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Paper Citation Record · LEDGER

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis

As of 18 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 5 inbound Pith citation observations for arXiv:2505.23325.

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

pith.paper-citation-record.v1
2505.23325 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:53:31.813629Z

measured 75 of 75 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:26:55.937172Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T18:17:55.110392Z

Reference resolution

70 of 70 outbound references displayed

  • verified exact0
  • verified fuzzy12
  • unresolved58
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aa8afa44-c11e-446f-8359-af55d0281a4d · outbound

This paper cites Qwen2.5-VL Technical Report.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Qwen2.5-VL Technical Report

Reference 1

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source=pdf_text observed=2026-08-07T12:53:22.515728Z digest=sha256:4eeb0523ac1d13799be4b3ff6e6301e2366d7f163851184c8ad0d1d38b70a85c

Observation 4fbbbc7a-2890-4382-b60f-0c5599f64eba · outbound

This paper cites Video generation models as world simulators.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Video generation models as world simulators

Reference 2

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source=pdf_text observed=2026-08-07T12:53:22.623707Z digest=sha256:2060ddf734791bea069773a5f0256c17528572001086b02aca8f1c8aaf31c71c

Observation 3b1dda67-0a37-443f-b596-5aa667624430 · outbound

This paper cites Emerging Properties in Self-Supervised Vision Transformers.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Emerging Properties in Self-Supervised Vision Transformers

Reference 3

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source=pdf_text observed=2026-08-07T12:53:22.800605Z digest=sha256:a00767f8be7492c2598f35379d6d1ae4629ed7176dcc6f1eccd0f6332cd5505e

Observation 167968c9-5e1d-43ba-b228-924fa750ea1b · outbound

This paper cites Pre-Trained Image Processing Transformer.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Pre-Trained Image Processing Transformer

Reference 4

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source=pdf_text observed=2026-08-07T12:53:22.896819Z digest=sha256:210b08280c9d9ea7135720178b1b50f99ec00a2afcd2909e588607cafc2f80c9

Observation 0988faea-3c00-4d54-97a6-0e75efb97c5c · outbound

This paper cites Re-Imagen: Retrieval-Augmented Text-to-Image Generator.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Re-Imagen: Retrieval-Augmented Text-to-Image Generator

Reference 5

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source=pdf_text observed=2026-08-07T12:53:23.012175Z digest=sha256:f479df7c799d977a915fb0f61e42800bec6cd70135118cfc19a6333c7ca5f97d

Observation 76dcc915-2829-404a-b84d-1a6bc0d21485 · outbound

This paper cites Anydoor: Zero-shot object-level image customization.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Anydoor: Zero-shot object-level image customization

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-07T12:53:36.274483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:23.149714Z digest=sha256:aaabf4c6c0f18e61e5ef9693539fedd5c628ce748687d389e134bc3f0e2f19b2

Observation 12f96487-8b01-4c9b-b8f7-051b18b6d64f · outbound

This paper cites Unireal: Universal image generation and editing via learning real-world dynamics, 2024.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Unireal: Universal image generation and editing via learning real-world dynamics, 2024

Reference 7

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raw_fallback, observed 2026-08-07T12:53:35.936652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:23.281171Z digest=sha256:669d404cf731efa615860f81541a3e0644ff581e4170c09de7fa3f4ba52f2aa7

Observation c2b4f917-7ab4-4834-ba56-c5a50cc25435 · outbound

This paper cites Xtuner: A toolkit for efficiently fine-tuning llm.https://github.com/InternLM/ xtuner, 2023.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Xtuner: A toolkit for efficiently fine-tuning llm.https://github.com/InternLM/ xtuner, 2023

Reference 8

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source=pdf_text observed=2026-08-07T12:53:23.378665Z digest=sha256:2cd51dfc1e3459ddfb734095f9b3a8aa0bf5b96705c9065e822e3a9591cae34d

Observation 0d6a55c5-639e-4ad7-981f-4886edef6c9c · outbound

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

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Scaling rectified flow transformers for high-resolution image synthesis

Reference 9

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source=pdf_text observed=2026-08-07T12:53:23.483328Z digest=sha256:5ada8a9c762fc06a03d579cb5c97c561223aa0e8c512c60a3a24e427e53edd99

Observation b5308a94-bedf-42c6-bce1-5c692b91b15a · outbound

This paper cites Ranni: Taming text-to-image diffusion for accurate instruction following.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Ranni: Taming text-to-image diffusion for accurate instruction following

