Paper Citation Record · LEDGER

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 35 inbound Pith citation observations for arXiv:2402.02207.

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

pith.paper-citation-record.v1
2402.02207 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 35 of 35 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 35 of 35 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:03:01.316234Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:39:16.634455Z

Reference resolution

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verified fuzzy0
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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d7a3d07d-855a-4e34-95f5-14b1e8d80198 · inbound

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone cites this paper.

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-10T20:19:27.304004Z

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.

Observation a8c50b2c-35f0-4872-aab9-a53c76c3262e · 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 Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 183

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:58:25.915671Z

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.

Observation ecf8ee3c-e995-45ad-acaa-e82216bc12c9 · inbound

Immune: Improving Safety Against Jailbreaks in Multi-modal LLMs via Inference-Time Alignment cites this paper.

Immune: Improving Safety Against Jailbreaks in Multi-modal LLMs via Inference-Time Alignment Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-12T11:03:01.316234Z

Source-reported events for the cited work

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Observation 95eaffb2-62e0-4c0b-badd-add4a4c5c957 · inbound

VLSBench: Unveiling Visual Leakage in Multimodal Safety cites this paper.

VLSBench: Unveiling Visual Leakage in Multimodal Safety Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T05:56:46.644425Z

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Observation 0d0b2274-fdd0-414f-b98b-7dacf4054af5 · inbound

Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features cites this paper.

Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 112

Resolution: unresolved; no resolver link, observed 2026-08-12T10:24:06.953421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7c02c9a-27b9-43be-af1b-bac8b97313e5 · inbound

Semantic Loss Guided Data Efficient Supervised Fine Tuning for Safe Responses in LLMs cites this paper.

Semantic Loss Guided Data Efficient Supervised Fine Tuning for Safe Responses in LLMs Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T20:33:59.583034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78aa38a4-f88a-4517-aa7c-0e1b43be75c5 · inbound

RapGuard: Safeguarding Multimodal Large Language Models via Rationale-aware Defensive Prompting cites this paper.

RapGuard: Safeguarding Multimodal Large Language Models via Rationale-aware Defensive Prompting Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T04:29:04.378439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ba08b25-c7d1-4545-896a-6847b723fea5 · inbound

Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging cites this paper.

Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-11T00:18:57.358405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a039b72-1081-4d6c-9c6c-26e53fa002e0 · inbound

Jailbreaking Multimodal Large Language Models via Shuffle Inconsistency cites this paper.

Jailbreaking Multimodal Large Language Models via Shuffle Inconsistency Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-10T21:26:00.687983Z

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Observation d2d7f9c5-5a15-4d84-92e2-f7394851636f · inbound

Internal Activation Revision: Safeguarding Vision Language Models Without Parameter Update cites this paper.

Internal Activation Revision: Safeguarding Vision Language Models Without Parameter Update Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T15:19:10.185796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fa57646-fe9f-4fef-ae7e-95bd036355e5 · inbound

When Data Manipulation Meets Attack Goals: An In-depth Survey of Attacks for VLMs cites this paper.

When Data Manipulation Meets Attack Goals: An In-depth Survey of Attacks for VLMs Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-08T15:38:17.335773Z

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Observation bf4c39da-e164-4a99-8e60-4ee06a4b2c4c · inbound

MM-RLHF: The Next Step Forward in Multimodal LLM Alignment cites this paper.

MM-RLHF: The Next Step Forward in Multimodal LLM Alignment Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-07T18:23:50.561901Z

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Observation e1a1672a-9ef9-4020-833a-cd655bfca1ab · inbound

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations cites this paper.

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T19:45:18.653326Z

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Observation 8483c4d9-565f-4c1c-a4cd-6bf3729d0d31 · inbound

Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs cites this paper.

Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:22:27.772873Z

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.

Observation ce6b2979-7bd1-4c8c-8804-4e63a1728c37 · inbound

VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration cites this paper.

VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T14:13:13.390836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7030a2a-6b04-40d9-aa36-666ba7ecdcdf · inbound

Seeing the Threat: Vulnerabilities in Vision-Language Models to Adversarial Attack cites this paper.

Seeing the Threat: Vulnerabilities in Vision-Language Models to Adversarial Attack Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T13:22:03.217330Z

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Unavailable: canonical work link unavailable.

Observation eb3ea9cb-e2c6-4341-a225-4e1d40090c0e · inbound

Bootstrapping LLM Robustness for VLM Safety via Reducing the Pretraining Modality Gap cites this paper.

Bootstrapping LLM Robustness for VLM Safety via Reducing the Pretraining Modality Gap Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:37:22.785969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8bbe007-6169-48fa-8d86-030ac4ed2cb4 · inbound

LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning cites this paper.

LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T23:59:57.357277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2429dbe8-2f4d-407a-ba74-8daf01e091ec · inbound

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security cites this paper.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T12:09:39.851015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf2017b8-9f15-4b28-8d26-e7b6bd44b6bf · inbound

Attention Misses Visual Risk: Risk-Adaptive Steering for Multimodal Safety Alignment cites this paper.

