Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2503.12874.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T13:51:18.065039Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T12:13:26.768727Z
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 81890854-838d-480d-bcf7-27338ddd465d · inbound
Disentangling Adversarial Prompts: A Semantic-Graph Defense for Robust LLM Security Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language Models
Reference 2
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 be1372dc-a0e6-4e93-b9ae-87b896158bed · inbound
CogniVerse: Revolutionizing Multi-Modal Retrieval-Augmented Generation with Cognitive Reflection and Geometric Reasoning Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language Models
Reference 61
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 3000efe9-740a-4306-92ef-9edd3a9747e6 · inbound
Two Sides of the Same Coin: Co-Evolving Search for Cross-Task Attacks on Vision-Language Models Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language Models
Reference 19
Source-reported events for the cited work
Unavailable: canonical work link unavailable.