SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI | Paper Citation Record

Observation e386d600-11db-4447-bbb0-3bdb46b0c2e6 · outbound

This paper cites and Bates, Stephen and Fisch, Adam and Lei, Lihua and Schuster, Tal , title =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI and Bates, Stephen and Fisch, Adam and Lei, Lihua and Schuster, Tal , title =

Reference 1

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Unresolved cited work

Reference 2

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI 225 , year =

Reference 3

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This paper cites Proceedings of the 42nd International Conference on Machine Learning , year =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Proceedings of the 42nd International Conference on Machine Learning , year =

Reference 4

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Reference 5

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This paper cites Official Journal of the European Union , url =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Official Journal of the European Union , url =

Reference 6

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This paper cites Advances in Neural Information Processing Systems , volume =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Advances in Neural Information Processing Systems , volume =

Reference 7

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This paper cites Computer Aided Verification , series =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Computer Aided Verification , series =

Reference 8

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This paper cites Journal of Logic and Algebraic Programming , volume =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Journal of Logic and Algebraic Programming , volume =

Reference 9

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This paper cites Proceedings of the 41st International Conference on Machine Learning , series =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Proceedings of the 41st International Conference on Machine Learning , series =

Reference 10

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Observation 2f581593-88e8-4a40-a6b1-6ec21efb9731 · outbound

This paper cites 2023 , doi =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI 2023 , doi =

Reference 11

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI 2024 , doi =

Reference 12

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Unresolved cited work

Reference 13

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This paper cites Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages =

Reference 14

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This paper cites and Schroeder, Michael D.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI and Schroeder, Michael D

Reference 15

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Unresolved cited work

Reference 16

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This paper cites Advances in Neural Information Processing Systems , volume =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Advances in Neural Information Processing Systems , volume =

Reference 17

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI International Conference on Learning Representations , year =

Reference 18

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Observation 3fbdd567-3e93-477e-bb33-75531a62bb26 · outbound

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Unresolved cited work

Reference 19

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Observation 85db97ed-5629-4e6c-a6e7-e1e92567facf · outbound

This paper cites Advances in Neural Information Processing Systems , volume =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Advances in Neural Information Processing Systems , volume =

Reference 20

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This paper cites 2024 , url =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI 2024 , url =

Reference 21

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Unresolved cited work

Reference 22

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Unresolved cited work

Reference 23

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Unresolved cited work

Reference 24

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI 2025 , url =

Reference 25

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Observation b93cbb9c-790a-42b5-8ff5-3d6436ade7e0 · outbound

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Unresolved cited work

Reference 26

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI 2023 , howpublished =

Reference 27

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations , pages =

Reference 28

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI 2024 , howpublished =

Reference 29

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Proceedings of the AAAI Conference on Artificial Intelligence , volume =

Reference 30

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This paper cites 2025 , howpublished =.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI 2025 , howpublished =

Reference 31

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI and Deshpande, Kaustubh and Sirdeshmukh, Ved and Mankikar, Meher and Scale Red Team and SEAL Research Team and Michael, Julian , journal =

Reference 33

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Safer or Luckier?

Reference 35

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Investigating the Potential Use of Frontier

Reference 36

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI 2025 , howpublished =

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Investigating the potential use of frontier AI models for offensive cyberattacks: A human uplift study

Reference 38

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Angelopoulos, Stephen Bates, Adam Fisch, Lihua Lei, and Tal Schuster

Reference 39

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This paper cites Why do we take LLM s seriously as a potential source of biorisk? https://www.anthropic.com/research/biorisk, 2025.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Why do we take LLM s seriously as a potential source of biorisk? https://www.anthropic.com/research/biorisk, 2025

Reference 40

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Claude system cards, 2026

Reference 41

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Safer or luckier? LLM s as safety evaluators are not robust to artifacts

Reference 42

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Framework convention on artificial intelligence and human rights, democracy and the rule of law, cets no

Reference 43

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI OR-Bench : An over-refusal benchmark for large language models

Reference 44

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Secure by design, 2023

Reference 45

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI General-purpose AI code of practice, 2025

