Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer | Paper Citation Record

Observation e0ed16a2-9d31-49cf-b141-03222a006b78 · outbound

This paper cites Approximate caching for efficiently serving{Text- to-Image}diffusion models.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Approximate caching for efficiently serving{Text- to-Image}diffusion models

Reference 1

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Observation c2c081a3-c18f-4e9e-b510-7261d594a3c4 · outbound

This paper cites Qwen Technical Report.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Qwen Technical Report

Reference 2

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Observation aa9bb1a7-4d87-4e78-8034-93c7bed08129 · outbound

This paper cites Round and Round We Go! What makes Rotary Positional Encodings useful?.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Round and Round We Go! What makes Rotary Positional Encodings useful?

Reference 3

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Observation 2efe5917-de46-40db-b023-e781c87f8ed6 · outbound

This paper cites Gpt-neox- 20b: An open-source autoregressive language model.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Gpt-neox- 20b: An open-source autoregressive language model

Reference 4

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Observation 38a6f7a2-ce87-4135-a3e1-9e8cedbec33d · outbound

This paper cites Taehv: Tiny autoencoder for hun- yuan video.https://github.com/madebyollin/ taehv, 2025.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Taehv: Tiny autoencoder for hun- yuan video.https://github.com/madebyollin/ taehv, 2025

Reference 5

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Observation 84d0ef3f-e380-4dff-907d-7793c0119df1 · outbound

This paper cites Token merging for fast stable diffusion.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Token merging for fast stable diffusion

Reference 6

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Observation 31ce9347-3152-4476-ac1a-c3bc083815f6 · outbound

This paper cites Ld-pruner: Efficient pruning of latent diffusion models using task-agnostic insights.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Ld-pruner: Efficient pruning of latent diffusion models using task-agnostic insights

Reference 7

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Observation ca16a58b-01ce-48d4-86ac-e5d416c99c65 · outbound

This paper cites Sparsedit: Token sparsification for efficient diffusion transformer.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Sparsedit: Token sparsification for efficient diffusion transformer

Reference 8

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Observation 670e1e22-1ba3-45d4-9538-933145eea156 · outbound

This paper cites Pixart-α: Fast train- ing of diffusion transformer for photorealistic text-to-image synthesis, 2023.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Pixart-α: Fast train- ing of diffusion transformer for photorealistic text-to-image synthesis, 2023

Reference 9

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Observation 1e56d59a-441a-46ac-8d52-72f3086b835e · outbound

This paper cites Q-dit: Ac- curate post-training quantization for diffusion transformers.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Q-dit: Ac- curate post-training quantization for diffusion transformers

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:25.852747Z

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Observation a6fdde84-867f-4e05-ab22-9d113dcf9426 · outbound

This paper cites $\Delta$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer $\Delta$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers

Reference 11

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Observation 5588daa0-1b4c-4c7b-a408-50218720e742 · outbound

This paper cites Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 12

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Observation 7c6ec55f-e690-4746-8d72-58c0828834fb · outbound

This paper cites Extending Context Window of Large Language Models via Positional Interpolation.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Extending Context Window of Large Language Models via Positional Interpolation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:26.189555Z

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Observation a2e19cb9-4de0-4135-ac68-b011db4bdc88 · outbound

This paper cites Edt: An efficient diffusion transformer frame- work inspired by human-like sketching.Advances in Neu- ral Information Processing Systems, 37:134075–134106,.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Edt: An efficient diffusion transformer frame- work inspired by human-like sketching.Advances in Neu- ral Information Processing Systems, 37:134075–134106,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:26.361776Z

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Observation 4e29edbd-83ab-4221-b045-18cc10660614 · outbound

This paper cites an unresolved cited work.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Unresolved cited work

Reference 15

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Observation 872c2f40-386c-4e93-911d-6117ec0833da · outbound

This paper cites Palm: Scaling language modeling with pathways.Journal of Machine Learning Research, 24(240): 1–113, 2023.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Palm: Scaling language modeling with pathways.Journal of Machine Learning Research, 24(240): 1–113, 2023

