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Paper Citation Record · LEDGER

Multi-target Backdoor Attacks for Code Pre-trained Models

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2306.08350.

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

pith.paper-citation-record.v1
2306.08350 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:25:31.810305Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T06:25:21.067297Z

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 6a7ccbb2-e578-4c65-baf9-bb75f8015138 · inbound

GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts cites this paper.

GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts Multi-target Backdoor Attacks for Code Pre-trained Models

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-15T06:25:21.070163Z

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=2026-05-15T06:25:20.966510Z digest=sha256:6b8d74e48956df914a4f5959adf6b0ab26ba79cbef904644316a0052c4e415fa

Observation f89a63e3-32a8-477d-9ddd-48c55ed2c1e6 · inbound

Neutralizing Backdoors through Information Conflicts for Large Language Models cites this paper.

Neutralizing Backdoors through Information Conflicts for Large Language Models Multi-target Backdoor Attacks for Code Pre-trained Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T11:25:31.810305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:25:31.810305Z digest=sha256:e37986899850aaf1d047117078ece5edb573fe6e7948effd0e740c42f8f4c76c

Observation b5012e99-a571-485f-9ab2-bbf7774931db · inbound

Lethe: Purifying Backdoored Large Language Models with Knowledge Dilution cites this paper.

Lethe: Purifying Backdoored Large Language Models with Knowledge Dilution Multi-target Backdoor Attacks for Code Pre-trained Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T14:42:31.435614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:42:31.435614Z digest=sha256:1ad68ba40131a2f98ac0c4ea5154e123ed60b698f8f3bd671368e3046a8cbac8