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Observation eb2d15ad-8499-4af6-b361-ab14ef0dc815 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Unresolved cited work
Reference 76
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Observation 176ee119-25c1-46d0-954b-c85682540813 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Transformer feed- forward layers are key-value memories
Reference 77
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Observation 5a63f034-1401-47c5-95d7-c04f884da692 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Machine Unlearning in Contrastive Learning
Reference 78
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Observation 99a8e40f-f5ab-470b-b8a5-cb11e6b59679 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Gauss-newton unlearning for the llm era.arXiv preprint arXiv:2602.10568, 2026
Reference 79
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Observation d51513d1-7b8a-4c27-98ba-2b5d92724f12 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Lacuna inc
Reference 80
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Observation 31e076e9-a0a3-4940-a1a6-90849d33cf6f · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Training data influence analysis and esti- mation: A survey.Machine Learning, 2024
Reference 81
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Observation 5835f582-8e0b-48b6-b8c5-e4afede69bdd · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats Adapting and evaluating influence-estimation methods for gradient-boosted decision trees.Journal of Machine Learning Research, 24:1–48, 2023
Reference 82
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Observation b8434a79-0da1-4053-92f8-3f669f3100e2 · outbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats IMU: Influence-guided Machine Unlearning
Reference 83
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