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Paper Citation Record · LEDGER

Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.18210.

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

pith.paper-citation-record.v1
2410.18210 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:57:29.830816Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:30:07.411174Z

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 be5c3d24-348e-4727-b2a0-ed4b80730346 · 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 Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks

Reference 120

Resolution
verified exact
arxiv_id, observed 2026-05-23T20:58:26.275281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T20:58:16.237327Z digest=sha256:26ee6113df34e19169329bd7df3dd0a8db13a5a8be7a593864af1ddf785a4821

Observation ef3b0565-4d01-47e9-94ed-130ff597e838 · inbound

MPO: Multilingual Safety Alignment via Reward Gap Optimization cites this paper.

MPO: Multilingual Safety Alignment via Reward Gap Optimization Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T14:57:29.830816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:57:29.830816Z digest=sha256:d610780932d7f5c40f82a8390654e112d504f2a249b0fbb4a819a784002edac9

Observation 8c39e4ec-1577-4bc0-ab76-8075d5d7b9a6 · inbound

The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-Training cites this paper.

The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-Training Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-11T00:45:50.591356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T18:18:56.476698Z digest=sha256:5a674d4e291ad55d4346367c7569d0ee0071aa95ee7da5de87d39c91380fc211

Observation 6a2cf54b-31c1-4532-8e02-f2e6bc7b630d · inbound

Concept Removal for Frontier Image Generative Models cites this paper.

Concept Removal for Frontier Image Generative Models Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks

Reference 113

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T19:30:07.412568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-25T21:18:32.620951Z digest=sha256:312df4cdd308a690a283a29044aa1fd6532030e6f99a302dee0b767cdf9639e3