Paper Citation Record · LEDGER

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2502.05209.

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

pith.paper-citation-record.v1
2502.05209 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:37:06.683217Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T10:46:17.055047Z

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 9ac562e3-c5b1-46c0-8e04-7102890168a9 · inbound

Prompt Attacks Reveal Superficial Knowledge Removal in Unlearning Methods cites this paper.

Prompt Attacks Reveal Superficial Knowledge Removal in Unlearning Methods Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T04:37:06.683217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b691c14-d0ac-4408-84b3-1a983d3c9287 · inbound

Anchoring Refusal Direction: Mitigating Safety Risks in Tuning via Projection Constraint cites this paper.

Anchoring Refusal Direction: Mitigating Safety Risks in Tuning via Projection Constraint Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T23:10:21.212266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0abc5024-ef5d-4655-95da-9c9b68ade291 · inbound

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning cites this paper.

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-18T10:46:17.058220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9195ab00-e824-41a4-9ef9-dd9eb8448c61 · inbound

RippleBench: Capturing Ripple Effects Using Existing Knowledge Repositories cites this paper.

RippleBench: Capturing Ripple Effects Using Existing Knowledge Repositories Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T18:41:33.209039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ba3b8fb-a6c3-43a7-8dbe-1d7aa8abb55a · inbound

Video Deepfake Abuse: How Company Choices Predictably Shape Misuse Patterns cites this paper.

Video Deepfake Abuse: How Company Choices Predictably Shape Misuse Patterns Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T19:59:01.358929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 735466bb-16e9-47f0-ad25-d74394d5c890 · inbound

Operationalising the Superficial Alignment Hypothesis via Task Complexity cites this paper.

Operationalising the Superficial Alignment Hypothesis via Task Complexity Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-02T22:49:13.999922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f63ce60-b49b-432b-94be-3091cd96bea2 · inbound

An Independent Safety Evaluation of Kimi K2.5 cites this paper.

An Independent Safety Evaluation of Kimi K2.5 Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities

Reference 91

Resolution: verified exact; arxiv_id, observed 2026-05-13T19:43:11.577719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ec539424-962b-4ec3-b385-e3a4912b5b1d · inbound

Is your algorithm unlearning or untraining? cites this paper.

Is your algorithm unlearning or untraining? Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:30:59.104808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.