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Paper Citation Record · LEDGER

Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2210.10683.

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

pith.paper-citation-record.v1
2210.10683 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:23:03.930809Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T04:09:34.710341Z

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 ddaa2197-671f-440c-b234-ec47304426f6 · inbound

A StrongREJECT for Empty Jailbreaks cites this paper.

A StrongREJECT for Empty Jailbreaks Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-16T21:28:02.786416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-16T21:28:02.745230Z digest=sha256:3c1c52cc21b8ed91083c7d2aac3c74d88ab50a8a966881300039ccc4bfd44e34

Observation 6739bf55-838f-469f-aaa1-d46636b2ef52 · inbound

Anyone Can Jailbreak: Prompt-Based Attacks on LLMs and T2Is cites this paper.

Anyone Can Jailbreak: Prompt-Based Attacks on LLMs and T2Is Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T12:23:03.930809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:23:03.930809Z digest=sha256:92c59866eb464e78266d0acb501512fe83afa86638444e11a3053ae875f8f622

Observation f424507d-f92c-42ad-8c06-c8aec74d8042 · inbound

The First Differentiable Transfer-Based Algorithm for Discrete MicroLED Repair cites this paper.

The First Differentiable Transfer-Based Algorithm for Discrete MicroLED Repair Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-05T22:21:02.760268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:21:02.760268Z digest=sha256:ba3561e359d102e9467f8ca700ee0cbc60ece9e90169cacb87929c99a554520e

Observation bcec3a58-277c-43ba-9c5e-8c99076fc256 · inbound

Harmful Prompt Laundering: Jailbreaking LLMs with Abductive Styles and Symbolic Encoding cites this paper.

Harmful Prompt Laundering: Jailbreaking LLMs with Abductive Styles and Symbolic Encoding Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-04T17:27:25.849173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:27:25.849173Z digest=sha256:63b24556c5223174b838d450f0165e1c77f15d6627d250d4d1f9bc6d9fe5f8e4

Observation 472464fd-c3a2-4519-919b-01ee2029bf4f · inbound

SafeSci: Safety Evaluation of Large Language Models in Science Domains and Beyond cites this paper.

SafeSci: Safety Evaluation of Large Language Models in Science Domains and Beyond Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-15T18:01:25.528515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-15T18:00:10.534346Z digest=sha256:491b5a49904daa5fa9dde918492e73f6ac2248998f509da12cf4eb7002be0f03

Observation 67369f55-d200-465b-89a9-5e1a35182b08 · inbound

FinRED: An Expert-Guided Benchmark Generation and Evaluation Framework for Financial LLM Red-Teaming cites this paper.

FinRED: An Expert-Guided Benchmark Generation and Evaluation Framework for Financial LLM Red-Teaming Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-07-04T04:09:34.712003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-26T17:11:40.088809Z digest=sha256:a6f3fdc4ece5db9bce87a8a54716392b99cf81a4b1690a8b98112c1d3712e5a5

Observation e9066142-3e38-423f-a58b-e7b4417941e4 · inbound

An Empirical Evaluation of Prompt Injection Vulnerabilities in Large Language Models Across Multilingual and Obfuscated Attack Scenarios cites this paper.

An Empirical Evaluation of Prompt Injection Vulnerabilities in Large Language Models Across Multilingual and Obfuscated Attack Scenarios Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:54:20.376507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T06:51:43.219551Z digest=sha256:455c5e2e6ebb0491a29735a8457c0bf0d596eb8877d9641c85e768b19e727897