Reference 16

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Observation e6c34b0e-8c19-4989-9c03-71af22d830fa · outbound

This paper cites A deep multi-level network for saliency prediction.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer A deep multi-level network for saliency prediction

Reference 17

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Observation 144134a0-3b22-49fa-87ea-4ea9766ce396 · outbound

This paper cites Predicting human eye fixations via an lstm- based saliency attentive model.IEEE Transactions on Im- age Processing, 27(10):5142–5154, 2018.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Predicting human eye fixations via an lstm- based saliency attentive model.IEEE Transactions on Im- age Processing, 27(10):5142–5154, 2018

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:26.844453Z

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Observation 68c5359b-fe50-4902-bf35-f223422e013d · outbound

This paper cites Scalable high-resolution pixel-space image syn- thesis with hourglass diffusion transformers.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Scalable high-resolution pixel-space image syn- thesis with hourglass diffusion transformers

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:26.960316Z

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Observation 1068bbf4-d072-40c3-be15-91da4d90bc12 · outbound

This paper cites Vq4dit: Efficient post-training vec- tor quantization for diffusion transformers.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Vq4dit: Efficient post-training vec- tor quantization for diffusion transformers

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:27.078408Z

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Observation 0a79e3c5-740c-42e9-a757-22671dbc3bd5 · outbound

This paper cites LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Reference 21

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Observation cf80460a-6c2b-48bc-a018-62cc57746575 · outbound

This paper cites Patched denoising diffusion models for high-resolution im- age synthesis.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Patched denoising diffusion models for high-resolution im- age synthesis

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:27.347342Z

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Observation 36ffeeff-54bb-4c40-b31b-26a1052cbebb · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 23

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Observation 4f8fe5bc-c994-4e68-8217-1287edfd8125 · outbound

This paper cites Fewer denoising steps or cheaper per-step inference: Towards compute-optimal dif- fusion model deployment.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Fewer denoising steps or cheaper per-step inference: Towards compute-optimal dif- fusion model deployment

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:27.616912Z

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Observation 9409960e-5c80-44f4-b2e3-08d5520fc90d · outbound

This paper cites The llama 3 herd of models.arXiv e-prints, pages arXiv–2407,.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer The llama 3 herd of models.arXiv e-prints, pages arXiv–2407,

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Observation 17a3f926-b427-4a27-b36b-947dcb1dde41 · outbound

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

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 26

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Observation d9dd0a1b-53a7-4b98-ace5-bdb50f1fdf4d · outbound

This paper cites Structural pruning for diffusion models.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Structural pruning for diffusion models

Reference 27

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Observation 0187e7f4-e393-4e2b-a618-cf7c7bfdd613 · outbound

This paper cites Tinyfusion: Diffusion transformers learned shallow.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Tinyfusion: Diffusion transformers learned shallow

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Observation ed0d0cab-40ff-4c6f-ab86-bf5d9103ce55 · outbound

This paper cites Video Diffusion Transformers are In-Context Learners.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Video Diffusion Transformers are In-Context Learners

Reference 29

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Observation d81bacbe-e3e6-48fd-9f36-fc2aa6052c75 · outbound

This paper cites Relational diffu- sion distillation for efficient image generation.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Relational diffu- sion distillation for efficient image generation

Reference 30

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Observation a5a37270-357e-45f6-892d-a32495f68057 · outbound

This paper cites Romantex: Decoupling 3d-aware rotary positional embedded multi-attention network for texture synthesis.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Romantex: Decoupling 3d-aware rotary positional embedded multi-attention network for texture synthesis

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Observation 8a365291-68ac-4f21-8736-ccee511e7369 · outbound

This paper cites Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models

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Observation 2ba9d8a4-e317-4b8a-bc94-b20cffabb96b · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

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Observation 8d5f83e2-0f82-4020-9611-f12717be5033 · outbound

This paper cites LTX-Video: Realtime Video Latent Diffusion.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer LTX-Video: Realtime Video Latent Diffusion

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Observation 546baabb-291c-4beb-bd2d-f8ad39a5b053 · outbound

