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Paper Citation Record · LEDGER

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers

As of 8 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 8 inbound Pith citation observations for arXiv:2505.14687.

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

pith.paper-citation-record.v1
2505.14687 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:33:12.833852Z

measured 67 of 67 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T06:40:16.892454Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T13:45:46.109771Z

Reference resolution

59 of 59 outbound references displayed

  • verified exact0
  • verified fuzzy23
  • unresolved35
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1aee1501-f069-4741-a986-6b2df5d8ef2a · outbound

This paper cites All are worth words: A vit backbone for diffusion models.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers All are worth words: A vit backbone for diffusion models

Reference 1

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Observation 79c19ce1-eb41-4073-bc28-c88e517ff778 · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 2

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Observation 570f195f-2620-41dc-914c-3d3c2f7f226a · outbound

This paper cites Pixart- σ: Weak-to-strong training of diffusion transformer for 4k text-to-image generation.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Pixart- σ: Weak-to-strong training of diffusion transformer for 4k text-to-image generation

Reference 3

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Observation 8e1e9712-4957-4e21-bf0d-88a4e3ac9617 · outbound

This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 4

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Observation f3978d47-c442-4331-bc50-de86e6ed8d5d · outbound

This paper cites COCONut-PanCap: Joint Panoptic Segmentation and Grounded Captions for Fine-Grained Understanding and Generation.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers COCONut-PanCap: Joint Panoptic Segmentation and Grounded Captions for Fine-Grained Understanding and Generation

Reference 5

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Observation b65944f0-5ef0-4d1f-90ca-b981e5a77b81 · outbound

This paper cites Flex Attention: A Programming Model for Generating Optimized Attention Kernels.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Flex Attention: A Programming Model for Generating Optimized Attention Kernels

Reference 6

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Observation 55148d36-2d75-4aad-8792-03b2310999da · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers An image is worth 16x16 words: Transformers for image recognition at scale

Reference 7

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Observation 4ed792c8-8bfc-49e3-a976-f12d51407e7b · outbound

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

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Scaling rectified flow transformers for high-resolution image synthesis

Reference 8

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Observation c084b80d-dd89-4d79-a5c9-8a0a46f8ebde · outbound

This paper cites Structural pruning for diffusion models.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Structural pruning for diffusion models

Reference 9

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Observation aa39bbf9-2236-4de0-b5dd-b96f1eddd47d · outbound

This paper cites Geneval: An object-focused framework for evaluating text-to-image alignment.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Geneval: An object-focused framework for evaluating text-to-image alignment

Reference 10

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Observation 4b10cff7-cce4-4bf4-a41e-21bfe2969bf6 · outbound

This paper cites Neighborhood attention transformer.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Neighborhood attention transformer

Reference 11

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Observation 0eea724e-96ed-45c3-81e6-87c7c20ea960 · outbound

This paper cites A Simple Video Segmenter by Tracking Objects Along Axial Trajectories.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers A Simple Video Segmenter by Tracking Objects Along Axial Trajectories

Reference 12

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Observation 03515be4-1de5-4509-b57b-0eb2ae6b54e8 · outbound

This paper cites Flowtok: Flowing seamlessly across text and image tokens.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Flowtok: Flowing seamlessly across text and image tokens

Reference 13

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Observation 03e5c20f-ce90-4244-ba60-26c8237e3e2f · outbound

This paper cites Masked autoencoders are scalable vision learners.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Masked autoencoders are scalable vision learners

Reference 14

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Observation 788e1d04-561d-4298-ba60-ebb3ee82799e · outbound

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

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 15

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Observation 37d84659-5348-4166-a3cf-c3936698a787 · outbound

This paper cites Denoising diffusion probabilistic models.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Denoising diffusion probabilistic models

Reference 16

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Observation 1f4363f6-381f-42b0-a7ea-d36456e50415 · outbound

This paper cites Vbench: Comprehensive benchmark suite for video generative models.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Vbench: Comprehensive benchmark suite for video generative models

Reference 17

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Observation d74470f6-32c6-427b-9b13-b484f376cc39 · outbound

This paper cites BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion

Reference 18

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Observation 2a26b896-c5e6-445e-8391-19d4a2ddce8e · outbound

This paper cites Democratizing Text-to-Image Masked Generative Models with Compact Text-Aware One-Dimensional Tokens.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Democratizing Text-to-Image Masked Generative Models with Compact Text-Aware One-Dimensional Tokens

