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Paper Citation Record · LEDGER

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation

As of 22 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2607.16828.

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

pith.paper-citation-record.v1
2607.16828 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T19:54:52.243491Z

measured 56 of 56 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

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Reference resolution

56 of 56 outbound references displayed

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Outbound references

Observation 22e7fabf-de88-4bc1-9627-0206e1340cb3 · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 1

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Observation 6c3e66a8-fdb2-4e25-982b-6bddda1b70e5 · outbound

This paper cites High-resolution image synthesis with latent diffusion models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation High-resolution image synthesis with latent diffusion models,

Reference 2

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Observation 61edda58-7823-48d3-858c-76afc4865b67 · outbound

This paper cites [Online].

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation [Online]

Reference 3

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Observation 796a753d-acc2-46d7-9198-8f127a19b9e0 · outbound

This paper cites Diffusion-based visual art creation: A survey and new perspectives,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Diffusion-based visual art creation: A survey and new perspectives,

Reference 4

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Observation 0b6a0480-1120-457a-8654-b1a2378548c7 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Photorealistic text-to-image diffusion models with deep language understanding,

Reference 5

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Observation 21d2f7ff-3eb9-49d1-93df-d0df32eef50b · outbound

This paper cites RoentGen: Vision-Language Foundation Model for Chest X-ray Generation.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation RoentGen: Vision-Language Foundation Model for Chest X-ray Generation

Reference 6

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Observation eb3a3f07-95f8-4e26-b968-21c4091be4ce · outbound

This paper cites Diffinfinite: Large mask-image synthesis via parallel random patch diffusion in histopathology,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Diffinfinite: Large mask-image synthesis via parallel random patch diffusion in histopathology,

Reference 7

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Observation dc15cda0-9467-454c-b5a2-84c0bf1224d4 · outbound

This paper cites Safe latent diffusion: Mitigating inappropriate degeneration in diffusion models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Safe latent diffusion: Mitigating inappropriate degeneration in diffusion models,

Reference 8

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source=pdf_text observed=2026-08-01T19:54:46.642395Z digest=sha256:a49899ccef6541485b2a63cd62469fcba24a1b3a19f2ab22a936e96969d87e18

Observation a87187c1-b828-4c17-9206-425628bc88df · outbound

This paper cites Unsafe diffusion: On the generation of unsafe images and hateful memes from text-to-image models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Unsafe diffusion: On the generation of unsafe images and hateful memes from text-to-image models,

Reference 9

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source=pdf_text observed=2026-08-01T19:54:46.779720Z digest=sha256:fddc6e0df401e4633d1f00015025c47947ce3d589e552de34f629bdfd881233c

Observation 8d4f6ff5-6282-4cd8-b0d6-629bfc859089 · outbound

This paper cites Sneakyprompt: Jail- breaking text-to-image generative models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Sneakyprompt: Jail- breaking text-to-image generative models,

Reference 10

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source=pdf_text observed=2026-08-01T19:54:46.884857Z digest=sha256:ec2d1a2bebba1cd20034a8be2bbb048f57307c0a9e4c416a6398b1e58dfd465d

Observation 62aff916-aad9-4a2b-a235-512f87536391 · outbound

This paper cites Safe-clip: Removing nsfw concepts from vision-and- language models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Safe-clip: Removing nsfw concepts from vision-and- language models,

Reference 11

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source=pdf_text observed=2026-08-01T19:54:46.962437Z digest=sha256:6124d6cb1ff2765972f0682787e722b17e004eb8e04208e86deec5c2eb956dbd

Observation 72e763c6-a561-49e7-9e90-96e38826bd4a · outbound

This paper cites Erasing concepts from diffusion models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Erasing concepts from diffusion models,

Reference 12

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source=pdf_text observed=2026-08-01T19:54:47.086271Z digest=sha256:24e27beb190c8e0af0a2292f15258d1889f0cf196cfa4e60d0c51494b31f627a

