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Paper Citation Record · LEDGER

Simulate and Eliminate: Revoke Backdoors for Generative Large Language Models

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.07667.

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

pith.paper-citation-record.v1
2405.07667 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:11:15.619772Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T04:42:33.850961Z

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 6a7627fc-133b-41b5-b33a-a9ab929449a0 · inbound

PEFTGuard: Detecting Backdoor Attacks Against Parameter-Efficient Fine-Tuning cites this paper.

PEFTGuard: Detecting Backdoor Attacks Against Parameter-Efficient Fine-Tuning Simulate and Eliminate: Revoke Backdoors for Generative Large Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T12:11:15.619772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:11:15.619772Z digest=sha256:1c5a7fda999151023e2b80a988a2226a3f42eb8ede494ede3d9ae72fe32f9275

Observation dba8c6d9-a6d2-462f-9b68-38fc751fdea4 · inbound

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

Neutralizing Backdoors through Information Conflicts for Large Language Models Simulate and Eliminate: Revoke Backdoors for Generative Large Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-12T11:25:31.794884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:25:31.794884Z digest=sha256:c57f08f49691fdd2aa1cdf54c7cb9d5b81c256ed5d6d44aaebe534a2a12fc6bd

Observation c517f5ed-9f60-4c20-9edb-110b04aee8ee · inbound

Trading Devil RL: Backdoor attack via Stock market, Bayesian Optimization and Reinforcement Learning cites this paper.

Trading Devil RL: Backdoor attack via Stock market, Bayesian Optimization and Reinforcement Learning Simulate and Eliminate: Revoke Backdoors for Generative Large Language Models

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-11T05:12:11.726825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:12:11.726825Z digest=sha256:f4232eb768f6eb39220da8644aff143c5246cd9049d31b59c88ac8767319667b

Observation 8f7cfc2d-1ddc-48f4-b1ba-570a8dcaa382 · inbound

Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety cites this paper.

Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety Simulate and Eliminate: Revoke Backdoors for Generative Large Language Models

Reference 170

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:42:33.854206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-23T04:39:04.591722Z digest=sha256:4bba4dc33030ad2e59012e0c0e006e603592aef713e84a6778caa9dd0f223311

Observation 4f077a8f-1203-4cba-a65a-f28d099fbb70 · inbound

Defense Against LLM Backdoors using Critical Neuron Isolation Pruning cites this paper.

Defense Against LLM Backdoors using Critical Neuron Isolation Pruning Simulate and Eliminate: Revoke Backdoors for Generative Large Language Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-01T11:29:55.862558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T11:29:55.862558Z digest=sha256:ef03f8deacaa04919f7baca003498ce48f2e030059e23e1d3cfe8e68faf1d815