Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Protecting Privacy Through Approximating Optimal Parameters for Sequence Unlearning in Language Models
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.14091.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T17:56:10.318406Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T10:46:17.106028Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 9c0885d9-27d2-46a7-88f0-6dbac6152efc · inbound
Reliable Unlearning Harmful Information in LLMs with Metamorphosis Representation Projection cites this paper.
Reliable Unlearning Harmful Information in LLMs with Metamorphosis Representation Projection Protecting Privacy Through Approximating Optimal Parameters for Sequence Unlearning in Language Models
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:56:10.318406Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 65264ae3-597f-463c-b45f-cd3669042ec7 · inbound
Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning cites this paper.
Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning Protecting Privacy Through Approximating Optimal Parameters for Sequence Unlearning in Language Models
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T10:46:17.108617Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.