Reference 46

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Regulation (eu) 2024/1689 laying down harmonised rules on artificial intelligence, 2024

Reference 47

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Selective classification for deep neural networks

Reference 48

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Gemini 3 pro model card, 2026

Reference 49

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI An Empirical Study of Multi-Generation Sampling for Jailbreak Detection in Large Language Models

Reference 50

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations

Reference 51

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI FORTRESS: Frontier Risk Evaluation for National Security and Public Safety

Reference 52

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI PRISM 4.0: Verification of probabilistic real-time systems

Reference 53

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI A brief account of runtime verification

Reference 54

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI A holistic approach to undesired content detection in the real world

Reference 55

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI HarmBench : A standardized evaluation framework for automated red teaming and robust refusal

Reference 56

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Artificial intelligence risk management framework ( AI RMF 1.0)

Reference 57

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Artificial intelligence risk management framework: Generative artificial intelligence profile

Reference 58

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SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI CAISI evaluation of DeepSeek ai models finds shortcomings and risks

Reference 59

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Observation 8c2266c6-4d8b-4abe-a70d-78fdef69d4ca · outbound

This paper cites GPT-5 system card, 2025.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI GPT-5 system card, 2025

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.755866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a44b9562-4e4e-4158-90da-effe1154a8df · outbound

This paper cites GPT-5.5 system card, 2026.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI GPT-5.5 system card, 2026

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.760363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cc1b510-a081-4d37-a465-c8fa80c98ce4 · outbound

This paper cites Evaluating Frontier Models for Dangerous Capabilities.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Evaluating Frontier Models for Dangerous Capabilities

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.764877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c60f9e8-3e1f-4254-8244-8600bc86b4d8 · outbound

This paper cites NeMo guardrails: A toolkit for controllable and safe LLM applications with programmable rails.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI NeMo guardrails: A toolkit for controllable and safe LLM applications with programmable rails

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.769159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76462850-05c8-4e54-a52a-3e78fa128dd6 · outbound

This paper cites XSTest : A test suite for identifying exaggerated safety behaviours in large language models.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI XSTest : A test suite for identifying exaggerated safety behaviours in large language models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.773831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a7feac4-3d05-441e-ba13-57d03795735e · outbound

This paper cites Saltzer and Michael D.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Saltzer and Michael D

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.778247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4b4bc95-6f10-4c78-bee9-f8301d54e997 · outbound

This paper cites Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.782750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71c8b7a1-6495-44bc-a25b-fd2cd0dc4005 · outbound

This paper cites Judging the judges: A systematic study of position bias in LLM -as-a-judge.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Judging the judges: A systematic study of position bias in LLM -as-a-judge

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.787855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5df24c37-9aa2-4d7b-ba37-12d9d6864e5f · outbound

This paper cites A StrongREJECT for empty jailbreaks.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI A StrongREJECT for empty jailbreaks

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.792585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90034dc1-7a10-4e5c-bbaa-aca42dac7f46 · outbound

This paper cites Frontier AI safety commitments, AI seoul summit 2024, 2024.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Frontier AI safety commitments, AI seoul summit 2024, 2024

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.797189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fa189bb-86f1-4bba-aff1-8d6c721b71fd · outbound

This paper cites Grok 4.1 model card, 2025.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Grok 4.1 model card, 2025

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.802025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccf80d18-6a88-4ddf-bc67-ab897124dd4b · outbound

This paper cites SORRY-Bench : Systematically evaluating large language model safety refusal.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI SORRY-Bench : Systematically evaluating large language model safety refusal

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.806410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 679131dd-d80e-44e7-9fc4-fcbb10eb3d2a · outbound

This paper cites ShieldGemma: Generative AI Content Moderation Based on Gemma.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI ShieldGemma: Generative AI Content Moderation Based on Gemma

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.810542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20ab5d61-2eaa-4375-92a1-14c712e8dede · outbound

This paper cites Judging LLM -as-a-judge with MT-Bench and chatbot arena.

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI Judging LLM -as-a-judge with MT-Bench and chatbot arena

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-01T04:12:58.815158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

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Outbound references

Pith citing papers