This paper cites Graph- based visual saliency.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Graph- based visual saliency

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Observation ccf80bf4-4d0b-4e9c-92a2-83feb7839497 · outbound

This paper cites Rotary position embedding for vision transformer.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Rotary position embedding for vision transformer

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Observation 77187c48-5a48-49e2-b234-0c0a8b8d999d · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.Advances in neural information processing systems, 30, 2017.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Gans trained by a two time-scale update rule converge to a local nash equilib- rium.Advances in neural information processing systems, 30, 2017

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Observation 248eea44-bdfb-4dfe-ad25-52c4dc642e16 · outbound

This paper cites Cascaded diffusion models for high fidelity image generation.Jour- nal of Machine Learning Research, 23(47):1–33, 2022.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Cascaded diffusion models for high fidelity image generation.Jour- nal of Machine Learning Research, 23(47):1–33, 2022

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Observation 5f8f55c7-5e8a-455f-8e41-d7806714a872 · outbound

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

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Vbench: Comprehensive benchmark suite for video generative models

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Observation 7295cc68-5800-4810-a296-ca5e52085c6c · outbound

This paper cites A model of saliency-based visual attention for rapid scene analysis.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer A model of saliency-based visual attention for rapid scene analysis

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Observation c86b0e01-4133-4ba2-96df-7212a577672b · outbound

This paper cites Latent space super-resolution for higher-resolution image generation with diffusion models.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Latent space super-resolution for higher-resolution image generation with diffusion models

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Observation 280e60da-f509-4285-a385-804752bfedb4 · outbound

This paper cites Upsample what matters: Region-adaptive latent sampling for accelerated diffusion transformers.arXiv preprint arXiv:2507.08422, 2025.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Upsample what matters: Region-adaptive latent sampling for accelerated diffusion transformers.arXiv preprint arXiv:2507.08422, 2025

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Observation 2fa753cc-1c5f-4ee9-a9b7-a183b32eb2bd · outbound

This paper cites Eml-net: An expandable multi- layer network for saliency prediction.Image and vision computing, 95:103887, 2020.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Eml-net: An expandable multi- layer network for saliency prediction.Image and vision computing, 95:103887, 2020

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Observation d1937e08-c35d-4c47-972b-112590eb5f54 · outbound

This paper cites Salicon: Saliency in context.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Salicon: Saliency in context

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Observation 0ceca32e-d177-4023-9dfa-0cf33affaaf4 · outbound

This paper cites Pyramidal flow matching for efficient video generative modeling.arXiv preprint arXiv:2410.05954,.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Pyramidal flow matching for efficient video generative modeling.arXiv preprint arXiv:2410.05954,

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Observation 3d7befc1-7629-43f3-bd81-ddfde1b206e1 · outbound

This paper cites Adaptive caching for faster video generation with dif- fusion transformers.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Adaptive caching for faster video generation with dif- fusion transformers

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Observation e1e05970-e027-4bbb-b696-698472925ad3 · outbound

This paper cites Musiq: Multi-scale image quality transformer.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Musiq: Multi-scale image quality transformer

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Observation 0d4714d8-7548-4eb4-b333-afe636b7e11e · outbound

This paper cites A nonparametric approach to bottom- 10 up visual saliency.Advances in neural information process- ing systems, 19, 2006.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer A nonparametric approach to bottom- 10 up visual saliency.Advances in neural information process- ing systems, 19, 2006

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Observation 600f4bfc-e528-40ef-b9f0-4f55c436e1a5 · outbound

This paper cites Diffusehigh: Training-free progressive high- resolution image synthesis through structure guidance.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Diffusehigh: Training-free progressive high- resolution image synthesis through structure guidance

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Observation 5a831529-3082-4b98-8607-96844a6a58f2 · outbound

This paper cites Imagenet classification with deep convolutional neural net- works.Advances in neural information processing systems, 25, 2012.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Imagenet classification with deep convolutional neural net- works.Advances in neural information processing systems, 25, 2012

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Observation d04ba5e9-6847-447a-a7d8-02b12a54dd91 · outbound