Reference 10

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source=pdf_text observed=2026-08-07T12:53:23.547205Z digest=sha256:b7e6c4a80ccd0d9ab6343432f49f842282bb7abfee61ee187fc8f6f481c0f49e

Observation cc51d835-1194-4856-ba3d-b9d11ef70b68 · outbound

This paper cites Bermano, Gal Chechik, and Daniel Cohen-Or.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Bermano, Gal Chechik, and Daniel Cohen-Or

Reference 11

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:23.639105Z digest=sha256:b6b299f8adb5c2cf4dab528ffecb654967abc2176c6071abe2278feec542a04c

Observation 82d05adb-55ee-4fea-b681-a7db3846a309 · outbound

This paper cites ACE: All-round Creator and Editor Following Instructions via Diffusion Transformer.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis ACE: All-round Creator and Editor Following Instructions via Diffusion Transformer

Reference 12

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source=pdf_text observed=2026-08-07T12:53:23.885001Z digest=sha256:477b33a06409e297e28d9e0b5b3d8e8558a79e1932b245097c207829da053227

Observation e6da8599-da65-4d05-b483-5aefd3094d0c · outbound

This paper cites GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

Reference 13

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source=pdf_text observed=2026-08-07T12:53:24.079442Z digest=sha256:422935f4db7cab963c1ee80822448b2d5bd1b4fb9c7f09139b1f00be3c298482

Observation d808e0ff-e324-4900-9bfe-45d038270315 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis LoRA: Low-Rank Adaptation of Large Language Models

Reference 14

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source=pdf_text observed=2026-08-07T12:53:24.253804Z digest=sha256:f5557c7a2839d2ed8b7e238e4e4a1e8aab621da0a08ce891c915b20f5c4cee7a

Observation 50e0b927-0d49-4166-8d47-258b819aa63a · outbound

This paper cites Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation

Reference 15

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source=pdf_text observed=2026-08-07T12:53:24.429433Z digest=sha256:13e5c572f9c8d596f1dfdc8f9444771dc0e2c68fcd62d436dad90f111e9145be

Observation a0f5eae7-47d0-46a1-bd50-8a90cc09322a · outbound

This paper cites DreamTuner: Single Image is Enough for Subject-Driven Generation.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis DreamTuner: Single Image is Enough for Subject-Driven Generation

Reference 16

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source=pdf_text observed=2026-08-07T12:53:24.588321Z digest=sha256:a07840791c89862b5c3093500567813ef8a527ac7050447133e1a5f68a6e6294

Observation b090f925-359c-49f5-bce4-e171ac7f2953 · outbound

This paper cites In-Context LoRA for Diffusion Transformers.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis In-Context LoRA for Diffusion Transformers

Reference 17

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source=pdf_text observed=2026-08-07T12:53:24.694788Z digest=sha256:348e26e664de6b781d1625088d733ff17684d3b7cf110558a950d72edab72f24

Observation 6fa9346b-0b09-4bb1-b965-7c95fa785143 · outbound

This paper cites FlexIP: Dynamic Control of Preservation and Personality for Customized Image Generation.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis FlexIP: Dynamic Control of Preservation and Personality for Customized Image Generation

Reference 18

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source=pdf_text observed=2026-08-07T12:53:24.822634Z digest=sha256:4f780bdc1024f01ec5fd057b267b024a3df8fa3811e0e43703cc07e93fc7ce84

Observation 57620f91-928c-473d-9ca4-898dcfdb13ee · outbound

This paper cites Image-to-Image Translation with Conditional Adversarial Networks.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Image-to-Image Translation with Conditional Adversarial Networks

Reference 19

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source=pdf_text observed=2026-08-07T12:53:25.018774Z digest=sha256:28643b91ddd3ffc32b9d44f3db63bdc44b6a1e491a237d3169fc921e12c964a0

Observation 83fe5650-905d-4252-8dec-ed2f9530e1c4 · outbound

This paper cites Hunyuanvideo: A systematic framework for large video generative models,.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Hunyuanvideo: A systematic framework for large video generative models,

Reference 20

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source=pdf_text observed=2026-08-07T12:53:25.201902Z digest=sha256:d3e99afadc3961398b6f46903f19e1d5e73013265f05eb13838a5e31502116c7