Observation d98b23fc-b403-498f-a3d4-aef187efd046 · outbound

This paper cites Receler: Reliable concept erasing of text-to-image diffusion models via lightweight erasers,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Receler: Reliable concept erasing of text-to-image diffusion models via lightweight erasers,

Reference 13

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source=pdf_text observed=2026-08-01T19:54:47.211965Z digest=sha256:982c0526217f845b3ca31de515c6286d0cb173d6c2a911f6fbffab4e8256eb28

Observation 5533bbc0-cad6-4972-9fec-b6841120a7d1 · outbound

This paper cites Unified concept editing in diffusion models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Unified concept editing in diffusion models,

Reference 14

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source=pdf_text observed=2026-08-01T19:54:47.292602Z digest=sha256:8ae9aa9621c127058477c04a89c8c34c0f0e1441b065c65aabd58d66c9010e9d

Observation 5a1216ee-25b5-4a08-bf31-473dc70015c7 · outbound

This paper cites Latent guard: a safety framework for text-to-image generation,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Latent guard: a safety framework for text-to-image generation,

Reference 15

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source=pdf_text observed=2026-08-01T19:54:47.391291Z digest=sha256:21881e39aa5356e3dae9c31a4962d160b0b10509fc8226d98a45ca0b5fc029a8

Observation 371643da-d1e0-4a6b-b248-7fb68d3c5358 · outbound

This paper cites Safety checker model card,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Safety checker model card,

Reference 16

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Observation 80f0b30a-8d36-426f-a75f-a9ade1565b50 · outbound

This paper cites SAFREE: Training-free and adaptive guard for safe text-to-image and video generation,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation SAFREE: Training-free and adaptive guard for safe text-to-image and video generation,

Reference 17

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Observation 743e9ff5-fefe-4a5f-80dc-ee505558cd1c · outbound

This paper cites Ring-a-bell! how reliable are concept removal methods for diffusion models?.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Ring-a-bell! how reliable are concept removal methods for diffusion models?

Reference 18

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Observation d01f48db-ad72-4fba-8c44-2b58cacffecb · outbound

This paper cites Prompting4debugging: Red-teaming text-to-image diffusion mod- els by finding problematic prompts,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Prompting4debugging: Red-teaming text-to-image diffusion mod- els by finding problematic prompts,

Reference 19

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source=pdf_text observed=2026-08-01T19:54:47.774482Z digest=sha256:6e9e55dcb1f827c3ee898d1f05d2656e77eddf6fc0a610b2e7f4c9890c5abcd8

Observation 2ad586f0-59ac-4dfb-b4a3-0de430f0c376 · outbound

This paper cites To generate or not? safety-driven unlearned diffusion models are still easy to generate unsafe images... for now,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation To generate or not? safety-driven unlearned diffusion models are still easy to generate unsafe images... for now,

Reference 20

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Observation 14019558-957b-4d11-8fc1-ee0731280f22 · outbound

This paper cites Initno: Boost- ing text-to-image diffusion models via initial noise optimization,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Initno: Boost- ing text-to-image diffusion models via initial noise optimization,

Reference 21

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Observation 70f265da-df26-4f40-a9e7-27003ce082af · outbound

This paper cites Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization

Reference 22

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Observation 87899827-953e-4eb9-8184-92288e5629e6 · outbound

This paper cites Good seed makes a good crop: Discovering secret seeds in text-to-image diffusion models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Good seed makes a good crop: Discovering secret seeds in text-to-image diffusion models,

Reference 23

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Observation e72a22f7-8e0b-471f-ba72-449b565728a2 · outbound

This paper cites The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise

Reference 24

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Observation fbfda0a4-464e-4123-9338-c6a35e8efca8 · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Scaling rectified flow transformers for high-resolution image synthesis,

Reference 25

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Observation f02d89b2-4dd4-47a8-951d-2679d3a130d9 · outbound

