Paper Citation Record · LEDGER

Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.18540.

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

pith.paper-citation-record.v1
2402.18540 v2

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 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:58:30.941185Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T02:25:55.507074Z

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 fc30f4cd-f9a0-4d2f-9ac7-58a61d6fcd7a · inbound

Proof-of-Learning with Incentive Security cites this paper.

Proof-of-Learning with Incentive Security Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-24T02:25:55.510376Z

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.

Observation 44891152-4c8f-47ea-b4e1-d598e46f4d77 · inbound

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey cites this paper.

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates

Reference 103

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:58:26.413890Z

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.

Observation 4fed7e0f-c7a7-4eb8-808c-4691a40cde4a · inbound

Vulnerability-Aware Alignment: Mitigating Uneven Forgetting in Harmful Fine-Tuning cites this paper.

Vulnerability-Aware Alignment: Mitigating Uneven Forgetting in Harmful Fine-Tuning Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T10:58:30.941185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70fcb23a-e528-4821-9f89-888045f82745 · inbound

Linearly Decoding Refused Knowledge in Aligned Language Models cites this paper.

Linearly Decoding Refused Knowledge in Aligned Language Models Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T21:27:34.954267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53cbdb86-343d-4044-9d33-c2070408d855 · inbound

Benign Fine-Tuning Breaks Safety Alignment in Audio LLMs cites this paper.

Benign Fine-Tuning Breaks Safety Alignment in Audio LLMs Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T08:02:24.920882Z

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.

Observation 0ba554f1-c066-4cb9-957a-7368f98cdfd3 · inbound

Robotics-Inspired Guardrails for Foundation Models in Socially Sensitive Domains cites this paper.

Robotics-Inspired Guardrails for Foundation Models in Socially Sensitive Domains Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-20T05:48:04.442559Z

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.