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Paper Citation Record · LEDGER

Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2503.06269.

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

pith.paper-citation-record.v1
2503.06269 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:24:26.474285Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6077e1dc-c411-4eb3-8de1-7e23de6a6069 · inbound

Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safety cites this paper.

Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safety Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T10:24:26.474285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:24:26.474285Z digest=sha256:447e2fa0f986e9c8c550e21b1a81f39a0dc41aed26a250629488dad624682320

Observation 4ca628cc-f4bc-4d34-a9c6-e8f5707518ee · inbound

Activation-Guided Local Editing for Jailbreaking Attacks cites this paper.

Activation-Guided Local Editing for Jailbreaking Attacks Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-07T02:17:06.219018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T01:35:34.320711Z digest=sha256:3b4dbf0b590e2f90f279ae87384ddcdd757d0e42ddcd5d29442acd29960ea9b7

Observation 11b013cf-96b5-4ecd-bb13-bb92445cb2c5 · inbound

Why Do Large Language Models Generate Harmful Content? cites this paper.

Why Do Large Language Models Generate Harmful Content? Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-07-07T02:17:06.219018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T15:31:13.545599Z digest=sha256:8a4f59a7e4de424ba7b631904ac9c3e7f3653a4f2541f5e2b51f7b6deb59677c

Observation 5de88d15-5e2d-4a26-a689-c21d1a2e888a · inbound

Subspace-Aware Sparse Autoencoders for Effective Mechanistic Interpretability cites this paper.

Subspace-Aware Sparse Autoencoders for Effective Mechanistic Interpretability Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models

Reference 21

Resolution
metadata mismatch
arxiv_id, observed 2026-07-07T02:17:06.219018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-28T02:07:18.198225Z digest=sha256:76e63125d7be68b833e8bab469a545ee9822a27da83c970cb4e456bbaf3d3ff6

Observation 06ccf45b-12eb-41f1-9dff-3fd8b955c8e2 · inbound

Investigating The Security of Modern AI and Cloud Infrastructure cites this paper.

Investigating The Security of Modern AI and Cloud Infrastructure Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models

Reference 139

Resolution
metadata mismatch
arxiv_id, observed 2026-07-07T02:17:06.219018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-26T11:31:39.910784Z digest=sha256:be99bad0a15e562e0a0bcf89d24f3c9408edc892924f47248f79e259d2bd83be

Observation ef9f9c5d-fc68-40c3-b21a-3fa395b573a9 · inbound

How Do LLMs Cite? A Mechanistic Interpretation of Attribution in Retrieval-Augmented Generation cites this paper.

How Do LLMs Cite? A Mechanistic Interpretation of Attribution in Retrieval-Augmented Generation Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-07-07T02:17:06.219018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-30T11:12:02.227976Z digest=sha256:c7021fe7bd548d67b080f7f282b92d8f43489bf5e05ef8101caa6b93eb18dbbf