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Paper Citation Record · LEDGER

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

As of 8 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 2026-08-08T06:32:00.761636+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=sha256:4a956f68b95322c272bf5939b0289849fa279ae9175466d2a4974f0c9bf6fc9f

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:a155353c5335bc0c4ad31ec483db1909dcd5ccc6703b887e1bcc8f3cfd81ab9e

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=sha256:0b569dbb81a30df831df992cd6681e00853930aae73dee46fdf866426e668b43

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=sha256:29d66abf1124ab3cdf2710b778935a983a6a76e524a128d6d4a9bd496c879b1c

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=sha256:92c37ecba3b11fa7bdeaf6721f707a88e5e465d3c91f439c96b85921dcf6be30

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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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:23.149714Z digest=sha256:dc842e68a3b59903c1cbe5e8bd6dc785e1c6198deb16805287301d3cacfdc0ed

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:23.281171Z digest=sha256:0624a92c4cbc000ac52dda66d99a5f31ca026cb361ad41376a808bdc5ca05cd6

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:bac78dad876dde133f3700489032be448c869f42df51366e7cf16edcf612a93f

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:aed9de69576f20aadbac78cb933fe42253c54ccea0222aa7209465821a314d1f

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=sha256:426b7941dce804ba60ed564d08b351b452560ef57f023866fed7f705d3df2a78

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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raw_fallback, observed 2026-08-07T12:53:35.713523Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:23.639105Z digest=sha256:0128f5f1b3e0eecc691d96556502d0744862876b5be0a85606cf42f58afe2e9e

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=sha256:684848419151b374518663d30856eda5a9e6d9c21138f7eb43364df0e35791f3

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=sha256:0c7eb551bd23d67bcb50fe2ca478a1bd358191b69823a147f055e4ebf37efbd5

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:f1f1cbee0062be13f45aab6c0d4fb6f4d8a5b8b1d47b454d11f0bf2ee854cae3

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=sha256:31e7cd94a70070f0984fc563acb51dfa046b32a075b2514289e12980277f9509

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=sha256:4e096d3b8875f84465913a76df0690e36cdfc47c29b859563f34be25a6402780

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=sha256:75af47cea9a4db51638af1b801fb5be5bb8885af062435d15f2d155d5f96a7df

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:a79a0a552fd645e3da906b4a79ca39da5753ce294a86a0dd81af6fff00b5bc10

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:f3f5eea99a65c3fe6ba1b0afe7010f76cc65b641b20300751426e2ff299102ab

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:ed6f31b0cab018f5efd7c42fc984b91c7463929d9b9adf9e623c49110d640aa4

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=sha256:8cb31ca0ab19cc2a9082daa43302d6c8c6dceb4071ea0a743184d3947b3ca9ce

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=sha256:4f5fd32f775b4d2f1c060d6f619455103b9492505af2a0f775058ea3f703ae57

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=sha256:8b79219f91751a2f62af149ae1dab6602147eb242a6f55085cf313c26a5d6aa1

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=sha256:18d7618eb0a7edcdfb939be137957888175afc7031b05a4dc41f10196b648ee9

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:d270ae067dd2ec9715804ed70de8b4a71f57d8e91ed4d6d1fc8baf73dcf5dae3

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=sha256:0cf4fa5f48dfe8ff07ac09b4ce325f9da1920c167caee803206733cb00a63dea

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=sha256:786d9835a9860d6b09264d590bf0296964a5d26ac0fa1a0a1bd1bff2bae645da

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:ae89ffe425410a8422022adaac6ebfa7d6d07944cfcfc66492775520d4886050

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=sha256:5d0f49a0210f1846f73f41036705243daf55f9802e7d16bb83b455513bbd871a

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:d9f53d88999c17e1afb728a5199e394c82dce4c848004ec8e583b525a04dabb9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:26.460823Z digest=sha256:55c45eca57a213ec179211e418dde1e64be31664031627cf09375a253835c634

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:26.689467Z digest=sha256:396fbff30ee152bdaa5229189eeae4f1bddf89df688e9d981ffc27cf14fa8282

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=sha256:3d2ae61b4248f9562cf998c55ce90ec1135da26467c97a67a1bf6c1b6cc3d0e5

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:ab79a5e4a1db464eb4c8df00916e320782d7b1f5d03bbf8df82efb868afb84d3

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=sha256:2afeaa3721668357de588d8099b27d1edf1f5f36c7eb54e6a9c57b6d58cd8ce9

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=sha256:0e784bbbdb358cc5cc3c38f7b0f829965e92fc871dc63d44e99a1c8251b48702

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:ff5518908067f1f0bf10f1d6ee1e5f7145d5ac35552f3a6f49626e7c60333cd9

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:f97838943b028f370abb6ea7743eccb273766d1e860b8fb37a399301f6e6ae07

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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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:27.519189Z digest=sha256:12daae782b6d9d73824792aa207eb84df9e5c556797f8b148c2ef1ab79dc7049

