Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T17:41:14.893434Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2607.17575.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T17:41:14.893434Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
39 of 39 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation a676ecb6-680c-4c2c-ba6d-b23ceab34b1d · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2025 , eprint=
Reference 1
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Observation 699330c4-26f0-44ab-96a3-24dddb3cd541 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails , journal=
Reference 2
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Observation 0e944141-cdd2-4148-a6cc-1d3a91e2fa8c · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Focal Loss for Dense Object Detection , year=
Reference 3
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Observation 729ce0d3-1b6d-40bd-b03f-6e73b58bb24c · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , month =
Reference 4
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Observation 9fb6e5dd-6ebe-4a37-be9f-c1dde874aac1 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Advances in neural information processing systems , volume=
Reference 5
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Observation a2868f8e-a838-41dc-b94c-b5e5ed5df194 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Advances in Neural Information Processing Systems , volume=
Reference 6
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Observation 21d5c186-1164-442d-9898-ed1c67077bcc · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Advances in Neural Information Processing Systems , volume=
Reference 7
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Unavailable: canonical work link unavailable.
Observation e0ed4f7c-85ae-473a-a25e-8456e162fcf1 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails International Conference on Learning Representations , year=
Reference 8
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Unavailable: canonical work link unavailable.
Observation 924c4245-b0bd-4517-b052-35debd7160aa · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails and Shen, Yelong and Wallis, Phillip and Allen-Zhu, Zeyuan and Li, Yuanzhi and Wang, Shean and Wang, Lu and Chen, Weizhu , booktitle=
Reference 9
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Observation cc17a8c6-4803-4e58-a64d-af53bdb010ed · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2024 , eprint=
Reference 10
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Observation 676a8799-868f-4ea3-b635-9309624deefb · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2023 , eprint=
Reference 11
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Observation b4ff3818-7ec1-4014-badf-d67bcb19da28 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails AEGIS: Online Adaptive AI Content Safety Moderation with Ensemble of LLM Experts
Reference 12
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Unavailable: canonical work link unavailable.
Observation 75a9ad8d-38e8-4f95-b3bf-e0e8254f3d51 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Why Should I Trust You?
Reference 13
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Observation d64b639d-4de7-4621-ad44-aca8c8657b96 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Advances in Neural Information Processing Systems , volume=
Reference 14
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Unavailable: canonical work link unavailable.
Observation 1bc1f87d-385a-4433-91f2-33b429b9c815 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Safety Layers in Aligned Large Language Models: The Key to LLM Security
Reference 15
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Observation 20830b46-1ab2-448e-95b6-2edad9f92057 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2024 , eprint=
Reference 16
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Observation 7c08dfc8-3af8-42a7-9475-f64cb4a8dc78 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2025 , eprint=
Reference 17
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Unavailable: canonical work link unavailable.
Observation 5d3f6084-5e55-4597-a282-eade13692f77 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security , pages =
Reference 18
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Observation 946b17c7-1c3c-47ad-bcb9-732a306d42ee · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2024 , eprint=
Reference 19
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Observation 5c49e62c-a0fa-4554-99bb-9e5d8172e279 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2025 , eprint=
Reference 20
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Observation 8594fac1-4aba-4d78-b4ff-1d2dcf19034d · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2025 , eprint=
Reference 21
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Observation 194766df-f3fc-4ee5-b3e4-e98f131d6330 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails International Conference on Learning Representations (ICLR) , year=
Reference 22
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Unavailable: canonical work link unavailable.
Observation 251709d5-1aed-4f85-8d74-73a188410857 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Forty-second International Conference on Machine Learning , year=
Reference 23
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Observation 160621a4-3af7-4f98-983d-d151546d850b · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2022 , eprint=
Reference 24
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Observation dad4d2ad-fb72-495d-953f-db42ab3e8872 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2025 , eprint=
Reference 25
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Observation 168fbcd5-01e3-4266-a2b7-3bd9f5f35ece · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails How Effective Is Constitutional
Reference 26
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Unavailable: canonical work link unavailable.
Observation 78455f52-0a7a-4d4b-9322-be3ba563e1c2 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails and Lee, Su-In , title =
Reference 27
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Unavailable: canonical work link unavailable.
Observation 7946530a-b7a4-4ec9-9245-66d88b5d043f · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Unresolved cited work
Reference 28
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Unavailable: canonical work link unavailable.
Observation 057402e3-23a1-463a-8b8a-ee67440dfac1 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails A Lightweight Explainable Guardrail for Prompt Safety
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 82820fad-4fc0-4810-b74f-18548072b1b3 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Safety Through Reasoning: An Empirical Study of Reasoning Guardrail Models
Reference 30
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9298491d-8af5-4135-a3ae-ef323f348575 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2025 , eprint=
Reference 31
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Observation 18eee0ce-992c-46bf-9c57-0d71d60ab61a · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails T hink G uard: Deliberative Slow Thinking Leads to Cautious Guardrails
Reference 32
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Observation 607d4dfe-8981-40e2-b709-2995b9194350 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails , title =
Reference 33
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Observation 55d8bd89-ac88-4608-8bdf-bd609ae38f3e · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails 2026 , eprint=
Reference 34
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Unavailable: canonical work link unavailable.
Observation 02561029-08a7-4ef5-bbbc-ca79dd6c9d0c · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails Faithfulness Tests for Natural Language Explanations
Reference 35
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Observation 548d26ad-aa2f-4f34-8d62-830fcb79cee9 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails ERASER : A Benchmark to Evaluate Rationalized NLP Models
Reference 36
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Observation fe2461f4-1f90-4baf-ad6e-d0f7f5362b64 · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails AEGIS 2.0: A Diverse AI Safety Dataset and Risks Taxonomy for Alignment of LLM Guardrails
Reference 37
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Observation 0709e7f2-f4fb-4d5b-a53e-fff1a26230de · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails T oxic C hat: Unveiling Hidden Challenges of Toxicity Detection in Real-World User- AI Conversation
Reference 38
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Observation c0d99aaa-b5a1-4b97-9ada-c2a961c70d6e · outbound
A Dual-Hypothesis Reasoning Framework for LLM Guardrails N e M o Guardrails: A Toolkit for Controllable and Safe LLM Applications with Programmable Rails
Reference 39
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No inbound Pith citation observations are available.