This paper cites Ndm: A noise-driven detection and mitigation framework against implicit sexual intentions in text-to-image generation,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Ndm: A noise-driven detection and mitigation framework against implicit sexual intentions in text-to-image generation,

Reference 26

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source=pdf_text observed=2026-08-01T19:54:48.619740Z digest=sha256:1c8be76bc8361382164f8df55bec9b7cd8f50b5ab3090c8b5ea4e94a1a45c452

Observation c5dfd547-7ba7-418b-9a88-af1603a0d045 · outbound

This paper cites Zero-shot text-to-image generation,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Zero-shot text-to-image generation,

Reference 27

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Observation cac163c8-7dd9-4ff2-8821-2a11cbf89910 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Learning transferable visual models from natural language supervision,

Reference 28

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Observation 87de1098-e955-4293-b68d-0bf809120d13 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 29

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Observation 3dcfb2df-5540-4b02-a78c-f6130237e688 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 30

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Observation 16809aaf-3785-4167-bd65-0c811ce88711 · outbound

This paper cites Multitrust: A comprehensive benchmark towards trustworthy multimodal large language mod- els,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Multitrust: A comprehensive benchmark towards trustworthy multimodal large language mod- els,

Reference 31

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source=pdf_text observed=2026-08-01T19:54:49.341774Z digest=sha256:e39a2fc5be3d2f5070ad9797e0facb890c82b72cb80609b1eb0fddc019f6e7c8

Observation 866ab451-92cd-4a42-b13e-b4916bebe97b · outbound

This paper cites MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models

Reference 32

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Observation dd471972-0eca-473a-822e-de137becc5eb · outbound

This paper cites Perception-guided jailbreak against text-to-image models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Perception-guided jailbreak against text-to-image models,

Reference 33

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Observation b2b4569a-78f9-4d5a-aac6-24df9bff1386 · outbound

This paper cites Gradbias: Unveiling word influence on bias in text-to-image generative models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Gradbias: Unveiling word influence on bias in text-to-image generative models,

Reference 34

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Observation 8bd59da1-35f2-4817-9731-bbbaa9e00fcd · outbound

This paper cites T2i- compbench++: An enhanced and comprehensive benchmark for compositional text-to-image generation,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation T2i- compbench++: An enhanced and comprehensive benchmark for compositional text-to-image generation,

Reference 35

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source=pdf_text observed=2026-08-01T19:54:49.825499Z digest=sha256:1aa008f21e85be12210946f590e6c0ccff79dbe0ec9790066713b439eb630be4

Observation 00634c13-2cca-4de9-a60c-9a698ae7342d · outbound

This paper cites Unified prompt attack against text-to-image generation models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Unified prompt attack against text-to-image generation models,

Reference 36

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source=pdf_text observed=2026-08-01T19:54:49.968465Z digest=sha256:7edfda78eabd68636cbbb42880377ca8af99f229656fedd79027ecc798729428

Observation 5b47f5ba-22d2-43e7-91d0-2bb4093fd357 · outbound

This paper cites Breaking the Ceiling: Exploring the Potential of Jailbreak Attacks through Expanding Strategy Space.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Breaking the Ceiling: Exploring the Potential of Jailbreak Attacks through Expanding Strategy Space

Reference 37

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source=pdf_text observed=2026-08-01T19:54:50.100594Z digest=sha256:a4f1758750f51e839ae250582a6d8954b8b51d83dbf6bc82a314196243754c6b

Observation 79f3d8fb-9f6a-480e-81f2-cb097cf43b26 · outbound

This paper cites How johnny can persuade llms to jailbreak them: Rethinking persuasion to challenge ai safety by humanizing llms,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation How johnny can persuade llms to jailbreak them: Rethinking persuasion to challenge ai safety by humanizing llms,