This paper cites Deepfix: A fully convolutional neural network for predicting human eye fixations.IEEE Transactions on Im- age Processing, 26(9):4446–4456, 2017.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Deepfix: A fully convolutional neural network for predicting human eye fixations.IEEE Transactions on Im- age Processing, 26(9):4446–4456, 2017

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Observation 2ae04c54-a66e-4d87-b5fe-70fcc2d615c1 · outbound

This paper cites Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet

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Observation fac82765-f947-49f6-b157-68ea30780dc9 · outbound

This paper cites Flux.1 kontext: Flow matching for in-context image generation and editing in latent space, 2025.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Flux.1 kontext: Flow matching for in-context image generation and editing in latent space, 2025

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Observation e89e2380-e22a-43ab-8d62-db81ad126e7e · outbound

This paper cites Efficient Scaling of Diffusion Transformers for Text-to-Image Generation.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Efficient Scaling of Diffusion Transformers for Text-to-Image Generation

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Observation c4fe7fb6-23de-4a0f-bf49-78cbefad256a · outbound

This paper cites Svdquant: Absorbing outliers by low- rank components for 4-bit diffusion models.arXiv preprint arXiv:2411.05007, 2024.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Svdquant: Absorbing outliers by low- rank components for 4-bit diffusion models.arXiv preprint arXiv:2411.05007, 2024

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Observation 82cc4082-8d26-4b12-81c4-ecef451579e8 · outbound

This paper cites Snapfusion: Text-to-image diffusion model on mobile de- vices within two seconds.Advances in Neural Information Processing Systems, 36:20662–20678, 2023.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Snapfusion: Text-to-image diffusion model on mobile de- vices within two seconds.Advances in Neural Information Processing Systems, 36:20662–20678, 2023

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Observation 001e6a19-564b-40af-aef8-eb00406fd66b · outbound

This paper cites Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:31.643191Z

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Observation f325ef30-433a-4cfe-a48a-9486290203bc · outbound

This paper cites Microsoft coco: Common objects in context.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Microsoft coco: Common objects in context

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Observation 20da9d7f-3dea-4ca2-9fd8-cdbd06dac9af · outbound

This paper cites Deepgaze iie: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Deepgaze iie: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:31.894657Z

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Observation 33e8180f-4855-4242-861a-8623b62671ea · outbound

This paper cites Deepgaze iie: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Deepgaze iie: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling

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Observation 3ca96e00-8c93-4b9f-b8a6-b616f38bb42b · outbound

This paper cites Timestep embedding tells: It’s time to cache for video diffusion model.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Timestep embedding tells: It’s time to cache for video diffusion model

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Source-reported events for the cited work

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Observation 03de78ed-b131-443d-8cea-80a3517d048e · outbound

This paper cites A deep spatial contextual long- term recurrent convolutional network for saliency detec- tion.IEEE Transactions on Image Processing, 27(7):3264– 3274, 2018.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer A deep spatial contextual long- term recurrent convolutional network for saliency detec- tion.IEEE Transactions on Image Processing, 27(7):3264– 3274, 2018

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Observation e5405504-91a3-4605-9e65-3464cc9dbd0b · outbound

This paper cites Region-adaptive sampling for diffusion transformers.arXiv preprint arXiv:2502.10389, 2025.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Region-adaptive sampling for diffusion transformers.arXiv preprint arXiv:2502.10389, 2025

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Observation 6afdf2cb-377b-4aa2-b498-c065d578fc41 · outbound

This paper cites Transalnet: Towards perceptually relevant visual saliency prediction.Neurocomputing, 494:455–467,.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Transalnet: Towards perceptually relevant visual saliency prediction.Neurocomputing, 494:455–467,

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Observation b586c417-93e3-4c4e-9dc5-9649d0600ded · outbound

This paper cites Token caching for diffusion transformer accel- eration.arXiv preprint arXiv:2409.18523, 2024.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Token caching for diffusion transformer accel- eration.arXiv preprint arXiv:2409.18523, 2024