Attention Misses Visual Risk: Risk-Adaptive Steering for Multimodal Safety Alignment Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T09:47:25.752076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1221b4cb-e16b-48f8-ad78-319fbd1f8d79 · inbound

VisInject: Disruption != Injection -- A Dual-Dimension Evaluation of Universal Adversarial Attacks on Vision-Language Models cites this paper.

VisInject: Disruption != Injection -- A Dual-Dimension Evaluation of Universal Adversarial Attacks on Vision-Language Models Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:56:08.104516Z

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.

Observation 50a962c4-c771-4438-98eb-8eb5bb46a5d3 · inbound

SafeSteer: A Decoding-level Defense Mechanism for Multimodal Large Language Models cites this paper.

SafeSteer: A Decoding-level Defense Mechanism for Multimodal Large Language Models Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T06:57:27.567797Z

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.

Observation 32ee3930-4fa1-4a5c-a920-8e1f3c209439 · inbound

When Vision Speaks for Sound cites this paper.

When Vision Speaks for Sound Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 78

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T22:13:46.890434Z

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.

Observation d7ac1984-15fb-4452-9c8d-85fd12cb450a · inbound

New Wide-Net-Casting Jailbreak Attacks Risk Large Models cites this paper.

New Wide-Net-Casting Jailbreak Attacks Risk Large Models Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:48:23.282107Z

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.

Observation 17dedf34-b8d5-43ac-9625-8babb5a25583 · inbound

Attention Hijacking: Response Manipulation Across Queries in Vision-Language Models cites this paper.

Attention Hijacking: Response Manipulation Across Queries in Vision-Language Models Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:28:21.653719Z

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.

Observation 19a1efc1-61d2-455c-a265-ffd6b2611629 · inbound

SafeSteer: Localized On-Policy Distillation for Efficient Safety Alignment cites this paper.

SafeSteer: Localized On-Policy Distillation for Efficient Safety Alignment Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 96

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T23:06:20.936544Z

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.

Observation 7681ac16-98ff-4654-9fab-b42a903747be · inbound

Constitutional On-Policy Safe Distillation cites this paper.

Constitutional On-Policy Safe Distillation Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:36:25.407430Z

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.

Observation 963082fe-a130-41cd-a8ba-16e83fc9f647 · inbound

Defending Against Malicious Finetuning by Scaling Train-time Adversarial Attacks cites this paper.

Defending Against Malicious Finetuning by Scaling Train-time Adversarial Attacks Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T20:47:22.922495Z

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.

Observation b03194f8-4fab-4c20-8960-01ce3c01d358 · inbound

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges cites this paper.

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 86

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T01:27:30.930139Z

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.

Observation 1e3f848c-fe44-4608-a4b8-3781ff6f3008 · inbound

ROBOSHACKLES: A Safety Dataset for Human-Injury Prevention in Embodied Foundation Models cites this paper.

ROBOSHACKLES: A Safety Dataset for Human-Injury Prevention in Embodied Foundation Models Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T00:39:16.636275Z

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.

Observation 9f7c5791-3228-4039-ab3d-795e5fbf26a5 · inbound

Safe responses matter: Output-aware safety guardrail mitigate over-refusal in MLLMs cites this paper.

Safe responses matter: Output-aware safety guardrail mitigate over-refusal in MLLMs Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-14T17:33:49.041193Z

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Unavailable: canonical work link unavailable.

Observation 7e02f988-e635-400b-a83d-0e25b20f020b · inbound

V-DEAL: Diagnosing Video Safety De-Calibration as an Understanding-Refusal Coupling Failure cites this paper.

V-DEAL: Diagnosing Video Safety De-Calibration as an Understanding-Refusal Coupling Failure Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T08:23:27.722142Z

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Observation f0361a0a-a3ba-47dc-a2d9-4bdd3ed26e80 · inbound

One Anchor for All: Unified Multilingual and Multimodal Safety Alignment for LVLMs cites this paper.

One Anchor for All: Unified Multilingual and Multimodal Safety Alignment for LVLMs Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-31T23:07:40.461286Z

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Unavailable: canonical work link unavailable.

Observation 647a6d08-e704-4322-adac-17452bb3262e · inbound

A Multimodal Automatic Redteaming Evaluation based on Atomic Jailbreak Strategy Decoupling and Combination cites this paper.

A Multimodal Automatic Redteaming Evaluation based on Atomic Jailbreak Strategy Decoupling and Combination Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 165

Resolution: unresolved; no resolver link, observed 2026-08-07T00:14:51.629463Z

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Unavailable: canonical work link unavailable.

Observation a2b8fe25-7ebe-41b8-95d7-33b9b1ea1b7a · inbound

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

Gradient Immunity: Null-Space Resistance to Malicious Fine-Tuning Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-06T10:46:10.797684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.