Reference 38

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source=pdf_text observed=2026-08-01T19:54:50.308695Z digest=sha256:6f9a751fd31f43e4f519cc7261010841e5ff889162f8433a9780c743404a2c29

Observation 289570de-a098-4e6b-9781-b27c5446786e · outbound

This paper cites Mma- diffusion: Multimodal attack on diffusion models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Mma- diffusion: Multimodal attack on diffusion models,

Reference 39

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source=pdf_text observed=2026-08-01T19:54:50.517766Z digest=sha256:6390f26737248cd16c3933db1c9eb6443223e29ff3335d04e6a2c056c4967aa1

Observation e0d78c40-82d5-4c44-a082-c3791886dd1b · outbound

This paper cites Reliable and efficient concept erasure of text-to-image diffusion models,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Reliable and efficient concept erasure of text-to-image diffusion models,

Reference 40

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source=pdf_text observed=2026-08-01T19:54:50.650160Z digest=sha256:bef31a90bd7885c2d74d6eacf6cdcdab0008b94e9d2bb01cc892b91e6386891d

Observation 23bae597-39d9-4574-8d18-40945464167d · outbound

This paper cites Towards nsfw-free text-to-image generation via safety-constraint direct preference optimization,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Towards nsfw-free text-to-image generation via safety-constraint direct preference optimization,

Reference 41

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source=pdf_text observed=2026-08-01T19:54:50.833762Z digest=sha256:87b2283d8ebe8eca0a5191c9eef0992acc658f01242a538ab695967f64202171

Observation 5fc8dd78-9952-4649-8b82-53e44f94b753 · outbound

This paper cites AlignGuard: Scalable Safety Alignment for Text-to-Image Generation.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation AlignGuard: Scalable Safety Alignment for Text-to-Image Generation

Reference 42

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source=pdf_text observed=2026-08-01T19:54:50.939159Z digest=sha256:7e8bebc788b8f9060eadee6a54328120ed246ff59457b09031834ec75797ec04

Observation 06e04a08-3018-42c7-b4b1-24e4414d85e3 · outbound

This paper cites STAIR: Improving Safety Alignment with Introspective Reasoning.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation STAIR: Improving Safety Alignment with Introspective Reasoning

Reference 43

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source=pdf_text observed=2026-08-01T19:54:51.025596Z digest=sha256:e8c3edc0554e587716060474e231d01b8fb9a2d1d52ab9ad3c7618b1738c758f

Observation 3d2a549f-728a-455a-92c4-2e0d9ab69cbb · outbound

This paper cites RealSafe-R1: Safety-Aligned DeepSeek-R1 without Compromising Reasoning Capability.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation RealSafe-R1: Safety-Aligned DeepSeek-R1 without Compromising Reasoning Capability

Reference 44

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source=pdf_text observed=2026-08-01T19:54:51.100764Z digest=sha256:90950210764def098b614a30613dc797a01ccfa47f111ee0474e7f4b41b6a45f

Observation f0752bb4-1820-4dd6-8052-c70ff58d16eb · outbound

This paper cites Classifier-Free Diffusion Guidance.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Classifier-Free Diffusion Guidance

Reference 45

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source=pdf_text observed=2026-08-01T19:54:51.178213Z digest=sha256:5e68f5b49c94f3e54016bdf5dec4e46017fac837639fda2fe6712bebd90850f7

Observation a44e352b-31ed-411c-8d23-4ad9820d159b · outbound

This paper cites Microsoft coco: Common objects in context,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Microsoft coco: Common objects in context,

Reference 46

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source=pdf_text observed=2026-08-01T19:54:51.263766Z digest=sha256:8eaf2875118647e243bbb0652d9d1ae9ddc642db9bcb5747237c90e7959b0009

Observation 1b81b50d-6453-4566-93b9-fed0bbc32f0d · outbound

This paper cites Visualizing data using t-sne.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Visualizing data using t-sne

