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Paper Citation Record · LEDGER

Adversarial Attacks and Defenses in Large Language Models: Old and New Threats

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2310.19737.

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

pith.paper-citation-record.v1
2310.19737 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:28:00.681961Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T05:05:22.782499Z

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 f29e3ee1-30b0-4ebf-9449-8f9dfee230ec · inbound

Trojan Detection Through Pattern Recognition for Large Language Models cites this paper.

Trojan Detection Through Pattern Recognition for Large Language Models Adversarial Attacks and Defenses in Large Language Models: Old and New Threats

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T18:07:46.881723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:07:46.881723Z digest=sha256:50625efd25ad77ca8d19dba511d5d71b4ddd34d41faa5b53e8d6eb1aafe749f2

Observation 5b879a50-5670-4f39-bab6-18f92f6b5a20 · inbound

Fast Proxies for LLM Robustness Evaluation cites this paper.

Fast Proxies for LLM Robustness Evaluation Adversarial Attacks and Defenses in Large Language Models: Old and New Threats

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T19:32:24.106441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:32:24.106441Z digest=sha256:8ae68a2ebdb6831e4f10a6798c9bc49214c64c1d119fd6b8ac28151a9c9b3538

Observation 8f2fbb1c-4f3e-43f5-a2f7-e5778ab80b88 · inbound

LLM Security: Vulnerabilities, Attacks, Defenses, and Countermeasures cites this paper.

LLM Security: Vulnerabilities, Attacks, Defenses, and Countermeasures Adversarial Attacks and Defenses in Large Language Models: Old and New Threats

Reference 113

Resolution
unresolved
no resolver link, observed 2026-08-16T04:28:00.681961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:28:00.681961Z digest=sha256:fc12242662d879408fa457e331fcd361b010f933451a326041103274e611b3e4

Observation 56e86c98-86db-4e90-9e14-86e48abcbd8e · inbound

Circumventing Safety Alignment in Large Language Models Through Embedding Space Toxicity Attenuation cites this paper.

Circumventing Safety Alignment in Large Language Models Through Embedding Space Toxicity Attenuation Adversarial Attacks and Defenses in Large Language Models: Old and New Threats

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T19:26:13.716377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:26:13.716377Z digest=sha256:500bdb352c7723dfc085bd2cd721790cf6d964cc2ed6a66a18b17f26ff6b7e51

Observation 2fb63d71-039d-43af-8ba0-f4c1c92cc05c · inbound

Embedding Poisoning: Bypassing Safety Alignment via Embedding Semantic Shift cites this paper.

Embedding Poisoning: Bypassing Safety Alignment via Embedding Semantic Shift Adversarial Attacks and Defenses in Large Language Models: Old and New Threats

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-15T16:21:58.899446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:21:58.899446Z digest=sha256:4288961e623339f0d20a6b303affdf12a16bce48392024259393cecb17abbaa1

Observation 7fb5b359-25b7-4026-a817-4ab16410468e · inbound

Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework cites this paper.

Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework Adversarial Attacks and Defenses in Large Language Models: Old and New Threats

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-18T18:16:43.711016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-18T18:13:01.662828Z digest=sha256:697b621661ebe628ae23ee32a9fdbaa5c7c491ac48d17268843e22ec33eb19e6

Observation 77bb57f4-5806-4483-95b8-122f52a3ccc2 · inbound

SkipOPU: An FPGA-based Overlay Processor for Large Language Models with Dynamically Allocated Computation cites this paper.

SkipOPU: An FPGA-based Overlay Processor for Large Language Models with Dynamically Allocated Computation Adversarial Attacks and Defenses in Large Language Models: Old and New Threats

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-02T18:16:47.252198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T18:16:47.252198Z digest=sha256:2673f8e6d8c6e83c37356df57068507026d21045d0264388278e285b25fd505f

Observation 9b68111b-9039-4c6d-9df9-d91e75bffd56 · inbound

Same Model, Different Weakness: How Language and Modality Reshape the Jailbreak Attack Surface in Frontier MLLMs cites this paper.

Same Model, Different Weakness: How Language and Modality Reshape the Jailbreak Attack Surface in Frontier MLLMs Adversarial Attacks and Defenses in Large Language Models: Old and New Threats

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:05:22.787129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-25T05:03:57.453043Z digest=sha256:cc8b495d6f6a7b5fb1c0aee8d412bddeaa4c20075e9b448f9b1e81ada43e7a32