Paper Citation Record · LEDGER

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models

As of 13 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2506.11253.

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

pith.paper-citation-record.v1
2506.11253 v2

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:16:59.215569Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-10T15:38:58.361411Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T15:47:23.228937Z

Reference resolution

52 of 52 outbound references displayed

verified exact2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c490bfde-19b5-41cf-a976-970fc9648ca9 · outbound

This paper cites GPT-4 Technical Report.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models GPT-4 Technical Report

Reference 1

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Observation d7ceea3b-f7b0-49e1-9f61-e3d07cae6de8 · outbound

This paper cites Related W ork T ask Unlearned Model/T arget Golatkar et al.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Related W ork T ask Unlearned Model/T arget Golatkar et al

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:16:59.945641Z

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Observation 75931b67-728b-4783-b5de-2d0eb9c841c4 · outbound

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

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation

Reference 8

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Observation 007309cc-74d7-4621-aa4c-a77654ce4fcb · outbound

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

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Simplicity prevails: Rethinking negative preference optimization for llm unlearning.arXiv preprint arXiv:2410.07163,

Reference 9

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Observation 4f245604-fae7-474c-af7d-95d115213e9c · outbound

This paper cites The importance of forgetting.Nature, 571(July):S12–S14,.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models The importance of forgetting.Nature, 571(July):S12–S14,

Reference 11

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Observation 43363dd3-a623-4840-a43a-7dbc0dcc090a · outbound

This paper cites Certified Data Removal from Machine Learning Models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Certified Data Removal from Machine Learning Models

Reference 12

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Observation 4973d31a-74b5-4a98-8a1e-b401339cde04 · outbound

This paper cites Editing Models with Task Arithmetic.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Editing Models with Task Arithmetic

Reference 14

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Observation e9fb23f5-45d8-43b7-9a9c-82581eb16ff4 · outbound

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

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Knowledge Unlearning for Mitigating Privacy Risks in Language Models

Reference 16

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Observation a56f72a9-7798-42c3-bc65-3fbfa7ee0543 · outbound

This paper cites RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models

Reference 17

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Observation f6852d84-a3f9-458d-8d7d-613a824a1f5b · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 18

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Observation 06916836-af25-4b91-8920-aeca350b691d · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models LLaVA-OneVision: Easy Visual Task Transfer

Reference 19

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Observation 535be7b8-3d09-4be7-9965-7f2252555238 · outbound

This paper cites Rethinking Machine Unlearning for Large Language Models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Rethinking Machine Unlearning for Large Language Models

Reference 20

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Observation cdd913a3-95d7-46ad-a4e1-85a1525769a1 · outbound

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

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models TOFU: A Task of Fictitious Unlearning for LLMs

Reference 21

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Observation e58cea4e-b143-449c-8fc0-1ea088d448ca · outbound

This paper cites Fast Model Editing at Scale.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Fast Model Editing at Scale

Reference 22

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Observation 274b3b34-4868-4762-b2eb-77209c76f17e · outbound

This paper cites GPT-4o System Card.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models GPT-4o System Card

Reference 23

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Observation 5465c0b5-06cd-4b7b-9fa8-6546f635fc50 · outbound

This paper cites Direct Unlearning Optimization for Robust and Safe Text-to-Image Models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Direct Unlearning Optimization for Robust and Safe Text-to-Image Models

Reference 24

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Observation 93ee4420-2133-4e9a-a712-ce7dbf5443b4 · outbound

This paper cites Safe-clip: Removing nsfw concepts from vision-and-language models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Safe-clip: Removing nsfw concepts from vision-and-language models

Reference 26

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Observation 64c8302c-e02c-4e6a-a036-87bfa10f9b4a · outbound

This paper cites How Data Inter-connectivity Shapes LLMs Unlearning: A Structural Unlearning Perspective.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models How Data Inter-connectivity Shapes LLMs Unlearning: A Structural Unlearning Perspective

Reference 27

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Observation e7c168d0-8417-41f3-a2dd-cb629ef0ff70 · outbound

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

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Regulation (eu) 2016/679 of the european parliament and of the council.Regulation (eu), 679: 2016,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:16:59.984697Z

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Observation e2d4e09b-22ed-4b89-9cc6-e72f5ad8c016 · outbound

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

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models MUSE: Machine Unlearning Six-Way Evaluation for Language Models

Reference 29

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Observation 90fd0c64-f36f-408c-94d2-a7125409c06a · outbound

This paper cites Position: LLM Unlearning Benchmarks are Weak Measures of Progress.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Position: LLM Unlearning Benchmarks are Weak Measures of Progress

Reference 30

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Observation 09e36e8b-b332-45dc-9c1a-a89d8eeef962 · outbound

This paper cites To Forget or Not? Towards Practical Knowledge Unlearning for Large Language Models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models To Forget or Not? Towards Practical Knowledge Unlearning for Large Language Models

Reference 31

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Observation 0933fb63-482f-41dd-928c-8c92c120dcd0 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models LLaMA: Open and Efficient Foundation Language Models

Reference 32

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Observation 40ed7878-ec87-4a9d-bc7d-07cd5e6faf96 · outbound

This paper cites Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition

Reference 33

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Observation 44f2363b-1af1-4026-adb0-4c781af1eced · outbound

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

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment

Reference 34

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Observation 173da392-4a5a-4887-9423-ddb7b129939b · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 35

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Observation c59366e9-0365-47a5-bfe3-423e19ff0cfc · outbound

This paper cites CLIPErase: Efficient Unlearning of Visual-Textual Associations in CLIP.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models CLIPErase: Efficient Unlearning of Visual-Textual Associations in CLIP

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:16:59.340722Z

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Observation ecf141a7-2300-4847-ba99-d043a8f50227 · outbound

