RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation | Paper Citation Record

Observation c76572a3-8091-4fff-a339-a97a94408c04 · outbound

This paper cites Yale University Press.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Yale University Press

Reference 1

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Observation 1ee6f9a4-eb73-49bd-b506-d75ef48e1df0 · outbound

This paper cites Algorithmic content moderation: Technical and political challenges in the automation of platform governance.Big Data & Society, 7(1).

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Algorithmic content moderation: Technical and political challenges in the automation of platform governance.Big Data & Society, 7(1)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.263650Z

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Observation b44d915d-0ee9-403f-a81f-9825fc26406a · outbound

This paper cites The hateful memes challenge: Detecting hate speech in multimodal memes.Advances in Neural Information Processing Systems (NeurIPS).

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation The hateful memes challenge: Detecting hate speech in multimodal memes.Advances in Neural Information Processing Systems (NeurIPS)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.306203Z

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Observation 73b6d848-712d-462a-acd3-1e96f7ade895 · outbound

This paper cites Assessing the generalizability of the hateful memes challenge dataset.Workshop on Online Abuse and Harms (WOAH).

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Assessing the generalizability of the hateful memes challenge dataset.Workshop on Online Abuse and Harms (WOAH)

Reference 4

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Observation 92f2739d-366b-4b78-ad07-6c07dc7c6928 · outbound

This paper cites Guardharmem and harmdetect: a multimodal dataset and baseline for harmful meme detection.Social Network Analysis and Mining.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Guardharmem and harmdetect: a multimodal dataset and baseline for harmful meme detection.Social Network Analysis and Mining

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.313000Z

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Observation cb58fc43-c807-4bb8-9297-998c10ac3559 · outbound

This paper cites Enhanced Multimodal Content Moderation of Children's Videos using Audiovisual Fusion.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Enhanced Multimodal Content Moderation of Children's Videos using Audiovisual Fusion

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:15:54.763537Z

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Observation 31cf1b0c-c18e-488c-a630-1c5c7ee60d37 · outbound

This paper cites Mm-safetybench: A benchmark for safety evaluation of multimodal large language models.European Conference on Computer Vision (ECCV).

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Mm-safetybench: A benchmark for safety evaluation of multimodal large language models.European Conference on Computer Vision (ECCV)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.295383Z

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Observation b221af96-e7ab-46a8-aa3d-05734cc10e1d · outbound

This paper cites MSTS: A Multimodal Safety Test Suite for Vision-Language Models.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation MSTS: A Multimodal Safety Test Suite for Vision-Language Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:15:54.769687Z

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Observation 92bc1c6d-d670-45d1-b123-181de42c3725 · outbound

This paper cites Mm-soc: Benchmark- ing multimodal large language models in social media platforms.Findings of the Association for Computational Linguistics (ACL).

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Mm-soc: Benchmark- ing multimodal large language models in social media platforms.Findings of the Association for Computational Linguistics (ACL)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.299651Z

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Observation 4fb872e6-df9b-44a2-9bef-ebe77d93a1c7 · outbound

This paper cites Benchmarking mllms on visually smuggled threats.OpenReview.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Benchmarking mllms on visually smuggled threats.OpenReview

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.292035Z

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Observation f0f2ab4e-b9a1-40cf-ab6d-eb788eadfd4a · outbound

This paper cites Davidson et al.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Davidson et al

Reference 11

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Observation 1369bf02-f7c2-446d-8650-f6513723985a · outbound

This paper cites Woodland, and Jose M.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Woodland, and Jose M

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.314721Z

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Observation 37e3268f-9379-4067-a36c-b87db76151f9 · outbound

This paper cites Watch your language: Investigating content moderation with large language models.International AAAI Conference on Web and Social Media (ICWSM).

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Watch your language: Investigating content moderation with large language models.International AAAI Conference on Web and Social Media (ICWSM)

Reference 13

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Observation 358b40a3-4536-4fe0-adf4-6484fa51d52a · outbound

This paper cites Advancing Content Moderation: Evaluating Large Language Models for Detecting Sensitive Content Across Text, Images, and Videos.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Advancing Content Moderation: Evaluating Large Language Models for Detecting Sensitive Content Across Text, Images, and Videos

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:15:54.775338Z

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Observation 778bff69-e2c3-4d45-8feb-0a4cc7e30112 · outbound

This paper cites Artificial intelligence risk management frame- work (ai rmf 1.0).

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Artificial intelligence risk management frame- work (ai rmf 1.0)

Reference 15

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Observation ca636a7b-14e4-40d5-9276-ebdb751812b0 · outbound

This paper cites Hee, Md Rafi Awal, Kim Traugott Wah Choo, and Roy Ka-Wei Lee.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Hee, Md Rafi Awal, Kim Traugott Wah Choo, and Roy Ka-Wei Lee

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.251501Z

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Observation c30ea03c-5e62-460b-93eb-e59047fb9000 · outbound

This paper cites GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning

Reference 17

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Observation 339e2126-dee5-49ba-9963-4d800d3388b0 · outbound

This paper cites BLM-Guard: Explainable multimodal ad moderation with chain-of-thought and policy-aligned rewards.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation BLM-Guard: Explainable multimodal ad moderation with chain-of-thought and policy-aligned rewards