Observation e006d9ce-ad44-4edf-863e-d7c0ac6451a5 · outbound

This paper cites Multi-Concept Customization of Text-to-Image Diffusion.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Multi-Concept Customization of Text-to-Image Diffusion

Reference 21

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source=pdf_text observed=2026-08-07T12:53:25.463468Z digest=sha256:d3d415f8e4dfb77b112935eab90f722f4267a945e48615802af5f91907a7f402

Observation 97659b9e-6620-4a7c-bf85-13c747931b93 · outbound

This paper cites Generating multi-image synthetic data for text-to-image customization, 2025.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Generating multi-image synthetic data for text-to-image customization, 2025

Reference 22

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source=pdf_text observed=2026-08-07T12:53:25.597628Z digest=sha256:e4b59b49402fb842006dd8a4f38dfa0d5c6898c620f687f3ce5a93f64fe59cae

Observation 58320eb3-87f3-401e-abd8-53fd391b51d7 · outbound

This paper cites an unresolved cited work.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Unresolved cited work

Reference 23

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source=pdf_text observed=2026-08-07T12:53:25.728120Z digest=sha256:00c1e122e7223dc64cd069fc95ad5e72f0df79ceed764ac1095bdaf4b950b4f8

Observation 4051e177-1810-428a-be08-a22d2a7e6297 · outbound

This paper cites BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing

Reference 24

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source=pdf_text observed=2026-08-07T12:53:25.799515Z digest=sha256:e1d85a9085d3433036940603814be0ec047e3f7b45df93041b5dbde81ef4a761

Observation de67ca17-d3b0-44f3-abab-56e439259247 · outbound

This paper cites Visualcloze: A universal image generation framework via visual in-context learning, 2025.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Visualcloze: A universal image generation framework via visual in-context learning, 2025

Reference 25

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source=pdf_text observed=2026-08-07T12:53:25.866127Z digest=sha256:554c9b0e6a74fbb987f75f6db8c6d66c4faaa38f6648e3f6e3736dbbb638f90d

Observation b144fdba-022b-44ad-88d1-baf77a4adf03 · outbound

This paper cites Microsoft COCO: Common Objects in Context.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Microsoft COCO: Common Objects in Context

Reference 26

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source=pdf_text observed=2026-08-07T12:53:25.933812Z digest=sha256:c678edc4945d31b703c4e1452edab2317d20c7f2d97043cf47eef3e4f0a879cd

Observation eebb71da-e1a6-4206-b3ba-b6d7b67678fd · outbound

This paper cites RealGeneral: Unifying Visual Generation via Temporal In-Context Learning with Video Models.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis RealGeneral: Unifying Visual Generation via Temporal In-Context Learning with Video Models

Reference 27

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source=pdf_text observed=2026-08-07T12:53:26.025517Z digest=sha256:ad0957bdbb1b142c599c44ca60999af77524222c423c3122d6c5e23f8ea5c2f3

Observation e0620991-1c15-45b6-8649-4e0a28f0d78b · outbound

This paper cites Flow Matching for Generative Modeling.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Flow Matching for Generative Modeling

Reference 28

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source=pdf_text observed=2026-08-07T12:53:26.123096Z digest=sha256:c451ca5fb9cf619ab35e6e09fe1b6a35eaa817ceb94e620cfe871b92c48e5445

Observation 0d1a92ec-5ef3-4e2e-a830-0fc4e02045dd · outbound

This paper cites ACE++: Instruction-Based Image Creation and Editing via Context-Aware Content Filling.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis ACE++: Instruction-Based Image Creation and Editing via Context-Aware Content Filling

Reference 29

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source=pdf_text observed=2026-08-07T12:53:26.248424Z digest=sha256:67348bb42d922b989ab2e67384c838ae07c7fcca39f1f68fc4165def10027e41

Observation 52d2831d-ae13-4cb0-9654-7ee95a727e21 · outbound

This paper cites SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations

Reference 30

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source=pdf_text observed=2026-08-07T12:53:26.366072Z digest=sha256:feba359bea118f71f70fcb2aee7336d969b780fffa6073abfc10e1800790951f

Observation e0b4540d-d307-4163-8434-ca7fdbc89f5f · outbound

This paper cites T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models,.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models,

Reference 31

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raw_fallback, observed 2026-08-07T12:53:35.336112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:26.460823Z digest=sha256:06f17ffa791f4b637a984f9086cc367dff2db08fefb63050034bbea8077b70b2

