Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2409.18025.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
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 2026-08-07T13:01:32.710152Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T17:58:47.261403Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 519bc41e-0dcb-4c33-8e15-b3338189d42c · inbound
Existing Large Language Model Unlearning Evaluations Are Inconclusive An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 6
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc4782b7-50e4-4a7d-848e-1ebc2bfd9f7d · inbound
UCD: Unlearning in LLMs via Contrastive Decoding An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 20
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 227d9c44-a5c2-40ad-9239-335234cbb5fc · inbound
Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4d69c909-1526-4c78-adb2-25676b41ec5e · inbound
BLUR: A Benchmark for LLM Unlearning Robust to Forget-Retain Overlap An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 16
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 97392904-e4f6-4862-91f5-2e0fae35a55f · inbound
Step-by-Step Reasoning Attack: Revealing 'Erased' Knowledge in Large Language Models An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0e6a0557-b99b-4b6c-8d9f-c7d264df0dfe · inbound
What Should LLMs Forget? Quantifying Personal Data in LLMs for Right-to-Be-Forgotten Requests An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 36
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fae628b5-9d1c-4bf5-9192-f6a92e89689b · inbound
Reliable Unlearning Harmful Information in LLMs with Metamorphosis Representation Projection An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 26
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9dd3bf4c-02b5-4566-b202-6096553fb338 · inbound
Module-Aware Parameter-Efficient Machine Unlearning on Transformers An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 35
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3dad871f-6b8e-4101-ad54-8d38fdbb88fb · inbound
OFMU: Optimization-Driven Framework for Machine Unlearning An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 23
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 c161c9ee-07da-4a2f-94fc-7db821b7adb1 · inbound
Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 31
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 d560bdf5-77c4-4315-ba8b-052c1424b66a · inbound
You Don't Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 2023
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0917c547-76f8-40da-a242-9fd8a672c199 · inbound
Is your algorithm unlearning or untraining? An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 20
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 54ca28d6-77cb-4f9f-a5f6-b97319187bf0 · inbound
Visual-Noise Guided In-Context Distillation for Multimodal Large Language Model Unlearning An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 16
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 6e472219-aba8-4b68-9a85-3dd88e448cf8 · inbound
RepSelect: Robust LLM Unlearning via Representation Selectivity An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 43
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 550c0e6a-bed8-4bb0-b08a-cdbe9744bf05 · inbound
PPE-Bench: A Benchmark for Evaluating MLLM Unlearning under Private-Public Entanglement An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf7d06db-0d6e-485a-b07d-5cd5d7123559 · inbound
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 21
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4d08acd8-1eae-44ce-bed4-16a589addb6e · inbound
Understanding Machine Unlearning Through the Lens of Mode Connectivity An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 48
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation becb4259-c9ee-4a51-b67b-aed74e0e4279 · inbound
Suppression Sticks, Locality Is Fragile: A Closed-Loop Target-and-Control Audit of Task-Vector Negation in VLA Policies An Adversarial Perspective on Machine Unlearning for AI Safety
Reference 41
Source-reported events for the cited work
Unavailable: canonical work link unavailable.