Reference 47

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source=pdf_text observed=2026-08-01T19:54:51.366278Z digest=sha256:1b99f74d8effa63ac9a5a94905a1412d869551c3877ee776501a8b7291d9cfac

Observation 724084fc-a5ae-4daf-9d0b-fcd69b5a5a0c · outbound

This paper cites A threshold selection method from gray-level histograms,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation A threshold selection method from gray-level histograms,

Reference 48

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source=pdf_text observed=2026-08-01T19:54:51.524070Z digest=sha256:d96d959e066833d7451ed5d52b8d2e338b727a92be2b5116df89b381a0f14883

Observation 66afe38c-c1d6-42aa-8c1a-2f9770b5ed0b · outbound

This paper cites Latent Space Disentanglement in Diffusion Transformers Enables Precise Zero-shot Semantic Editing.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Latent Space Disentanglement in Diffusion Transformers Enables Precise Zero-shot Semantic Editing

Reference 49

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source=pdf_text observed=2026-08-01T19:54:51.655341Z digest=sha256:fc848ab54623204ee2ec4e883886e54190d476c719fa3b394a36e6df2ad1f582

Observation 0b7995e0-b47a-49db-9eae-d2edb382b89c · outbound

This paper cites CLIPScore: A Reference-free Evaluation Metric for Image Captioning.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 50

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source=pdf_text observed=2026-08-01T19:54:51.754971Z digest=sha256:a5f44eba87477da777fc5a55a382243e7163363a297c5a1311467b352f88b6ea

Observation 50b18a0b-f5d5-484c-856d-b529a03cce22 · outbound

This paper cites distilroberta-nsfw-prompt-stable- diffusion,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation distilroberta-nsfw-prompt-stable- diffusion,

Reference 51

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source=pdf_text observed=2026-08-01T19:54:51.815402Z digest=sha256:649457205b78dca39b3dae9018c193547bbdd7b0a0c74ca1addab15faaea5492

Observation f2f498da-089b-4efc-8f38-c5204747d016 · outbound

This paper cites GPT-4 Technical Report.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation GPT-4 Technical Report

Reference 52

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source=pdf_text observed=2026-08-01T19:54:51.898800Z digest=sha256:50fda5b2adeba7c4b0f9b276b21ec060231a2d20a8ce12701354067efd1f366b

Observation 31c45b51-4eb1-4118-8536-1a0550fc3096 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation BERTScore: Evaluating Text Generation with BERT

Reference 53

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source=pdf_text observed=2026-08-01T19:54:52.003152Z digest=sha256:f5e7e163835fafee9f200cd60b4fa49b1a610dd5d718816313d35e7b61c1c0c0

Observation 05acb3d9-3eb8-44ae-b66e-21d889cb909c · outbound

This paper cites Nudenet: Neural nets for nudity classification, detec- tion and selective censoring,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Nudenet: Neural nets for nudity classification, detec- tion and selective censoring,

Reference 54

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source=pdf_text observed=2026-08-01T19:54:52.090935Z digest=sha256:1637e921348a6ff1df482a797bd4bf7fdde0588592a4b4cf9248f2da96461dde

Observation c75754cf-b864-4c0b-9278-e9d0e55265a0 · outbound

This paper cites Nsfw image detection,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Nsfw image detection,

Reference 55

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source=pdf_text observed=2026-08-01T19:54:52.181888Z digest=sha256:ce6ac70a0e3d4c5869df8096ab91df8c1abe270c3bf0e07017c314470a96db0a

Observation b6a30062-d7bf-48af-8371-a6e82d12daba · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium,.

UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation Gans trained by a two time-scale update rule converge to a local nash equilibrium,

Reference 56

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source=pdf_text observed=2026-08-01T19:54:52.243491Z digest=sha256:b5b980cddd0ae394e936a8bdad3d37fdad0785c922160a5687c6f67e099608c9

Pith citing papers

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