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Paper Citation Record · LEDGER

Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal Transport

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.12329.

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

pith.paper-citation-record.v1
2406.12329 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:03:33.449038Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e3708281-a51d-418a-ae13-18323c286d61 · inbound

Not Every Token Needs Forgetting: Selective Unlearning to Limit Change in Utility in Large Language Model Unlearning cites this paper.

Not Every Token Needs Forgetting: Selective Unlearning to Limit Change in Utility in Large Language Model Unlearning Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal Transport

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:33.449038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:33.449038Z digest=sha256:5bef11e5a99fb828468eab038fb073af732e7e3e0cdbb6b37aec812bdaaf70fa

Observation 1e3c9a78-8260-4f2e-887c-2967a7bee3af · inbound

iShumei-Chinchunmei at SemEval-2025 Task 4: A balanced forgetting and retention multi-task framework using effective unlearning loss cites this paper.

iShumei-Chinchunmei at SemEval-2025 Task 4: A balanced forgetting and retention multi-task framework using effective unlearning loss Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal Transport

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T15:22:15.942541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:22:15.942541Z digest=sha256:526038eedb57d318f12e72e6a2d57f53d59bfc3ed778d60e17c58c8dec9426b2

Observation 80358d86-857f-4019-8934-16038c48e4e8 · inbound

A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction cites this paper.

A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal Transport

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T13:54:39.523397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:54:39.523397Z digest=sha256:fcce6524a9b33f5a13cf3e8b5ad4a18672d5ecf19f1fc4f5213de77a10d6f523

Observation 070199a1-96bc-4c3b-85b2-b4fb1c1610e3 · inbound

OFMU: Optimization-Driven Framework for Machine Unlearning cites this paper.

OFMU: Optimization-Driven Framework for Machine Unlearning Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal Transport

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-18T13:06:23.500105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T13:05:50.233483Z digest=sha256:509751849721c85cf81931c33430809badafd1463a877f65086b58512d4126fb

Observation d303384a-c455-4ee3-b3db-ab960d4fe663 · inbound

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data cites this paper.

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal Transport

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:57:21.762614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-13T05:56:38.042978Z digest=sha256:5428ae7c70bc69afff3ca8a208565d67696a76ddfd0d04e52392d6406681f2da