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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 11 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 2026-08-11T06:34:44.6726+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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source=pdf_text observed=2026-08-01T19:54:46.498621Z digest=sha256:eca6eeddeebe108e43127683ac1715447f98131d20170fe1c1e02c00de573811

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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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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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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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=sha256:1a56d7a66e069017fb9f26d1c77e189583bdaa43ba3834adc2b1725a7f6a0ee1

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=sha256:46ecb8e61340946b73f736ca0b33ddcd0550dd69ba534d997e1770b2e8dd463f

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:e90da8dd4a9ec2d6e8b63d4df5c7590edf929d96fd17cc90936741f884e7cbde

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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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=sha256:1ff998d42e870254427dfad6e9099000b915d76d1b4f4cbab013f2c5b1a0151d

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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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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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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source=pdf_text observed=2026-08-01T19:54:49.185462Z digest=sha256:314b826dc96d5a8ea3d6818329f7e15be9955f1fe8ebd2781a91e06565d8102c

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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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=sha256:1d6708f282e1aac1bdaa4d0c5a4842a0c05a8cd1c502ecc79223804209c807ea

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=sha256:31336a7aee2c3a6266b1f5800b9ba688eedf1022df4b66480bf07f8e367876f0

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=sha256:6c41e104494a6884688409db2dc5ce242fcabc03afdf83a672dbbe54630c5066

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=sha256:8d2d74421ada910f28095085a1ab06c6819506547e502e583914b60817fd6065

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=sha256:252f928062cbdd5eba440a81e13f104a342ada30a3b64ab01350e9d025be2013

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:eb4a428076b0edafb8571676ee801f56fb54abefd61af9869b668415774b158e

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:df43e44ba80ec53c490b2fb13bbfa8fe5438f8bce4da596852c06dbf3f607dab

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:fff16d0ad4bc2a3d0959c9019f21e2777616c8f2f58e6c65b38d93f4b470565f

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=sha256:32a4b25364c7e9f0b11470bd5f98245af403384a23262e9d516d331c757285eb

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=sha256:570fcc96d41b4d185c17502ec32312b68a04735d37670f05c1d3ea639bd70ba5

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:b74ee280c8b7037d6bb4ae0b53accede010a29a7555837cc0f13e8939f069274

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:f1faa655d05716aa872e8bd255cb17c4b10711d7ab2591bb620ad24a7838037a

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=sha256:06cbdd09fdb079be20a6299b4ca8a15e45690ee4086281b656289ec433690528

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=sha256:29ef2982f4e9adf56e5087be10cc4a4a619fc39a5d48a608731937a16536ebfd

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=sha256:0c5d279ebee1380d37cc8160df737b9468871519df95fc396ef7f4772c1619a6

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:a39b871d02e8a4a7b39090b9ee2083b6ff2f0a4553fa5741ec9eee258cee2d1b

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=sha256:63c4997171b1471c2ddce29e8390d3178ff2c2a053f62a7989bae0597d2545f6

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=sha256:6babd30cbe3e912d0f1b0c2c0342e4ef00324a3962988c9aa0835ca687a09f25

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=sha256:489d016195b20714ffea56199a665461a80db899d63690aad2978776a3fadb4f

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=sha256:6d03a339122413542b9e4d64d5db40fd0eae123c6ba56fdd0e48e52fb388986b

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:ea63ac587917e86a3c1b9d856fab903f2e110103f30261262b4917823884c040

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=sha256:06bf3ce800e14c36727c9c4266478fb2b02b210d5999c55a408c08f7c69d6874

Pith citing papers

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