Reference 19

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Observation 1787af12-90c5-4b72-9f49-63638d80ea82 · outbound

This paper cites Auto-encoding variational bayes.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Auto-encoding variational bayes

Reference 20

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Observation d75af1e5-a66f-4b6b-97b7-02db52c580e4 · outbound

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

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 21

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Observation b2bb5ecf-4d31-43cb-8817-516329cc1819 · outbound

This paper cites Flux: Official inference repository for flux.1 models, 2024.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Flux: Official inference repository for flux.1 models, 2024

Reference 22

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Observation 9cc94751-2b32-4437-b9e8-535fa9d70074 · outbound

This paper cites Set transformer: A framework for attention-based permutation-invariant neural networks.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Set transformer: A framework for attention-based permutation-invariant neural networks

Reference 23

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Observation f2caf802-0014-48e2-b3de-918c4742d692 · outbound

This paper cites Koala: Empirical lessons toward memory-efficient and fast diffusion models for text-to-image synthesis.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Koala: Empirical lessons toward memory-efficient and fast diffusion models for text-to-image synthesis

Reference 24

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Observation d5ca0487-ccd4-49f5-ae78-14d7505d2ada · outbound

This paper cites Playground v2.5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generation.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Playground v2.5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generation

Reference 25

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Observation 2a90d978-d06c-48d5-b03f-3b411c00ea1b · outbound

This paper cites Q-diffusion: Quantizing diffusion models.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Q-diffusion: Quantizing diffusion models

Reference 26

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Observation b92128ce-cfe6-4f37-9d28-195864e60914 · outbound

This paper cites Microsoft coco: Common objects in context.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Microsoft coco: Common objects in context

Reference 27

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Observation 972035e3-7f4a-4f27-92ca-ed1145ceb719 · outbound

This paper cites Flow matching for generative modeling.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Flow matching for generative modeling

Reference 28

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

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Observation 0f3c9bf9-39e8-4cd3-8cf7-717e30be88b4 · outbound

This paper cites Pseudo numerical methods for diffusion models on manifolds.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Pseudo numerical methods for diffusion models on manifolds

Reference 29

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

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Observation 0cd2cb5c-2199-4a34-a237-179c20409316 · outbound

This paper cites Alleviating distortion in image generation via multi-resolution diffusion models and time-dependent layer normalization.NeurIPS, 2024.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Alleviating distortion in image generation via multi-resolution diffusion models and time-dependent layer normalization.NeurIPS, 2024

Reference 30

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raw_fallback, observed 2026-08-07T15:33:16.093310Z

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

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Observation 19652a10-b693-4a25-877e-120a4bd9af9c · outbound

This paper cites Revision: High-quality, low-cost video generation with explicit 3d physics modeling for complex motion and interaction.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Revision: High-quality, low-cost video generation with explicit 3d physics modeling for complex motion and interaction

Reference 31

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Observation 35b85fd9-8839-4faa-a332-90f6e4ea280d · outbound

This paper cites CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

Reference 32

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Observation f4577a30-29a3-43a2-9d6c-eab7419c672d · outbound

This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Flow straight and fast: Learning to generate and transfer data with rectified flow

Reference 33

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Observation 4d94bc75-79ca-4c30-a430-b229abadc9d4 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Swin transformer: Hierarchical vision transformer using shifted windows

Reference 34

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Observation 1dbe9e44-1332-4068-bf74-324f3776c0db · outbound

This paper cites Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers

Reference 35

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raw_fallback, observed 2026-08-07T15:33:15.882654Z

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

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Observation f3338114-3ca9-4c04-8fe0-8ad611cde28c · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Pytorch: An imperative style, high-performance deep learning library

Reference 36

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source=pdf_text observed=2026-08-07T15:33:10.831193Z digest=sha256:3d5bba8164c3fd62411a0d9dbc8ea41c7afe7e76d30063d529995f2d416a6f9e

Observation 86184171-4eff-455c-bce7-036aa8a98720 · outbound

This paper cites Scalable diffusion models with transformers.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Scalable diffusion models with transformers

Reference 37

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source=pdf_text observed=2026-08-07T15:33:10.906479Z digest=sha256:16ba5cb0dc77c33f49e9cfd697c087680740b2dfb0e11d10c28d18ebd912f942

