Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:42:40.099901Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 4 inbound Pith citation observations for arXiv:2505.21179.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:42:40.099901Z
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Pith citing papers itemized under the disclosed page cap.
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A source-named dated measurement, never combined with another source.
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87 of 87 outbound references displayed
External citation measurements
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Observation 8b54f44b-4545-46fb-b897-1b964a48bb3b · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Unresolved cited work
Reference 1
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Observation 04f4ec63-320d-4073-8230-f8515d2c9760 · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models High-resolution image synthesis with latent diffusion models
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Observation 7efe85fa-47a9-43e5-896c-97bad61d63bc · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Denoising diffusion probabilistic models
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Photorealistic text-to- image diffusion models with deep language understanding
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Observation 5529450a-25a3-4f96-9480-40296ef0ecdf · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Imagen Video: High Definition Video Generation with Diffusion Models
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Observation 22a4c4d8-a21c-402f-81e2-a4492c995ad5 · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Wan: Open and Advanced Large-Scale Video Generative Models
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Observation 430db95e-017d-4f2f-8155-df99c8e59c18 · outbound
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Observation 8458682c-a9c9-495f-9d32-0e50a53013b8 · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Gans trained by a two time-scale update rule converge to a local nash equilibrium
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Imagereward: Learning and evaluating human preferences for text-to-image generation
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Observation afa0b65f-42d3-42b3-9f70-be000a9417d5 · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Hierarchical Text-Conditional Image Generation with CLIP Latents
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Observation a48c735c-3dd2-44fd-be3d-f629a778b2be · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Make-A-Video: Text-to-Video Generation without Text-Video Data
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Observation eb1d2162-44e6-472b-91e8-ace61f52b47c · outbound
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Observation d2d2576c-7d30-4c89-8ba5-055b9772c08f · outbound
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Photorealistic video generation with diffusion models
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Score-based generative modeling through stochastic differential equations
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Observation ba572255-8ba1-4e5e-b02e-957776ec0469 · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Elucidating the design space of diffusion-based generative models
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Building normalizing flows with stochastic interpolants
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Albergo, Nicholas M
Reference 30
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Observation da07234a-9026-4d35-9c4a-b4f74f51e078 · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Flow Matching in Latent Space
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Observation 867d164c-b9cc-40e8-a7e3-1047efb90241 · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Instaflow: One step is enough for high-quality diffusion-based text-to-image generation
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models PixArt-\Sigma: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation
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Observation 5c9985a9-f60c-436a-9496-d462c89a3dda · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Playground v3: Improving Text-to-Image Alignment with Deep-Fusion Large Language Models
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Observation 8d25b664-d343-44b7-9efa-c2b375a88f8a · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Lumina-next : Making lumina-t2x stronger and faster with next-dit
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Lumina-Video: Efficient and Flexible Video Generation with Multi-scale Next-DiT
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Hyper-SD: Trajectory segmented consistency model for efficient image synthesis
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models The fox is made of polygons
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Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Unresolved cited work
Reference 83
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Observation 55e644a0-53f8-485f-89f6-0ce42bc9f6bb · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Unresolved cited work
Reference 84
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Observation c0a82516-356d-45df-a109-fc928ee5d5ce · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Unresolved cited work
Reference 85
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Observation c559a8c7-f6a9-4306-8642-e4af26f8d0f0 · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Unresolved cited work
Reference 86
Source-reported events for the cited work
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Observation b46cf0dd-d7b2-46d3-9216-ad4015c6055d · outbound
Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models Unresolved cited work
Reference 87
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 790861f9-52da-427e-adc3-92cbedaba624 · inbound
Not all tokens contribute equally to diffusion learning Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models
Reference 3
Source-reported events for the cited work
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Observation d15d1ca8-8d33-47cd-bfed-8dad3040c2d5 · inbound
Orthogonal Negative Guidance in Attention Feature Space for Text-to-Image Generation Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models
Reference 11
Source-reported events for the cited work
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Observation 388d1a1b-301c-4f95-9918-62f300ce82d8 · inbound
Not All Prediction Targets Keep Training-Free Diffusion Guidance on the Manifold Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models
Reference 4
Source-reported events for the cited work
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Observation 264cc489-2207-45f9-8aff-038b8842aa41 · inbound
MissingBench-Verified: Probing Vision-Language Models' Inability to Detect Missing Object Parts Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models
Reference 14
Source-reported events for the cited work
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