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Paper Citation Record · LEDGER

Gradient Projection For Continual Parameter-Efficient Tuning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.13383.

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

pith.paper-citation-record.v1
2405.13383 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 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:35:03.928425Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T19:16:09.484017Z

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 e7877621-c5aa-4bf6-8d0d-d7f929c06335 · inbound

Continual Gradient Low-Rank Projection Fine-Tuning for LLMs cites this paper.

Continual Gradient Low-Rank Projection Fine-Tuning for LLMs Gradient Projection For Continual Parameter-Efficient Tuning

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T20:35:03.928425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:35:03.928425Z digest=sha256:5c7cf7013f498ff84fe46d0645c3c7c7f63bee1e642130f945e8618970ba6265

Observation 9ee14a4c-0ae1-4b50-a50c-82b3590507fb · inbound

Hidden Failure Modes of Gradient Modification under Adam in Continual Learning, and Adaptive Decoupled Moment Routing as a Repair cites this paper.

Hidden Failure Modes of Gradient Modification under Adam in Continual Learning, and Adaptive Decoupled Moment Routing as a Repair Gradient Projection For Continual Parameter-Efficient Tuning

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:16:09.486016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T12:23:27.911085Z digest=sha256:e6564e9e3612480513067b2ff0bd762ebb999689dbc846e7f05f40eacf3c65f1

Observation dce42a87-0eae-4ea5-b538-45329304fca4 · inbound

Hidden Failure Modes of Gradient Modification under Adam in Continual Learning, and Adaptive Decoupled Moment Routing as a Repair cites this paper.

Hidden Failure Modes of Gradient Modification under Adam in Continual Learning, and Adaptive Decoupled Moment Routing as a Repair Gradient Projection For Continual Parameter-Efficient Tuning

Reference 1989

Resolution
unresolved
no resolver link, observed 2026-08-02T15:45:03.235629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T15:45:03.235629Z digest=sha256:ac50e3ac0e1bb906f562b12c0ef32196671f353354dffcdc6b693a13ce39fd39

Observation 4be6d904-49f4-4c62-9326-44ef9d94d028 · inbound

TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement cites this paper.

TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement Gradient Projection For Continual Parameter-Efficient Tuning

Reference 20

Resolution
unresolved
no resolver link, observed 2026-07-31T22:47:14.150772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T22:47:14.150772Z digest=sha256:ef36f1662e4cf1fc9688dfbf33a7c4872882b8eb7c5d5a5a1fa375e8dd15f75d

Observation 55a35ffa-db3a-4837-84f8-456a7fe71678 · inbound

TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement cites this paper.

TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement Gradient Projection For Continual Parameter-Efficient Tuning

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-03T01:42:10.771069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T01:42:10.771069Z digest=sha256:e33e40660db00fc9744320d6ddd3d4c3e3d4d331223c00214d5312a8296b0356