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=sha256:591471800ad9a44718e604820cb594fd769d1cca56c231cdebae1bfb4a503d3b

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=sha256:82c9e7e8634cc9fe65007ceeb6e5190634931eb561190e7293a0a8d3750f54c8

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:ecffe1fef7ba493a887c3b7d18f5bdf65b7c31857b05fe202c6f2b007b1a00f6

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=sha256:751800f6c7fd8af33246d356443a6d26243dbaa855033bfa41086d63fb82f096

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=sha256:3ed66d606f7ff3c5d0300bc72084087765b05cfd0ed677258dfe4c3b2d139ab6

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=sha256:339e92a6be28bd978b7c1802532b4c180fd615cdc355e12c3d231a17e106b840

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=sha256:9798663d87fb3b44edc1206508f6d465b9dbf7c058b0f3ee1f4ed28f23986f20

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-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:53:28.364742Z digest=sha256:2c26eded564b4f40dfae27aeb8f11e718808d0f02511f221e086f20768dec8fe

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=sha256:117182368e85a108cfa0a0895cd51fc2ebd169b19df4db33323a89271adbb45b

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=sha256:3a1077f657ee03f9d12455ed65f9158b27e2b724721f9828164d930da8f8e293

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:efd32e422cf61fdee715af47e0426f1601d62a4a82c49b9b99fa9f4d2132cb30

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=sha256:02bded51b28c57b41348b9677f049bb3f0abbc59e44c0152edad900ddc402f42

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:29.934326Z digest=sha256:e0223a3a32939887f2498bf9661be6f2b66c13411870a2dfb90020d19aed7ab5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:29.975109Z digest=sha256:f4f2d7422c499a95f6456420371ede1128839b3d10a8b6009a1d2cfd11c25cc6

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=sha256:447ea27186cc5e2e0cfc6fa65c13bfe7247b71842761cc0d081b035ce1e090ce

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=sha256:805b3feb91ab4bd2d85fd18f5c64d39237edaad396bf6a47f06eb11b0af69924

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:e3f292e7adefdc71da95dac2dc5ab3db8654a7ea87928a8f807ce17bceeb73c8

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=sha256:4336a9ec23702321328e87ab4b072f95a6969a6bb183501b67f6a01981d3da6e

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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source=pdf_text observed=2026-08-07T12:53:30.777391Z digest=sha256:66d3e3d831debd4a823f841e9f6f31de86ba7cb89c51497b8bb7f0788bb36ae6

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:30.944749Z digest=sha256:fd4de3764a2636656c899d91ec1c4f8c61a7cd1c95081056791501e9cbb4c6aa

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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source=pdf_text observed=2026-08-07T12:53:31.038003Z digest=sha256:d33560cdbed9582a273d5508e612d07725e971449138d751e13283aadd8a4951

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:cfc8558aa08f9f7eb1e3781ed4921e84ae033b3b47b81531c33e934025a70888

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=pdf_text observed=2026-08-07T12:53:31.319577Z digest=sha256:ec3ec57995d4626a0ef6ad22d8a197cb184b3d9cc0d64447157a08275f66c162

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=sha256:2a8195acfd456a0a8d7f1804cd9e2ee27849918e3cdf4e83e4d2ac20b3823ca2

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:31.608564Z digest=sha256:acd364788f7beeae977c88214c203fb473e63d492a29894eccaa73c28724b4ad

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=sha256:63bc9ae726e4dfb319edc35803c6aeea761a720cdb612f6bbe3819205db33f26

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:31.707544Z digest=sha256:f0826527efed0f5aab2a7dbfb6fcf8531f2b14fb33f7814c6ea5b28871d5b015

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:53:31.813629Z digest=sha256:54dc70dc8d3f159d8dd76ba99e3ab3179a723fd1eb87d8f6b7e52f86e1070049

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:53:23.757908Z digest=sha256:181ac9afde4849bb39729cfb7132ae366cae91471f59faf278e910d235a26499

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:53:26.559174Z digest=sha256:0a4ff7dca616cbcb08462a97bfbcdc86c66231c88790a9590b69ecb60dafa300

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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no resolver link, observed 2026-08-07T12:53:25.339574Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:53:25.339574Z digest=sha256:481ce866763053e51e53286fae46953abd9420412f2fa5ae5fd345ff553593b2

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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source=pdf_text observed=2026-08-07T11:26:55.937172Z digest=sha256:f89c3edcb6d7eab1854079900825216712e0e4110fb201b439b941563a1725b9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T18:17:54.943863Z digest=sha256:806fc691694bd6b60f08a21a1ca490da89231a51ada8e29697de2c3067ec3a3a

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T17:42:00.634333Z digest=sha256:593e09276077dbe2f2da51e946f84fbdc00ed0e34b2309104ad701f2f67bafe4

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T02:10:27.595446Z digest=sha256:c41eada451dac240cfde6436ce0bae16f80d6518b1ead38eb84367a086c5e835

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:cc2b4f4695506ad1f7adc3bcc656f8b6f5f850777ec51a7a771ba15c79564c88