Paper Citation Record · LEDGER

A hybrid framework for effective and efficient machine unlearning

As of 23 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2412.14505.

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

pith.paper-citation-record.v1
2412.14505 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:14:04.567403Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

verified exact0
verified fuzzy27
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 590b5267-5063-47e9-9c70-009c031f268c · outbound

This paper cites State of Califor nia Oﬃce of the Attorney General (2024), https://oag.ca.gov/privacy/ccpa.

A hybrid framework for effective and efficient machine unlearning State of Califor nia Oﬃce of the Attorney General (2024), https://oag.ca.gov/privacy/ccpa

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:05.102820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 82ca679e-f57e-47a1-b0a1-360568e3e975 · outbound

This paper cites http://archive.ics.uci.edu/ml (1996).

A hybrid framework for effective and efficient machine unlearning http://archive.ics.uci.edu/ml (1996)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:05.083277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f13d0910-4308-45d0-be58-9592a20698ee · outbound

This paper cites In: 20 21 IEEE Symposium on Security and Privacy (SP).

A hybrid framework for effective and efficient machine unlearning In: 20 21 IEEE Symposium on Security and Privacy (SP)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:05.064105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 703ca40a-c59f-4f4f-a601-e7e96bd26a07 · outbound

This paper cites In: International Conference on Machine Learning.

A hybrid framework for effective and efficient machine unlearning In: International Conference on Machine Learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:05.045175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 70f4dc97-802b-4a75-86d9-0a1b7677dabe · outbound

This paper cites In: 2015 IEEE symposium on security and privacy.

A hybrid framework for effective and efficient machine unlearning In: 2015 IEEE symposium on security and privacy

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:05.028696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8c297ef5-630e-4624-96e7-d19f026bf643 · outbound

This paper cites In : 28th USENIX security symposium (USENIX security 19).

A hybrid framework for effective and efficient machine unlearning In : 28th USENIX security symposium (USENIX security 19)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:05.012089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a64ddc8c-8b7b-4a84-b20f-6d4d1a2f6c14 · outbound

This paper cites In: Proceed- ings of the ACM Web Conference 2022.

A hybrid framework for effective and efficient machine unlearning In: Proceed- ings of the ACM Web Conference 2022

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.993029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 604c3868-8412-4eb9-8086-98de244026af · outbound

This paper cites In: Proceedings of the 2022 ACM SIGSAC conferen ce on computer and communications security.

A hybrid framework for effective and efficient machine unlearning In: Proceedings of the 2022 ACM SIGSAC conferen ce on computer and communications security

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.975249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2bf09013-092d-4588-ba80-a2e9cd11e337 · outbound

This paper cites https://archive.ics.uci.edu/ml/machine-learning-databases/census-income-mld.

A hybrid framework for effective and efficient machine unlearning https://archive.ics.uci.edu/ml/machine-learning-databases/census-income-mld

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.958116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fd2964a9-13cf-483d-b226-fc72c1d2c9d8 · outbound

This paper cites Advances in neural information proces sing systems 32 (2019).

A hybrid framework for effective and efficient machine unlearning Advances in neural information proces sing systems 32 (2019)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.941277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8306dcfc-8baf-477f-a11f-13ff191c818e · outbound

This paper cites In: Proceedings of the IEEE/CV F Conference on Computer Vision and Pattern Recognition.

A hybrid framework for effective and efficient machine unlearning In: Proceedings of the IEEE/CV F Conference on Computer Vision and Pattern Recognition

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.925053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 66045641-4c4a-4a3d-b05c-00bd69683882 · outbound

This paper cites IEE E Transactions on Infor- mation Forensics and Security 17, 265–279 (2021).

A hybrid framework for effective and efficient machine unlearning IEE E Transactions on Infor- mation Forensics and Security 17, 265–279 (2021)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.907947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c4b718be-b211-44a3-b868-59accd0c25af · outbound

This paper cites In: Proceedings of the AAAI Conference on Artiﬁcial Intelligence.

A hybrid framework for effective and efficient machine unlearning In: Proceedings of the AAAI Conference on Artiﬁcial Intelligence

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.888973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f5eebba7-381b-4317-953f-bafe18520c71 · outbound

This paper cites arXiv preprint arXiv:1911.0 3030 (2019).