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:15:54.712692Z

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Observation 20566b96-ccf4-409c-b117-3699d00ee101 · outbound

This paper cites Age appropriate de- sign: A code of practice for online services.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Age appropriate de- sign: A code of practice for online services

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.270626Z

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Observation beefeb0f-5cea-4fe7-8868-dbcdd1152186 · outbound

This paper cites Child online safety: Age-appropriate content.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Child online safety: Age-appropriate content

Reference 20

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Observation d70e1031-ffc1-49b3-a736-98dd80fd5635 · outbound

This paper cites Violent or graphic content policies.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Violent or graphic content policies

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:15:54.729667Z

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Observation 14f7a1eb-fdc3-4272-a467-ba1b730a8336 · outbound

This paper cites Do not post violent content.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Do not post violent content

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:15:54.791306Z

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Observation 9c8a6747-bc31-40fa-9e75-4218df2a1bd6 · outbound

This paper cites Approach to newsworthy content.https://transparency.meta.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Approach to newsworthy content.https://transparency.meta

Reference 23

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Observation f7b3f7b9-dc32-45c7-9365-9b191d14f660 · outbound

This paper cites Videos of teachers hitting children.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Videos of teachers hitting children

Reference 24

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Observation 21e413a3-5b92-4b71-8056-17ce9dbc75a8 · outbound

This paper cites an unresolved cited work.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Unresolved cited work

Reference 25

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This paper cites Gemini 3.1 pro model card.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Gemini 3.1 pro model card

Reference 26

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This paper cites Claude opus 4.6 system card.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Claude opus 4.6 system card

Reference 27

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This paper cites Qwen2.5-VL Technical Report.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Qwen2.5-VL Technical Report

Reference 28

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This paper cites Qwen3-VL Technical Report.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Qwen3-VL Technical Report

Reference 29

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This paper cites InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Reference 30

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This paper cites LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models

Reference 31

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RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Unresolved cited work

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RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Unresolved cited work

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RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation independent

Reference 34

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RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation decision_relations

Reference 35

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RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Unresolved cited work

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RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Unresolved cited work

Reference 37

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This paper cites It proposes a benchmark formulation, dataset construction protocol, and empirical evaluation.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation It proposes a benchmark formulation, dataset construction protocol, and empirical evaluation

Reference 38

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Observation 1bc2c9e3-f9b5-409d-8e65-3757937adfe5 · outbound

This paper cites Prompts, parsing rules, task- specific breakdowns, and additional results are provided in Appendices A and E.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Prompts, parsing rules, task- specific breakdowns, and additional results are provided in Appendices A and E

Reference 39

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This paper cites We will release the dataset, prompts, and evaluation scripts with documentation for repro- ducing the main experiments.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation We will release the dataset, prompts, and evaluation scripts with documentation for repro- ducing the main experiments

Reference 40

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This paper cites Additional prompt templates, task-specific settings, and detailed results are provided in Appendices A and E.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Additional prompt templates, task-specific settings, and detailed results are provided in Appendices A and E

Reference 41

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RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Unresolved cited work

Reference 42

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This paper cites Appendix E includes implementation details for running the evaluation, including model access assumptions and evaluation scripts.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Appendix E includes implementation details for running the evaluation, including model access assumptions and evaluation scripts

Reference 43

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This paper cites The paper documents harmful-content handling, intended use, prohibited use, privacy filtering, annotator safety considerations, and release procedures in Appendix F.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation The paper documents harmful-content handling, intended use, prohibited use, privacy filtering, annotator safety considerations, and release procedures in Appendix F

Reference 44

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RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Unresolved cited work

Reference 45

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RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Unresolved cited work

Reference 46

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This paper cites Appendix F documents source attribution, licensing considera- tions, redistribution constraints, and release procedures.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Appendix F documents source attribution, licensing considera- tions, redistribution constraints, and release procedures

Reference 47

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This paper cites Appendix F provides dataset documentation, including data fields, source material, annotation process, intended use, release format, and maintenance plan.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Appendix F provides dataset documentation, including data fields, source material, annotation process, intended use, release format, and maintenance plan

Reference 48

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Observation f8a9e7e1-b76a-4f9e-ba00-20020c1ccaf1 · outbound

This paper cites Appendix B provides the annotation guidelines, task instructions, reliability analysis, and human expert reference protocol.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Appendix B provides the annotation guidelines, task instructions, reliability analysis, and human expert reference protocol

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.301656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 72cb465f-c652-44e2-a49d-c93a1207c0fc · outbound

This paper cites Appendix F describes annotator safety procedures, exposure warnings, and data handling.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation Appendix F describes annotator safety procedures, exposure warnings, and data handling

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.290423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2114839c-c36b-4742-b5e0-4868fed50f1d · outbound

This paper cites These outputs are used only for candidate generation or routing and do not define final labels, which are expert-reviewed or adjudicated.

RuleSafe-VL: Evaluating Rule-Conditioned Decision Reasoning in Vision-Language Content Moderation These outputs are used only for candidate generation or routing and do not define final labels, which are expert-reviewed or adjudicated

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T10:54:13.288565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers