Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1901.06796.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T12:30:20.520881Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T04:07:00.102841Z
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 38bc95ef-34d2-454c-8990-513d99970a39 · inbound
Universal Adversarial Triggers for Attacking and Analyzing NLP cites this paper.
Universal Adversarial Triggers for Attacking and Analyzing NLP Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T12:30:20.520881Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b448cfd4-57bb-417a-9149-d529a62ebed6 · inbound
Evaluating Defensive Distillation For Defending Text Processing Neural Networks Against Adversarial Examples cites this paper.
Evaluating Defensive Distillation For Defending Text Processing Neural Networks Against Adversarial Examples Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T11:56:22.287741Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 132820db-0149-4a09-bae1-61ebfc8c7bcf · inbound
Towards Understanding Neural Machine Translation with Word Importance cites this paper.
Towards Understanding Neural Machine Translation with Word Importance Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T05:59:04.612538Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7a3085c-aac9-40c1-a77b-6f3a3d818f03 · inbound
The Relationship Between Network Similarity and Transferability of Adversarial Attacks cites this paper.
The Relationship Between Network Similarity and Transferability of Adversarial Attacks Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T13:39:29.563385Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0dc3ffe2-6c99-471d-878c-0087a82c812f · inbound
TrustGLM: Evaluating the Robustness of GraphLLMs Against Prompt, Text, and Structure Attacks cites this paper.
TrustGLM: Evaluating the Robustness of GraphLLMs Against Prompt, Text, and Structure Attacks Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey
Reference 40
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T04:07:00.107270Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.