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:32.551857Z

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Observation 89ea124f-8d33-4c80-aa5a-6eb4ed223bad · outbound

This paper cites Dpm-solver: A fast ode solver for diffu- sion probabilistic model sampling in around 10 steps.Ad- vances in neural information processing systems, 35:5775– 5787, 2022.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Dpm-solver: A fast ode solver for diffu- sion probabilistic model sampling in around 10 steps.Ad- vances in neural information processing systems, 35:5775– 5787, 2022

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:32.627689Z

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Observation df1ce7f7-9112-4057-83da-c3de12473991 · outbound

This paper cites Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models.Machine Intel- ligence Research, pages 1–22, 2025.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models.Machine Intel- ligence Research, pages 1–22, 2025

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Source-reported events for the cited work

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Observation f64126a2-b27a-449b-8818-07cfecbbca4b · outbound

This paper cites FiT: Flexible Vision Transformer for Diffusion Model.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer FiT: Flexible Vision Transformer for Diffusion Model

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:32.838768Z

Source-reported events for the cited work

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Observation 0d3fdb25-7947-4c8d-a7b7-cb140fa83d97 · outbound

This paper cites Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:32.920590Z

Source-reported events for the cited work

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Observation 883b67b1-ee34-4df6-95a6-472c4a70a443 · outbound

This paper cites FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality

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Source-reported events for the cited work

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Observation ee4ec104-5a3d-4396-8999-cca2cc647b36 · outbound

This paper cites Video saliency forecasting transformer.IEEE transactions on circuits and systems for video technology, 32(10):6850–6862, 2022.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Video saliency forecasting transformer.IEEE transactions on circuits and systems for video technology, 32(10):6850–6862, 2022

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:33.030512Z

Source-reported events for the cited work

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Observation 98cc296d-39f4-4339-b1be-0c7cea862a45 · outbound

This paper cites Learning-to-cache: Accelerating diffusion trans- former via layer caching.Advances in Neural Information Processing Systems, 37:133282–133304, 2024.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Learning-to-cache: Accelerating diffusion trans- former via layer caching.Advances in Neural Information Processing Systems, 37:133282–133304, 2024

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:33.116605Z

Source-reported events for the cited work

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Observation 01d30cb4-c66b-4087-a6b1-a0e62464c120 · outbound

This paper cites Deepcache: Accelerating diffusion models for free.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Deepcache: Accelerating diffusion models for free

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:33.252340Z

Source-reported events for the cited work

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Observation 484e2779-171b-4140-b1c7-e6fe2678e603 · outbound

This paper cites Latte: Latent Diffusion Transformer for Video Generation.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Latte: Latent Diffusion Transformer for Video Generation

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:33.319218Z

Source-reported events for the cited work

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Observation d25ffed7-2d32-4c7c-b8a8-4693e20ad475 · outbound

This paper cites Magcache: Fast video generation with magnitude- aware cache.arXiv preprint arXiv:2506.09045, 2025.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Magcache: Fast video generation with magnitude- aware cache.arXiv preprint arXiv:2506.09045, 2025

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:33.426515Z

Source-reported events for the cited work

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Observation a7c2cf35-981b-40a3-b56e-b167401d6275 · outbound

This paper cites LieRE: Lie Rotational Positional Encodings.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer LieRE: Lie Rotational Positional Encodings

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:33.510808Z

Source-reported events for the cited work

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Observation dc8b98ff-ce4a-4a2d-bcd6-fa3ad6a06555 · outbound

This paper cites Scalable diffusion mod- els with transformers.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Scalable diffusion mod- els with transformers

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:33.662966Z

Source-reported events for the cited work

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Observation 3f0bc936-b6ed-40cb-b2bc-96eb100559d9 · outbound

This paper cites Ntk-aware scaled rope allows llama models to have extended (8k+) context size without any fine-tuning and minimal perplexity degrada- tion, 2023.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Ntk-aware scaled rope allows llama models to have extended (8k+) context size without any fine-tuning and minimal perplexity degrada- tion, 2023

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:33.839699Z

Source-reported events for the cited work

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Observation 7acbadee-78d0-4b3e-ab79-71a90e569547 · outbound

