Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Robustifying Safety-Aligned Large Language Models through Clean Data Curation
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2405.19358.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:02:34.676929Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T05:39:40.646531Z
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 f0b51629-049c-469b-8238-798f25eb3fa2 · 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 Robustifying Safety-Aligned Large Language Models through Clean Data Curation
Reference 101
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T20:58:25.882305Z
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 0220af5e-d502-47e3-8036-525afa5ab5d0 · inbound
SafeTuneBed: A Toolkit for Benchmarking LLM Safety Alignment in Fine-Tuning cites this paper.
SafeTuneBed: A Toolkit for Benchmarking LLM Safety Alignment in Fine-Tuning Robustifying Safety-Aligned Large Language Models through Clean Data Curation
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:02:34.676929Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4af70bc5-9a73-4257-b581-701f3804edc8 · inbound
LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning cites this paper.
LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning Robustifying Safety-Aligned Large Language Models through Clean Data Curation
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:59:56.430016Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 831d6b8d-5863-4549-91ae-16d888141391 · inbound
The Man Behind the Sound: Demystifying Audio Private Attribute Profiling via Multimodal Large Language Model Agents cites this paper.
The Man Behind the Sound: Demystifying Audio Private Attribute Profiling via Multimodal Large Language Model Agents Robustifying Safety-Aligned Large Language Models through Clean Data Curation
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:45:45.113679Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 28e14957-bee0-429e-8e76-69e286284121 · inbound
The Safety Gap Toolkit: Evaluating Hidden Dangers of Open-Source Models cites this paper.
The Safety Gap Toolkit: Evaluating Hidden Dangers of Open-Source Models Robustifying Safety-Aligned Large Language Models through Clean Data Curation
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:08:24.224530Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d2e0d114-69e5-4e94-89e2-62545587e11c · inbound
SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses cites this paper.
SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses Robustifying Safety-Aligned Large Language Models through Clean Data Curation
Reference 119
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T09:25:48.263901Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cb5d68f3-c45c-4d73-9413-449c7f55a1bc · inbound
One Step to the Side: Why Defenses Against Malicious Finetuning Fail Under Adaptive Adversaries cites this paper.
One Step to the Side: Why Defenses Against Malicious Finetuning Fail Under Adaptive Adversaries Robustifying Safety-Aligned Large Language Models through Clean Data Curation
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T21:05:04.077615Z
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 452714d2-905f-4bb4-be5c-5b59976d985b · inbound
Aligned but Fragile: Enhancing LLM Safety Robustness via Zeroth-Order Optimization cites this paper.
Aligned but Fragile: Enhancing LLM Safety Robustness via Zeroth-Order Optimization Robustifying Safety-Aligned Large Language Models through Clean Data Curation
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T07:43:13.526324Z
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 1424f6a0-ea11-42df-8125-197cc394bd12 · inbound
Open Weight AI Models Require Proportional Evaluation Approaches cites this paper.
Open Weight AI Models Require Proportional Evaluation Approaches Robustifying Safety-Aligned Large Language Models through Clean Data Curation
Reference 5
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T05:39:40.648490Z
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.