Paper Citation Record · LEDGER

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

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 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 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:24:12.757587Z

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 2026-08-22T06:32:14.747728+00:00.

Observation e405a8d6-9bc0-4576-b2fe-355e8cf6dc6b · inbound

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment cites this paper.

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks

Reference 249

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:12.757587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

Observation 489fd2b8-42f6-4b34-9894-db8109956679 · inbound

LLaVA-NeuMT: Selective Layer-Neuron Modulation for Efficient Multilingual Multimodal Translation cites this paper.

LLaVA-NeuMT: Selective Layer-Neuron Modulation for Efficient Multilingual Multimodal Translation Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T18:10:55.897561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-22T06:32:14.747728+00:00.

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 2026-08-22T06:32:14.747728+00:00.