A hybrid framework for effective and efficient machine unlearning arXiv preprint arXiv:1911.0 3030 (2019)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.872538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4abca710-abca-4660-be38-c9518eb7312d · outbound

This paper cites Advances in Neural Information Pr ocessing Systems 34, 16319–16330 (2021).

A hybrid framework for effective and efficient machine unlearning Advances in Neural Information Pr ocessing Systems 34, 16319–16330 (2021)

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.856128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c684b005-94e1-4cb7-b5bd-b18a5c24e668 · outbound

This paper cites https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results.

A hybrid framework for effective and efficient machine unlearning https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.838878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7cf178d3-5369-4953-a460-34456d222329 · outbound

This paper cites https://www.kaggle.com/competitions/acquire-valued-shoppers-chal.

A hybrid framework for effective and efficient machine unlearning https://www.kaggle.com/competitions/acquire-valued-shoppers-chal

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.820546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 16d56acc-16f0-4d2e-82d7-1a957c31353f · outbound

This paper cites In: International conference on machine learning.

A hybrid framework for effective and efficient machine unlearning In: International conference on machine learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.803919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 09961f0f-9748-4776-8bf1-a89d07cb6588 · outbound

This paper cites In: Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communicatio ns Security.

A hybrid framework for effective and efficient machine unlearning In: Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communicatio ns Security

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.787759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7a93fcbf-7add-4d85-ba48-696a5dd63cbd · outbound

This paper cites an unresolved cited work.

A hybrid framework for effective and efficient machine unlearning Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:14:04.770300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2c01aac3-3f56-4ad7-8703-38d56cf20073 · outbound

This paper cites In: Algorithmic Learning Theor y.

A hybrid framework for effective and efficient machine unlearning In: Algorithmic Learning Theor y

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.754017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 51fab8a9-d1f2-4f8a-ac97-1d52dcb8f417 · outbound

This paper cites In: 2017 IEEE symposium on security and privacy (SP).

A hybrid framework for effective and efficient machine unlearning In: 2017 IEEE symposium on security and privacy (SP)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.736569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8ec285de-dab2-4108-b376-0e0631bf52c9 · outbound

This paper cites In: 31st USENIX Security Symposium (USENIX Security 22).

A hybrid framework for effective and efficient machine unlearning In: 31st USENIX Security Symposium (USENIX Security 22)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.717134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 89680bfe-0200-44e1-90c0-a6990cf5403b · outbound

This paper cites In: 25th USENIX security symposium (USENIX Security 16).

A hybrid framework for effective and efficient machine unlearning In: 25th USENIX security symposium (USENIX Security 16)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.696594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation db5ac4b4-51fc-4bcf-a112-8fd732531dc6 · outbound

This paper cites : Joint coding and scheduling optimization for distributed learning over wir eless edge networks.

A hybrid framework for effective and efficient machine unlearning : Joint coding and scheduling optimization for distributed learning over wir eless edge networks

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.680173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 667265f1-d7be-45c2-af50-078d9fb579e9 · outbound

This paper cites In: 39th IEEE International Conference on Data Engineering, ICDE 2023, A naheim, CA, USA, April 3-7, 2023.

A hybrid framework for effective and efficient machine unlearning In: 39th IEEE International Conference on Data Engineering, ICDE 2023, A naheim, CA, USA, April 3-7, 2023

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.663251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 014b88ce-990e-4e00-a63a-9396e513a485 · outbound

This paper cites IEEE Trans.

A hybrid framework for effective and efficient machine unlearning IEEE Trans

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.646377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation eedd0cf0-e864-4799-83ee-43d8dcc6615c · outbound

This paper cites , Yu, G.: FSP: towards ﬂexible synchronous parallel frameworks for distributed m achine learning.

A hybrid framework for effective and efficient machine unlearning , Yu, G.: FSP: towards ﬂexible synchronous parallel frameworks for distributed m achine learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:04.629167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 704b6e9a-a140-4930-a8a8-b81545c25b05 · outbound

This paper cites Machine Unlearning of Features and Labels.

A hybrid framework for effective and efficient machine unlearning Machine Unlearning of Features and Labels

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T12:14:04.567403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.