This paper cites YaRN: Efficient Context Window Extension of Large Language Models.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer YaRN: Efficient Context Window Extension of Large Language Models

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:33.948881Z

Source-reported events for the cited work

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Observation 4381c461-4fd7-47eb-bc14-b5188c581c79 · outbound

This paper cites Wuerstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Wuerstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:34.111709Z

Source-reported events for the cited work

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Observation 3713926a-4465-4e44-9092-995673139acc · outbound

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

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:34.229570Z

Source-reported events for the cited work

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Observation da37359e-8e51-42a0-a18e-aead4df6f9cc · outbound

This paper cites Video motion transfer with diffusion transformers.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Video motion transfer with diffusion transformers

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Source-reported events for the cited work

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Observation bc663ef4-c0fc-4c63-8195-2921165c76cd · outbound

This paper cites Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13039da8-6b1c-4595-a602-72480932028e · outbound

This paper cites CineScale: Free Lunch in High-Resolution Cinematic Visual Generation.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer CineScale: Free Lunch in High-Resolution Cinematic Visual Generation

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Source-reported events for the cited work

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Observation 89bab8a5-c88d-46ef-844a-89cf0a7fa820 · outbound

This paper cites Freescale: Unleashing the resolution of diffusion mod- els via tuning-free scale fusion.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Freescale: Unleashing the resolution of diffusion mod- els via tuning-free scale fusion

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2295b7ac-8185-43c4-a9b7-df3ad4ed4ab2 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Learn- ing transferable visual models from natural language super- vision

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:34.747012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14e76cb2-00d3-425c-9c4f-7b750957498c · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer SAM 2: Segment Anything in Images and Videos

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:34.898300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d77bf99-93e8-4681-9931-55517ce6c520 · outbound

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

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer High-resolution image synthesis with latent diffusion models

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b3dc856-a6ab-4b9e-adb0-6f8f94c9396d · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural in- formation processing systems, 35:36479–36494, 2022.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural in- formation processing systems, 35:36479–36494, 2022

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0cfa7333-14eb-4e27-bf43-41cb2ee2cfa0 · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Progressive Distillation for Fast Sampling of Diffusion Models

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Source-reported events for the cited work

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Observation b348a2c2-8752-421b-ba4d-59a4ee94ed26 · outbound

This paper cites Skrr: Skip and Re-use Text Encoder Layers for Memory Efficient Text-to-Image Generation.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Skrr: Skip and Re-use Text Encoder Layers for Memory Efficient Text-to-Image Generation

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7405d1a7-eb55-41b9-a805-f35dbe90a15b · outbound

This paper cites Post-training quantization on diffusion models.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Post-training quantization on diffusion models

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a2304ef-5e90-4ab0-86d5-1e419724144f · outbound

This paper cites DINOv3.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer DINOv3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 453e8f68-bf2a-4d2d-b1fb-9e17d941db41 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Very Deep Convolutional Networks for Large-Scale Image Recognition

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2048fbb-e6cc-477f-abb4-7b44fae98295 · outbound

This paper cites Denoising Diffusion Implicit Models.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Denoising Diffusion Implicit Models

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40868428-7d8b-44ff-a323-6185ac1ff1c7 · outbound

This paper cites Consistency Models.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Consistency Models

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:35.913201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bb7fe64-0adc-443c-aff9-4770f27f69de · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568: 127063, 2024.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568: 127063, 2024

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5904c76-8d9f-405f-84f7-29e461304773 · outbound

This paper cites A length-extrapolatable transformer.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer A length-extrapolatable transformer

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88bd2714-ba7c-4634-a4d8-d1705cc6c909 · outbound

This paper cites Exploring the deep fusion of large language models and diffusion transformers for text-to-image synthesis.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Exploring the deep fusion of large language models and diffusion transformers for text-to-image synthesis

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:36.264238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0162a3f4-26f2-4996-b7aa-0a5b26d00a8b · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Gemma: Open Models Based on Gemini Research and Technology

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