Observation 043dafce-3774-4c63-ac1a-3847466d5983 · outbound

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

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Learning transferable visual models from natural language supervision

Reference 38

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source=pdf_text observed=2026-08-07T15:33:10.970631Z digest=sha256:706b2725fa9956be45f21d2db090a33cf650732848e0de615abc7aa046860ff2

Observation a275f21e-61a1-43de-8f5a-b6f5a8de9e99 · outbound

This paper cites Stand-alone self-attention in vision models.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Stand-alone self-attention in vision models

Reference 39

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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=2026-08-07T15:33:11.011275Z digest=sha256:5cffb29de3d49197d108d993e3f22c171141023b27a0c29118e666721bf5830c

Observation 2bbd127e-dbbb-433b-813f-e49370cc231c · outbound

This paper cites Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation

Reference 40

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source=pdf_text observed=2026-08-07T15:33:11.114818Z digest=sha256:38003fa952d4f1dbd56e7e78c6d3adeee6351b84988461c82b08bd65f14618bc

Observation 9f72c516-3ad7-4c04-8ece-4ef59bbc362f · outbound

This paper cites Flowar: Scale-wise autoregressive image generation meets flow matching.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Flowar: Scale-wise autoregressive image generation meets flow matching

Reference 41

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raw_fallback, observed 2026-08-07T15:33:15.477595Z

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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=2026-08-07T15:33:11.195760Z digest=sha256:77d6e34af358bd55bac0a9ce64f5ac3d5adad5caa6fc95adafed2815ab50b446

Observation 94c821a4-de10-4790-81ad-2d7123d4bd17 · outbound

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

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers High-resolution image synthesis with latent diffusion models

Reference 42

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source=pdf_text observed=2026-08-07T15:33:11.277092Z digest=sha256:824b08fdcec3d820bcf72581f2d866342822d6d201e9ed917405ae1c67e58b5e

Observation 6398b433-bfa5-4f43-8e83-f8eeeefeec59 · outbound

This paper cites Progressive distillation for fast sampling of diffusion models.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Progressive distillation for fast sampling of diffusion models

Reference 43

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raw_fallback, observed 2026-08-07T15:33:15.272853Z

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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=2026-08-07T15:33:11.359332Z digest=sha256:cd5a3fda7ff4b50d43f4fce6b345beb4127e92b524d65a493942eb4966fe64be

Observation 321737fb-993e-48a6-a12b-32fbfd077602 · outbound

This paper cites Post-training quantization on diffusion models.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Post-training quantization on diffusion models

Reference 44

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raw_fallback, observed 2026-08-07T15:33:15.032194Z

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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=2026-08-07T15:33:11.455816Z digest=sha256:88616f17a39f5a414a6809030f6721522a747285c8eb90146e1de71d07a53393

Observation c24fecb9-67b7-4ab2-a03d-d5e391791211 · outbound

This paper cites Deeply Supervised Flow-Based Generative Models.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Deeply Supervised Flow-Based Generative Models

Reference 45

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source=pdf_text observed=2026-08-07T15:33:11.513331Z digest=sha256:82f12e7c56ec1cc3a1cf860a34568a74050a8f403810bb81b18135d6b35a8405

Observation 19ff55c3-075f-45ca-bbf3-7053f4ce474c · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Score-Based Generative Modeling through Stochastic Differential Equations

Reference 46

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source=pdf_text observed=2026-08-07T15:33:11.607502Z digest=sha256:859409d03fc8fac4fafb86540595abf95ebd800aa01f45d6287b028b3bc57a2f

Observation 5ab29220-e2f7-49e4-a5c8-71683cfec651 · outbound

This paper cites Attention is all you need.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Attention is all you need

Reference 47

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source=pdf_text observed=2026-08-07T15:33:11.705712Z digest=sha256:690d0f24178f9079a66ec3d55f6f8c7d3a4ca6800b3062a3ed41db776287e949

Observation 0a5d231c-f14c-4c32-ad4f-523e11f1d95d · outbound

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

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Wan: Open and Advanced Large-Scale Video Generative Models

Reference 48

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source=pdf_text observed=2026-08-07T15:33:11.772789Z digest=sha256:870b27a9e674c0baa4db8b2994829d876edc478afe993fee4091f3759a3e24ab

Observation 335f927a-0a5c-4a67-a57f-1cefeef14486 · outbound

This paper cites Axial- deeplab: Stand-alone axial-attention for panoptic segmentation.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Axial- deeplab: Stand-alone axial-attention for panoptic segmentation

