Paper Citation Record · LEDGER

Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.00867.

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

pith.paper-citation-record.v1
2403.00867 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:25:30.570537Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T22:32:12.939049Z

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 e93f0364-7149-4003-8217-f80e5f3b63a1 · inbound

Jailbreak Attacks and Defenses Against Large Language Models: A Survey cites this paper.

Jailbreak Attacks and Defenses Against Large Language Models: A Survey Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T02:20:44.669253Z

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.

Observation dfefeffe-7bac-4fdc-8c74-b065e759989e · inbound

JBShield: Defending Large Language Models from Jailbreak Attacks through Activated Concept Analysis and Manipulation cites this paper.

JBShield: Defending Large Language Models from Jailbreak Attacks through Activated Concept Analysis and Manipulation Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T12:25:30.570537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26f571ff-b04f-46a5-942b-925e13134998 · inbound

Exposing the Ghost in the Transformer: Abnormal Detection for Large Language Models via Hidden State Forensics cites this paper.

Exposing the Ghost in the Transformer: Abnormal Detection for Large Language Models via Hidden State Forensics Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:32:12.941277Z

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.

Observation d8d6d865-4a1a-4a70-be4b-8fe5eb1030de · inbound

Advancing Jailbreak Strategies: A Hybrid Approach to Exploiting LLM Vulnerabilities and Bypassing Modern Defenses cites this paper.

Advancing Jailbreak Strategies: A Hybrid Approach to Exploiting LLM Vulnerabilities and Bypassing Modern Defenses Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T22:20:13.802452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88f1a97e-6cac-4a1a-979c-18c93aba7ad0 · inbound

ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments cites this paper.

ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T01:02:54.772296Z

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.