Paper Citation Record · LEDGER

Refine Large Language Model Fine-tuning via Instruction Vector

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2406.12227.

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

pith.paper-citation-record.v1
2406.12227 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:25:47.723135Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T07:18:07.075481Z

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 c406ac68-edda-4679-a3f9-511941a25658 · inbound

Unveiling and Addressing Pseudo Forgetting in Large Language Models cites this paper.

Unveiling and Addressing Pseudo Forgetting in Large Language Models Refine Large Language Model Fine-tuning via Instruction Vector

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-12T18:25:47.723135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13993b6b-bd8a-4151-a0a1-d7471d0d71ed · inbound

ROMAS: A Role-Based Multi-Agent System for Database monitoring and Planning cites this paper.

ROMAS: A Role-Based Multi-Agent System for Database monitoring and Planning Refine Large Language Model Fine-tuning via Instruction Vector

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T13:07:15.901797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59d0fae7-a188-454b-afb6-92fcb5cb2419 · inbound

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead Refine Large Language Model Fine-tuning via Instruction Vector

Reference 150

Resolution: unresolved; no resolver link, observed 2026-08-06T21:36:33.682212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60ce44fb-4f21-4da9-af7b-9996a6d58220 · inbound

FOREVER: Forgetting Curve-Inspired Memory Replay for Language Model Continual Learning cites this paper.

FOREVER: Forgetting Curve-Inspired Memory Replay for Language Model Continual Learning Refine Large Language Model Fine-tuning via Instruction Vector

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T16:31:05.710268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation da2d9c53-5658-4390-88be-2d14a9174b67 · inbound

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models cites this paper.

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models Refine Large Language Model Fine-tuning via Instruction Vector

Reference 132

Resolution: verified exact; arxiv_id, observed 2026-05-16T12:40:54.767005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8159a091-c9d0-4065-bd49-e84477ba3ee4 · inbound

Fine-Tuning Without Forgetting via Loss-Adaptive Learning Rates cites this paper.

Fine-Tuning Without Forgetting via Loss-Adaptive Learning Rates Refine Large Language Model Fine-tuning via Instruction Vector

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:18:07.077307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.