This paper cites Machine Unlearning of Pre-trained Large Language Models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Machine Unlearning of Pre-trained Large Language Models

Reference 37

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Observation bbc83ff9-b702-4e5f-a336-df8a0bb7fe04 · outbound

This paper cites Large Language Model Unlearning.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Large Language Model Unlearning

Reference 38

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Observation 5aceda00-4049-4784-b77b-801c094bf065 · outbound

This paper cites Unlearning bias in language models by partitioning gradients.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Unlearning bias in language models by partitioning gradients

Reference 39

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Observation 28a29f8b-6728-4cff-a65d-e9704c1e0701 · outbound

This paper cites A Closer Look at Machine Unlearning for Large Language Models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models A Closer Look at Machine Unlearning for Large Language Models

Reference 40

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This paper cites MC-MKE: A Fine-Grained Multimodal Knowledge Editing Benchmark Emphasizing Modality Consistency.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models MC-MKE: A Fine-Grained Multimodal Knowledge Editing Benchmark Emphasizing Modality Consistency

Reference 41

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Observation 54a55582-cf63-440d-85cd-08ffc6999436 · outbound

This paper cites What makes unlearning hard and what to do about it.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models What makes unlearning hard and what to do about it

Reference 42

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Observation 27b04d05-3bff-4801-976b-1f315f431fc0 · outbound

This paper cites Fortuitous Forgetting in Connectionist Networks.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Fortuitous Forgetting in Connectionist Networks

Reference 43

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Observation aad7ee1b-2627-41ba-bd0a-203ba498c09f · outbound

This paper cites We systematically categorize unlearning tasks, models, and targets of related papers in Table.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models We systematically categorize unlearning tasks, models, and targets of related papers in Table

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:16:59.958716Z

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Observation 6b8e50f1-8f52-4a1a-bdcf-fd308e4e5bd9 · outbound

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Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Unresolved cited work

Reference 46

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Observation fb7b42a5-4e77-44cf-b599-441873f917b0 · outbound

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Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:16:59.918496Z

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Observation 15047fd9-0568-48ef-8ae6-5af349171c56 · outbound

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Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Unresolved cited work

Reference 48

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:16:59.904316Z

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This paper cites According to the results shown 20 Published in Transactions on Machine Learning Research (May/2026) Table 10: Prompts of CompCars-S and ImgnetDogs dataset.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models According to the results shown 20 Published in Transactions on Machine Learning Research (May/2026) Table 10: Prompts of CompCars-S and ImgnetDogs dataset

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:16:59.877181Z

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Observation c9e1a491-a0a6-4409-96c3-91e05903e3ec · outbound

This paper cites Additionally, relabeling- based methods fail to achieve effective unlearning, similar to their performance on the ImgnetDogs dataset.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Additionally, relabeling- based methods fail to achieve effective unlearning, similar to their performance on the ImgnetDogs dataset

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:16:59.863924Z

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Observation d15c1bde-18a0-4b5b-9fb4-06bf0ca69e87 · outbound

This paper cites Dataset Food101 Flower102 Caltech101 OxfordPet Cifar100 Avg↑ Origin CLIP (Radford et al.,.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Dataset Food101 Flower102 Caltech101 OxfordPet Cifar100 Avg↑ Origin CLIP (Radford et al.,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:16:59.850878Z

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Observation 9f9f822c-f12f-4abc-a476-d36abfa31992 · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 1998

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

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Who's Harry Potter? Approximate Unlearning in LLMs

Reference 2009

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Observation 6569e482-0535-4487-850e-fad30ca062d1 · outbound

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

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models In-Context Unlearning: Language Models as Few Shot Unlearners

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-07T04:16:59.102844Z

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Observation 420a2376-ca45-4692-b973-a13f33a65aa1 · outbound

This paper cites Efficient repair of polluted machine learning systems via causal unlearning.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Efficient repair of polluted machine learning systems via causal unlearning

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:17:00.027962Z

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Observation cbac58b9-5639-45c6-b510-164b33f4e541 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models On the Opportunities and Risks of Foundation Models

Reference 2019

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Observation 039d944a-0e88-4175-a9f4-dd7522ad6c7d · outbound

This paper cites The optimization objective for relabeling is as follows: LRelabel = ∑ (xi,.)∈Df [−log(yrand|xi,θ)],(8) wherey rand is randomly chosen from the label set andyrand̸=y f.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models The optimization objective for relabeling is as follows: LRelabel = ∑ (xi,.)∈Df [−log(yrand|xi,θ)],(8) wherey rand is randomly chosen from the label set andyrand̸=y f

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:16:59.890658Z

Source-reported events for the cited work

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Observation 883e2145-e05b-4681-9fd0-1fdd61d4ba24 · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:17:00.040789Z

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Observation aa180ff8-3e4c-4ad7-ac18-262db154ee96 · outbound

This paper cites Knowledge Sanitization of Large Language Models.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Knowledge Sanitization of Large Language Models

Reference 2022

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Observation 0348db6d-e4a1-42ac-ba8d-243ce460fc4d · outbound

This paper cites Microsoft COCO Captions: Data Collection and Evaluation Server.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 2023

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Observation 0f26619f-a3be-4b77-a9e6-91693dd8827f · outbound

This paper cites VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark.

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T04:16:59.050489Z

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Observation 1de5dcf1-9dc5-4024-b11b-a803ebcb148f · outbound

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

Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models Unlearn What You Want to Forget: Efficient Unlearning for LLMs

Reference 2025

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Pith citing papers

Observation 433a215d-df29-4d63-b34d-6cbbf17cf988 · inbound

Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks cites this paper.

Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models

Reference 113

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T15:47:23.230057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.