Reference 49

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raw_fallback, observed 2026-08-07T15:33:14.822785Z

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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=2026-08-07T15:33:11.883552Z digest=sha256:788a085e145c28d3b4445b1921a9726fd9c3ef334ade1c9ba7959db58807ea90

Observation 38e89115-e881-4974-8c2e-638c6bcb5b66 · outbound

This paper cites Linformer: Self-Attention with Linear Complexity.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Linformer: Self-Attention with Linear Complexity

Reference 50

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source=pdf_text observed=2026-08-07T15:33:11.991320Z digest=sha256:9ad290633c2bd2f8c7efa47f49b06d5f7aa277f892844aa1b44b54a69e236c86

Observation 26888ff7-48f0-4f2b-a890-68aa6548ffe5 · outbound

This paper cites PPT: Token Pruning and Pooling for Efficient Vision Transformers.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers PPT: Token Pruning and Pooling for Efficient Vision Transformers

Reference 51

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source=pdf_text observed=2026-08-07T15:33:12.123223Z digest=sha256:461068cad4b77b91187efa4deddb4f749b52640444897a4433febbe163dc5d07

Observation 7d171f7b-9679-4dd8-98b7-0f4657292cc7 · outbound

This paper cites Revealing the dark secrets of masked image modeling.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Revealing the dark secrets of masked image modeling

Reference 52

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raw_fallback, observed 2026-08-07T15:33:14.625332Z

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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=2026-08-07T15:33:12.199902Z digest=sha256:cf043fde9f55d93788e407c05847588386ae5ffe81e4f623906e85d46998d6cf

Observation 21e1b526-6c24-4eb8-9732-6fa63313b9fa · outbound

This paper cites Imagereward: Learning and evaluating human preferences for text-to-image generation.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Imagereward: Learning and evaluating human preferences for text-to-image generation

Reference 53

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raw_fallback, observed 2026-08-07T15:33:14.439072Z

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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=2026-08-07T15:33:12.267943Z digest=sha256:490e033b941e851fd08a54c74571fc672e02383729b9f67b2694c8056a314ec7

Observation 20031a9d-1774-46c2-9f24-63e9b5f8b4bd · outbound

This paper cites 1.58-bit FLUX.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers 1.58-bit FLUX

Reference 54

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source=pdf_text observed=2026-08-07T15:33:12.353042Z digest=sha256:6a4a283a39ad61c94b0abdcef44625b3648cf36834b76d8fe7ccb7e02d43ea92

Observation 5ca922d8-374f-4f87-84ea-6bbce513e84b · outbound

This paper cites Randomized Autoregressive Visual Generation.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Randomized Autoregressive Visual Generation

Reference 55

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source=pdf_text observed=2026-08-07T15:33:12.464495Z digest=sha256:6a2667042214e2f9e9b7c436d4ed1a21c9b50150945785794decf2a56ba7da8d

Observation 7620ea40-4ef0-47f6-b852-c29001f5d12e · outbound

This paper cites An image is worth 32 tokens for reconstruction and generation.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers An image is worth 32 tokens for reconstruction and generation

Reference 56

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raw_fallback, observed 2026-08-07T15:33:14.221647Z

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source=pdf_text observed=2026-08-07T15:33:12.577214Z digest=sha256:04a397580196936d30e7526d981038075edda5e33779e3d454f39f23c2d4ef90

Observation 57186a5d-b8a1-4890-9d3e-67454e39df8b · outbound

This paper cites Ditfastattn: Attention compression for diffusion transformer models.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Ditfastattn: Attention compression for diffusion transformer models

Reference 57

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raw_fallback, observed 2026-08-07T15:33:14.001466Z

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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=2026-08-07T15:33:12.642624Z digest=sha256:330865b8ef79fe97dccfb3441a61ce44b6b25f3d653f4a3e56205c07d7b3efaa

Observation 09a73369-39d8-4ca8-9def-216df835b5ed · outbound

This paper cites Big bird: Transformers for longer sequences.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Big bird: Transformers for longer sequences

Reference 58

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raw_fallback, observed 2026-08-07T15:33:13.837906Z

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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=2026-08-07T15:33:12.738393Z digest=sha256:6ac56612c313fab11897dfe99f7ce1de106e371eac5b37d6548b953492a45eb9

Observation 5f1ba8ba-8080-4e44-b3d1-2a3d53862c32 · outbound

This paper cites Fast Video Generation with Sliding Tile Attention.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers Fast Video Generation with Sliding Tile Attention

Reference 59

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source=pdf_text observed=2026-08-07T15:33:12.833852Z digest=sha256:d6ff600f978799941429357d94c09bb8eafb67c236e8b57b81205d221a9553fd

Pith citing papers

Observation e35993a9-d991-427b-84a6-22aa4778c62d · inbound

DC-DiT: Adaptive Compute and Elastic Inference for Visual Generation via Dynamic Chunking cites this paper.