Observation cc656117-7b64-4218-8591-8b5265798ce8 · outbound

This paper cites Kosmos-g: Generating images in context with multimodal large language models, 2024.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Kosmos-g: Generating images in context with multimodal large language models, 2024

Reference 32

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raw_fallback, observed 2026-08-07T12:53:35.101862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:26.689467Z digest=sha256:89c02416e600e91a71fea629a5c35ac6513add479671addd266a569f8d1cb4d5

Observation 243f49b9-f87a-46c2-afe4-94728d64eef4 · outbound

This paper cites Scalable Diffusion Models with Transformers.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Scalable Diffusion Models with Transformers

Reference 33

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source=pdf_text observed=2026-08-07T12:53:26.850329Z digest=sha256:d8d45b80ef292d1ed867e11db7df049dc1f1ff62e6f02e6e31c835de8d98072a

Observation 6e9d63c4-de91-4ab4-8fc4-1e3fe876fdc7 · outbound

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

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 34

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source=pdf_text observed=2026-08-07T12:53:26.972678Z digest=sha256:b092f1b0345b9bd9b8d592dd18b7f90678f67ca224875ea30a9e6c7f56bbe0b7

Observation 86f62b77-0205-4070-b02f-890ed7daf412 · outbound

This paper cites BootPIG: Bootstrapping Zero-shot Personalized Image Generation Capabilities in Pretrained Diffusion Models.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis BootPIG: Bootstrapping Zero-shot Personalized Image Generation Capabilities in Pretrained Diffusion Models

Reference 35

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source=pdf_text observed=2026-08-07T12:53:27.096830Z digest=sha256:9ce657ec266b4422c9f0a078559bff512aaa9a9d84692fe6bcfee520011d54ba

Observation 7a3873b5-8789-4556-9a85-19ba4b7cf5ab · outbound

This paper cites UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild

Reference 36

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source=pdf_text observed=2026-08-07T12:53:27.194331Z digest=sha256:268d3d605186fbe4b2d54f258ef3203f2de7170aea17e363565f74751427840f

Observation 51750bf5-8cc0-4955-9a6a-21315693b1d3 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Learning Transferable Visual Models From Natural Language Supervision

Reference 37

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source=pdf_text observed=2026-08-07T12:53:27.273796Z digest=sha256:c0bd282a8e7bf9a5efe94220b91fb3aabb487055ad02cb8cbfaaf4fece79a982

Observation 2bed482b-d625-492f-aab4-92a292a9fcd9 · outbound

This paper cites High-Resolution Image Synthesis with Latent Diffusion Models.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis High-Resolution Image Synthesis with Latent Diffusion Models

Reference 38

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source=pdf_text observed=2026-08-07T12:53:27.441730Z digest=sha256:d138cbb13025ecf03cbc798a7055899676b11e384558b09e251afc50e81416a6

Observation 53d177e7-c07a-43cb-a859-9773f44859a2 · outbound

This paper cites Pathways on the image manifold: Image editing via video generation, 2025.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Pathways on the image manifold: Image editing via video generation, 2025

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-07T12:53:34.839305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:27.519189Z digest=sha256:6b9938894079c030c7f03f5eb1d43504353658a4f399737545d528ca14960a03

Observation 0912837b-7be2-4506-9683-7809e2b7c9c2 · outbound

This paper cites DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation

Reference 40

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source=pdf_text observed=2026-08-07T12:53:27.573672Z digest=sha256:c47cf6d80cc334646acbef18ba0c51bd648deefb4119612e0a55432ef45c0722

Observation aa974bee-d64e-4d0a-9454-dd74708d3f55 · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 41

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source=pdf_text observed=2026-08-07T12:53:27.658040Z digest=sha256:e57291e478d56aed3a2e568727b890038ffab9d757fcdb77e4cd30555ef93f17

Observation 2e646a31-dff3-4317-92b8-7540b0931263 · outbound

This paper cites OutfitAnyone: Ultra-high Quality Virtual Try-On for Any Clothing and Any Person.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis OutfitAnyone: Ultra-high Quality Virtual Try-On for Any Clothing and Any Person

Reference 42

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source=pdf_text observed=2026-08-07T12:53:27.768065Z digest=sha256:f79808480236ca9604709168d2e29b31d553128832bf8140774758d585c5d82b

