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Paper Citation Record · LEDGER

Unleashing GHOST: An LLM-Powered Framework for Automated Hardware Trojan Design

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.02816.

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

pith.paper-citation-record.v1
2412.02816 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:39:15.857392Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T09:36:26.568013Z

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 c904fc10-9917-44fa-84e9-c86b4cf276e9 · inbound

Architectural Backdoors in Deep Learning: A Survey of Vulnerabilities, Detection, and Defense cites this paper.

Architectural Backdoors in Deep Learning: A Survey of Vulnerabilities, Detection, and Defense Unleashing GHOST: An LLM-Powered Framework for Automated Hardware Trojan Design

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T16:39:15.857392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:39:15.857392Z digest=sha256:2cab54b03eb9971e280f0345f5011c416bb313e811a08ae7469e414265b53d77

Observation 45872eff-c932-4e53-a4fc-3f6cd4b21805 · inbound

SafeTune: Mitigating Data Poisoning in LLM Fine-Tuning for RTL Code Generation cites this paper.

SafeTune: Mitigating Data Poisoning in LLM Fine-Tuning for RTL Code Generation Unleashing GHOST: An LLM-Powered Framework for Automated Hardware Trojan Design

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:36:26.570412Z

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.

source=pdf_text observed=2026-05-07T10:16:07.200458Z digest=sha256:a7c7efe60095121e0506efe00d8acc2ea74645f5c16b8c652bdf7a81bf1f0f00