DC-DiT: Adaptive Compute and Elastic Inference for Visual Generation via Dynamic Chunking Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers

Reference 12

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arxiv_id, observed 2026-05-15T15:10:05.851830Z

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source=pdf_text observed=2026-05-15T15:10:00.146694Z digest=sha256:312382f61df8d3b02d9b460e8348ccb51aea267f4e92733309a3379ccc50ac13

Observation 43ca65b5-c884-476c-89eb-9a67ba031992 · inbound

A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens cites this paper.

A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers

Reference 59

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arxiv_id, observed 2026-05-10T23:10:50.174151Z

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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=2026-05-10T19:19:17.796377Z digest=sha256:f347f70027d4e1f9a9be84d98da9dc3a8c5568a0e1e9eec4c882b1f89f96bdd5

Observation b86c1ea3-1ce8-4a08-a0f2-0ad7cacd5cdf · inbound

Frequency-Aware Flow Matching for High-Quality Image Generation cites this paper.

Frequency-Aware Flow Matching for High-Quality Image Generation Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers

Reference 45

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arxiv_id, observed 2026-05-10T11:00:04.105673Z

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=2026-05-10T10:58:05.541289Z digest=sha256:ccd09b799f035f38217ca67e839614a8f8625f1477c3cdf288d1233d5d48a25e

Observation a1252ef0-c61f-4411-b75a-250093626758 · inbound

Efficient Video Diffusion Models: Advancements and Challenges cites this paper.

Efficient Video Diffusion Models: Advancements and Challenges Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers

Reference 110

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arxiv_id, observed 2026-05-10T09:03:25.769904Z

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=2026-05-10T08:28:29.706249Z digest=sha256:1db7968e5dcd6717103c2e83a3be791008038ba0261374d9fa7df42112f52b31

Observation 46388b3a-5e1a-407a-8fa7-2421d098f3b5 · inbound

Attention Sinks in Diffusion Transformers: A Causal Analysis cites this paper.

Attention Sinks in Diffusion Transformers: A Causal Analysis Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers

Reference 10

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arxiv_id, observed 2026-05-12T06:26:24.044397Z

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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=2026-05-12T04:18:26.883899Z digest=sha256:eeb89d5cf45cd4259d2f9c77ab448dc624a0c0282959d7ef6f4a57d48c37fd2a

Observation a5fff18d-56e4-433c-a0a9-601a2ebc0192 · inbound

Attention Sinks in Diffusion Transformers: A Causal Analysis cites this paper.

Attention Sinks in Diffusion Transformers: A Causal Analysis Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers

Reference 10

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arxiv_id, observed 2026-05-13T06:02:23.283147Z

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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=2026-05-13T05:59:16.233848Z digest=sha256:4c5c54c82b1241dbb3447e53a2bcb5fdf5846c0a1ea14d88859bcadc75e328ec

Observation 5a6911fb-01fb-4563-a1ba-bcbc644f8972 · inbound

Attention Sinks in Diffusion Transformers: A Causal Analysis cites this paper.

Attention Sinks in Diffusion Transformers: A Causal Analysis Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers

Reference 10

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arxiv_id, observed 2026-07-01T13:45:46.111412Z

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=2026-06-30T22:47:11.360530Z digest=sha256:575506e482ecf6919d693e019499d3fbc44319788392ca7816a4fccc1202a3cd

Observation 03ed245a-a299-4c3a-9bee-234a7289ec20 · inbound

ACID: Adaptive Caching for vIDeo generation cites this paper.

ACID: Adaptive Caching for vIDeo generation Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers

Reference 13

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no resolver link, observed 2026-08-02T06:40:16.892454Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T06:40:16.892454Z digest=sha256:77977b46e13f34e7485ccad4e2e1cadaff896a0324b8b3369c0243d78194f07e