Observation 9bf47773-36cb-4c04-9e88-52b751623f84 · outbound

This paper cites OminiControl: Minimal and Universal Control for Diffusion Transformer.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis OminiControl: Minimal and Universal Control for Diffusion Transformer

Reference 43

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source=pdf_text observed=2026-08-07T12:53:27.889742Z digest=sha256:17960fd5507571b1de393dba1d1d0bb407cc6d71d01770ce98c6c50d694a1cc9

Observation 9520d78b-51aa-498f-88b2-da9757dfdd97 · outbound

This paper cites Emo: Emote portrait alive generating expressive portrait videos with audio2video diffusion model under weak conditions.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Emo: Emote portrait alive generating expressive portrait videos with audio2video diffusion model under weak conditions

Reference 44

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source=pdf_text observed=2026-08-07T12:53:27.963363Z digest=sha256:8f12bdfd84bcb0bf013eebc4bcd737a676984cdca2ac0b9530725f950f4c6002

Observation 3e20c2e0-2596-4a38-843b-847fc8d1698f · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Wan: Open and Advanced Large-Scale Video Generative Models

Reference 45

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source=pdf_text observed=2026-08-07T12:53:28.089019Z digest=sha256:a716145873d19e20f27068c7cdb801008877d709c57e7d84b16d3a93b0a5fea7

Observation 35f5ae99-6e02-40e4-bc21-64cd33791876 · outbound

This paper cites MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance

Reference 46

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source=pdf_text observed=2026-08-07T12:53:28.265120Z digest=sha256:9231add5aefb68c64f00c891ba451d1b444ba092af17c37d4941db75575010cf

Observation 3ef60ca9-376e-400d-a205-e319dc938c54 · outbound

This paper cites Images Speak in Images: A Generalist Painter for In-Context Visual Learning.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Images Speak in Images: A Generalist Painter for In-Context Visual Learning

Reference 47

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source=pdf_text observed=2026-08-07T12:53:28.364742Z digest=sha256:5ac938058c8a4380ef996786b0395a8653dfb7b648e6b26064a8893eb5de33d2

Observation 02e4607b-721c-426e-87a0-692699a9a502 · outbound

This paper cites Bovik, H.R.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Bovik, H.R

Reference 48

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source=pdf_text observed=2026-08-07T12:53:28.459005Z digest=sha256:8c351c7169143abc58485e63e10f59bee0941c8f631a2a779ed60929324c15b1

Observation 648dc1a1-1a9c-4e34-9a3f-2583a7f3dbe5 · outbound

This paper cites ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation

Reference 49

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source=pdf_text observed=2026-08-07T12:53:28.602302Z digest=sha256:406272b555492c6f7f70018919f29f7ebb50041af41fddb750e15a5d89e33940

Observation 320137bf-3f49-434a-a5a4-e127f3e0da13 · outbound

This paper cites Less-to-More Generalization: Unlocking More Controllability by In-Context Generation.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

Reference 50

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source=pdf_text observed=2026-08-07T12:53:29.227782Z digest=sha256:dbdc0555740e555e4fa44e5674806166139408f99644886c8e73052ba0474ec6

Observation 9ac4c8ac-ae23-4bdc-bb24-02da617503d2 · outbound

This paper cites OmniGen: Unified Image Generation.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis OmniGen: Unified Image Generation

Reference 51

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source=pdf_text observed=2026-08-07T12:53:29.727336Z digest=sha256:3c2ab9dbbffc25957b0e15d8adfd6043742152cb9dca67fcb5d185c5cd5ac3d5

Observation 46656ce4-947e-4829-a277-9ea6f2663364 · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data, 2024.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Depth anything: Unleashing the power of large-scale unlabeled data, 2024

Reference 52

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raw_fallback, observed 2026-08-07T12:53:34.560875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:29.934326Z digest=sha256:9da47cdc2eb932ed60be9a1d6ff18e4250061066f24f919ddd6118f2674c3ff9

Observation 9ffd1d01-3d5c-4119-83eb-20b794d517b2 · outbound

This paper cites Cogvideox: Text-to-video diffusion models with an expert transformer,.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Cogvideox: Text-to-video diffusion models with an expert transformer,

Reference 53

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raw_fallback, observed 2026-08-07T12:53:34.394259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:29.975109Z digest=sha256:a09924ac5e1fc4ae02d9b4198be18ef036ede35438131d3f0113f610b816d8d8

