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Paper Citation Record · LEDGER

Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2409.01586.

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

pith.paper-citation-record.v1
2409.01586 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:58:29.726809Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T21:05:04.078784Z

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 93af6967-16e1-40b8-8330-285e22e4bfa0 · inbound

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey cites this paper.

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-23T20:58:26.165122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T20:58:16.237327Z digest=sha256:24355fcc1f491c7e9fa3db20f8449fd94f5c0b0073c61ea7bdab8a628670e86e

Observation 730e1b8c-f0d2-4475-a877-ecd165e9bca3 · 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 Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 121

Resolution
metadata mismatch
arxiv_id, observed 2026-05-23T04:42:33.745007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T04:39:04.591722Z digest=sha256:b37634f8e4eb0c69550b2d2b6982a64c226a1f675e252783270b940a2ea17021

Observation 9e4699fb-d4ab-4a02-8f2d-b0fbe064a521 · inbound

Secure LLM Fine-Tuning via Safety-Aware Probing cites this paper.

Secure LLM Fine-Tuning via Safety-Aware Probing Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T13:11:35.859103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T13:07:09.402763Z digest=sha256:3a674c7bb35b724d3446607b66edcc4de2e7a6ba8da7884b3c910576d5b63600

Observation 432e1bfa-79a9-4200-a759-08918ef0de8c · inbound

Vulnerability-Aware Alignment: Mitigating Uneven Forgetting in Harmful Fine-Tuning cites this paper.

Vulnerability-Aware Alignment: Mitigating Uneven Forgetting in Harmful Fine-Tuning Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T10:58:29.726809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:58:29.726809Z digest=sha256:ba5677348802bc081fc11c9b2ab7643b92cea83c27c16ddf58eb6c01965fb3c3

Observation c3e88d80-0562-4312-a7f4-06d60523dc35 · inbound

Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning cites this paper.

Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T20:41:50.562505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T20:40:44.496392Z digest=sha256:f694ca8db9a0c6d66545cbd61f3fee1fc564e6750933495599b48a4a54d4db0c

Observation 0f8c58c5-b4a2-45ad-84ff-55c498bcb8cb · inbound

Anchoring Refusal Direction: Mitigating Safety Risks in Tuning via Projection Constraint cites this paper.

Anchoring Refusal Direction: Mitigating Safety Risks in Tuning via Projection Constraint Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-04T23:10:21.153674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:10:21.153674Z digest=sha256:b54fe450ee6d6f2834c6d5e4597adfae60c445f092dbaf3cf858bac1bfa14971

Observation 8cfb6400-5c9e-4148-bcae-beb5aafdf18e · inbound

MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security cites this paper.

MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-04T23:09:41.485922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:09:41.485922Z digest=sha256:e20d587a14a22a9c4361c2d2ad05503942e7a22277221c9c57faf27df73c5664

Observation 9d77a97c-4df9-4c06-9fed-156425c79b0f · inbound

Preventing Safety Drift in Large Language Models via Coupled Weight and Activation Constraints cites this paper.

Preventing Safety Drift in Large Language Models via Coupled Weight and Activation Constraints Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:21:01.793449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T16:04:25.851592Z digest=sha256:ab7a22efc366f81ed7ca0b417484271e42ff5672ec4467a8a013517288a448a4

Observation 39d3deeb-87fd-4701-ad08-215b3685191a · inbound

AlignCultura: Towards Culturally Aligned Large Language Models? cites this paper.

AlignCultura: Towards Culturally Aligned Large Language Models? Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T12:56:05.116988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T02:36:36.854805Z digest=sha256:8ff2b1868e34ef70f1093c27908e56ce3e6074a9afefbe7dca95b2143e55d29b

Observation fe145d2a-9633-4509-bd91-3e1d021b8255 · inbound

Information Extraction of Nested Complex Structure of Quantum Cascade Lasers via Large Language Models cites this paper.

Information Extraction of Nested Complex Structure of Quantum Cascade Lasers via Large Language Models Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 57

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T04:41:21.968863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T04:40:40.693392Z digest=sha256:fe50a2513db5ef08abfcc6110fc87f10981341d3ab0e05b0b9bdb4b259b5d881

Observation a2dfaf6b-1bf7-4400-82bf-315d25f2f086 · inbound

One Step to the Side: Why Defenses Against Malicious Finetuning Fail Under Adaptive Adversaries cites this paper.

One Step to the Side: Why Defenses Against Malicious Finetuning Fail Under Adaptive Adversaries Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T21:05:04.080397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T21:01:25.549340Z digest=sha256:dcdfb9bc60815607d57cd3b9d055501770c847dede0048d4c2e07e602d461e07

Observation 75e4eee9-a5e3-4ba6-a677-00a307f7fe34 · inbound

SPARD: Defending Harmful Fine-Tuning Attack via Safety Projection with Relevance-Diversity Data Selection cites this paper.

SPARD: Defending Harmful Fine-Tuning Attack via Safety Projection with Relevance-Diversity Data Selection Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-06-29T13:53:28.635480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T13:49:56.311711Z digest=sha256:67d911a205ddf7d3dbe51df114f841adb442ca04fd1e6ca6273e31cc9ca7ecf9

Observation 0bee95b9-158f-44c2-a685-f6661945d8cc · inbound

HyperSafe: Inference-Time Safety Recovery for Fine-Tuned Language Models cites this paper.

HyperSafe: Inference-Time Safety Recovery for Fine-Tuned Language Models Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 26

Resolution
unresolved
no resolver link, observed 2026-07-14T05:21:30.132993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T05:21:30.132993Z digest=sha256:a874d38ad6f31782543e59cfbe980eaadbc1b29b3041be773f0874d2841f3f20

Observation 1eaae0ff-20ab-47a9-93f8-65a8648886a3 · inbound

Emergent Misalignment Recruits a Pre-existing Persona Subspace cites this paper.

Emergent Misalignment Recruits a Pre-existing Persona Subspace Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 139

Resolution
unresolved
no resolver link, observed 2026-08-01T07:46:17.515379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T07:46:17.515379Z digest=sha256:c466c0ec9291bf884a39faa9c1352430afb8e877bea925dc6659209090af92a4

Observation b9582b11-b73f-412c-8a81-e4eb05b95bef · inbound

Gradient Immunity: Null-Space Resistance to Malicious Fine-Tuning cites this paper.

Gradient Immunity: Null-Space Resistance to Malicious Fine-Tuning Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-06T10:46:10.851158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:46:10.851158Z digest=sha256:dabd311fee5caeb67fba5bd9dc69cbce96d267d31d3f15b5442f37601f1ebfd3