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Paper Citation Record · LEDGER

GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2503.09117.

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

pith.paper-citation-record.v1
2503.09117 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 2026-08-19T06:32:44.657259+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:16:50.577231Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T19:46:08.391201Z

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 d4c63adc-4c2e-4e9c-88df-eb9e8f176f58 · inbound

A mean teacher algorithm for unlearning of language models cites this paper.

A mean teacher algorithm for unlearning of language models GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-16T12:16:50.577231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:16:50.577231Z digest=sha256:95863bfc71e38f4db6fa70808eab407f9a692fae852fd980fa0ae487e4485259

Observation 63c26bd7-b753-472c-9d5e-127cab59d723 · inbound

Null Space Constrained Contrastive Visual Forgetting for MLLM Unlearning cites this paper.

Null Space Constrained Contrastive Visual Forgetting for MLLM Unlearning GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:46:08.399419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-08T11:06:45.175766Z digest=sha256:f17adbae7ff29ce834aeaf2d41d6a574750949eda74951acba5323045f27681a

Observation 1d322fae-e92d-4e3f-9636-6525a94cb6c5 · inbound

HermesHFL: Incentive-Compatible Hierarchical Federated Unlearning for Dynamic LLM Fine-Tuning cites this paper.

HermesHFL: Incentive-Compatible Hierarchical Federated Unlearning for Dynamic LLM Fine-Tuning GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs

Reference 11

Resolution
unresolved
no resolver link, observed 2026-07-14T04:58:48.985125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T04:58:48.985125Z digest=sha256:5d227c31c79e1a7c2fa6a93ceb6bd9cf90ba4df7c83230ed0e06d87c8fc2cb08

Observation d92fec51-14c6-43fa-885e-0c2ade868004 · inbound

HermesHFL: Incentive-Compatible Hierarchical Federated Unlearning for Dynamic LLM Fine-Tuning cites this paper.

HermesHFL: Incentive-Compatible Hierarchical Federated Unlearning for Dynamic LLM Fine-Tuning GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-02T06:56:09.015924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T06:56:09.015924Z digest=sha256:378e46e609cd2758b00a99d6369d06b4aea72cbbfd8eb6a22bc16edca203194b

Observation 239f1267-b5d6-498e-ba70-d25c90f28c06 · inbound

HermesHFL: Incentive-Compatible Hierarchical Federated Unlearning for Dynamic LLM Fine-Tuning cites this paper.

HermesHFL: Incentive-Compatible Hierarchical Federated Unlearning for Dynamic LLM Fine-Tuning GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T04:25:54.070559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T04:25:54.070559Z digest=sha256:21dd82071c5616470ccfa6683bbde30db278a03e796f8a45b67dcb27cf9ba332