Observation 7e3fc520-b9d8-428b-9b0c-28d2492af878 · outbound

This paper cites IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Reference 54

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source=pdf_text observed=2026-08-07T12:53:30.237475Z digest=sha256:0493be02a872d9016e6a4c89921b5dd504cdd0ef4c07aa00b2b020b4a5b460f5

Observation bfb670ce-16c0-4764-904c-1859e2507857 · outbound

This paper cites ObjectMover: Generative Object Movement with Video Prior.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis ObjectMover: Generative Object Movement with Video Prior

Reference 55

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source=pdf_text observed=2026-08-07T12:53:30.408952Z digest=sha256:c5934845ab901b88070f3de1e08b14445bdf00544cbf8139fc8146f1a10efe49

Observation d2c46835-2ba1-4c49-be0d-83e2a74603b0 · outbound

This paper cites JeDi: Joint-Image Diffusion Models for Finetuning-Free Personalized Text-to-Image Generation.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis JeDi: Joint-Image Diffusion Models for Finetuning-Free Personalized Text-to-Image Generation

Reference 56

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source=pdf_text observed=2026-08-07T12:53:30.525808Z digest=sha256:52622f48b64c25ff2befa360b024d19126c89e31d9d5032eb6339bcb5721f008

Observation 34811bf5-c029-4d39-b90d-26e15c5fe086 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 57

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source=pdf_text observed=2026-08-07T12:53:30.136888Z digest=sha256:57eb5edbadc5983599625392e372385f4232632817bc98b55bdc4eaff18cfd31

Observation 52e12105-c447-46b7-9ad0-6f3318182959 · outbound

This paper cites Adding Conditional Control to Text-to-Image Diffusion Models.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Adding Conditional Control to Text-to-Image Diffusion Models

Reference 58

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no resolver link, observed 2026-08-07T12:53:30.777391Z

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source=pdf_text observed=2026-08-07T12:53:30.777391Z digest=sha256:6470ceb8c2e8c4a49e343c0720a5bc02db147b16fd7d4487d47c386f0f2cb56d

Observation c2ed3c3a-522d-4ff1-b216-ebdd426cf547 · outbound

This paper cites Framepainter: Endowing interactive image editing with video diffusion priors, 2025.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Framepainter: Endowing interactive image editing with video diffusion priors, 2025

Reference 59

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verified fuzzy
raw_fallback, observed 2026-08-07T12:53:34.178606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:30.944749Z digest=sha256:d0f1ec28338ef76d543395c361132e69b78c933cc99af2b7a120436477086865

Observation 80d9c484-5c5f-4e4e-baed-abe2d4be1325 · outbound

This paper cites SSR-Encoder: Encoding Selective Subject Representation for Subject-Driven Generation.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis SSR-Encoder: Encoding Selective Subject Representation for Subject-Driven Generation

Reference 60

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no resolver link, observed 2026-08-07T12:53:31.038003Z

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source=pdf_text observed=2026-08-07T12:53:31.038003Z digest=sha256:a04ae27ad5669bda55746696b850df735cf39ee1cd93a36f342ff723f63fc291

Observation b7f7f55a-a9a4-4b17-b60a-7db377a29df6 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis mixup: Beyond Empirical Risk Minimization

Reference 61

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:53:30.654223Z digest=sha256:19854eff1a3a55bd879c366ec1bcb5fd02b9fc89b5c17196393f269f9acc4c1e

Observation 06d7d17d-210f-457b-8afc-ce0cb217cd38 · outbound

This paper cites Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Models.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Models

Reference 62

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:53:31.319577Z digest=sha256:c524bdfabc43a0e698f4b63b2fb2d598a892415094e9fcc97dc32c1176b42752

Observation 2f75b79a-8377-4460-ac67-91195de42a36 · outbound

This paper cites Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

Reference 63

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source=pdf_text observed=2026-08-07T12:53:31.447194Z digest=sha256:97cbc9c19ae2bcc13099165fefa3f2cdfbb1a029dc3acd3379e51c5a607fcf92

Observation d969ff91-810a-4f4d-9b1e-a099d5a0c0c1 · outbound

This paper cites [depth].

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis [depth]

Reference 64

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verified fuzzy
raw_fallback, observed 2026-08-07T12:53:33.885043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:31.608564Z digest=sha256:14001edc9e37713ac6fc970a1515bd2126141bf5202ea75099a5a002461ad1a2

Observation 0d46ac32-7a64-40d5-8378-53326c8e5270 · outbound

This paper cites EasyControl: Adding Efficient and Flexible Control for Diffusion Transformer.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis EasyControl: Adding Efficient and Flexible Control for Diffusion Transformer

Reference 65

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source=pdf_text observed=2026-08-07T12:53:31.157666Z digest=sha256:7b494683ffcc162486306fc4f4b94753b368b36d25d4e76f33b79d191f588e73

Observation 1ffe697d-07fc-421c-bf41-2d15c0dea4e3 · outbound

This paper cites Color: saturation, hue, brightness, and distribution.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis Color: saturation, hue, brightness, and distribution

Reference 69

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verified fuzzy
raw_fallback, observed 2026-08-07T12:53:33.584390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:31.707544Z digest=sha256:43bd4eab0dfc4aef6ed5f11e8d006fa574ca35e3848898072f461e48a818f1d8

Observation 75cb6671-5972-4e80-9b3a-68cbd6ab7db3 · outbound

This paper cites subject_consistency\.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis subject_consistency\

Reference 70

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verified fuzzy
raw_fallback, observed 2026-08-07T12:53:33.313391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T12:53:31.813629Z digest=sha256:3de13335265234ea4401536f07d967c3ccbb6aa02bdf7e4ea03711825ff62481

Observation 4d06814a-e6b6-4d16-954e-52c660e4cdc7 · outbound

This paper cites An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Reference 2022

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:53:23.757908Z digest=sha256:efb6b2de0ba3acae622958cc1f3a17e75a7dbe64f2164b50e209bcefabee1daf

Observation 66349a54-4bfd-4207-a87b-96befd67ff80 · outbound

This paper cites T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models

Reference 2023

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no resolver link, observed 2026-08-07T12:53:26.559174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:53:26.559174Z digest=sha256:ba1a087e62a59883d6561ceb944fdc7a4f1387c8c2d8880aecfc749b978a5697

Observation 6f915303-3baa-4906-81ff-311cad3b66b0 · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 2025

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:53:25.339574Z digest=sha256:9cc241876141509a454545b230fdf90dfc1f69732123a10eb258a6b3d346fd9a

Pith citing papers

Observation e603ddbb-b89c-4cf5-a06b-448d4669bad5 · inbound

Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences cites this paper.

Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis

Reference 6

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no resolver link, observed 2026-08-07T11:26:55.937172Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:26:55.937172Z digest=sha256:be851b00688a2fe166b61bb7965a1fd14279617ddd231e076c2d2bbf33cbfa8f

Observation 9f5f2eb9-e380-41f6-8387-72b8dca5ec5a · inbound

Reward Forcing: Efficient Streaming Video Generation with Rewarded Distribution Matching Distillation cites this paper.

Reward Forcing: Efficient Streaming Video Generation with Rewarded Distribution Matching Distillation Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis

Reference 5

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verified exact
arxiv_id, observed 2026-05-16T18:17:55.112233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-16T18:17:54.943863Z digest=sha256:04d7e6da627ea825c4b43ed51440fe32e35d8b6030a746bbaeee43709c81542a

Observation 0b48afa5-599c-4ab0-b15a-ff69543bc923 · inbound

DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models cites this paper.

DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:16:30.482415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-07T17:42:00.634333Z digest=sha256:88e1b609443b422debb00e9a93b3d6fc1cf075a597453f595540c12bd2b28c72

Observation a3b40466-56f7-4e69-8cc0-a1a7c82659c3 · inbound

Offline Preference Optimization for Rectified Flow with Noise-Tracked Pairs cites this paper.

Offline Preference Optimization for Rectified Flow with Noise-Tracked Pairs Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:11:15.477310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-12T02:10:27.595446Z digest=sha256:e67faf9fd0102b094c12ec2d6529f8a458ea5baba7d97320429325e7280c38d9

Observation 23023443-cf99-4bdd-82b2-36e9945fdb08 · inbound

Chamaileon: Cross-Context Binder Design with Contextualized Modeling and Mixed Sampling cites this paper.

Chamaileon: Cross-Context Binder Design with Contextualized Modeling and Mixed Sampling Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-30T20:27:19.050844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T20:27:19.050844Z digest=sha256:df5f60786e3a554be063642fdde6f79f5f086c414a39d565c6dee729a31d2e14