Paper Citation Record · LEDGER

Masked Autoencoders Are Effective Tokenizers for Diffusion Models

As of 9 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 9 inbound Pith citation observations for arXiv:2502.03444.

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

pith.paper-citation-record.v1
2502.03444 v2

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T04:47:30.494924Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:12:35.779135Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:50:11.463918Z

Reference resolution

45 of 45 outbound references displayed

verified exact0
verified fuzzy6
unresolved36
parse uncertain0
malformed identifier1
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6d312cda-e11e-46ca-abe5-7d6bb89f6774 · outbound

This paper cites CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.300523Z

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Observation 315e1a6b-2f5c-467e-9166-774844a93d46 · outbound

This paper cites We use a classifier-free guidance scale of 2.0.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models We use a classifier-free guidance scale of 2.0

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:47:31.353123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c320df9f-cd57-4c37-a478-7d707f9ab734 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Imagenet: A large-scale hierarchical image database

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.315643Z

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Observation 9abfc1e2-5d1f-4142-a911-d84939b87c1a · outbound

This paper cites MDTv2: Masked Diffusion Transformer is a Strong Image Synthesizer.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models MDTv2: Masked Diffusion Transformer is a Strong Image Synthesizer

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.325347Z

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Observation 9fd820e9-6c9f-4c1d-ab9b-dc06f0d92388 · outbound

This paper cites Learning Mixtures of Gaussians Using Diffusion Models.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Learning Mixtures of Gaussians Using Diffusion Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.330316Z

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Observation 34a3c264-4b60-4807-8bb5-2c4553194f57 · outbound

This paper cites Rethinking the Objectives of Vector-Quantized Tokenizers for Image Synthesis.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Rethinking the Objectives of Vector-Quantized Tokenizers for Image Synthesis

Reference 11

Resolution: metadata mismatch; local_arxiv, observed 2026-08-09T04:47:31.134178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ef981338-a86b-4db4-a4ba-fe029231fdfb · outbound

This paper cites Auto-Encoding Variational Bayes.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Auto-Encoding Variational Bayes

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.352649Z

Source-reported events for the cited work

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Observation 3659ef7d-8169-4307-be1f-38c83d87caef · outbound

This paper cites Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.357328Z

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Observation ca61901c-c8ed-4221-8b40-163581a829ae · outbound

This paper cites Scalable autoregressive image generation with mamba.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Scalable autoregressive image generation with mamba

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.362139Z

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Observation 88c84e75-e3bf-4e02-9c0d-9be1286d50b3 · outbound

This paper cites MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.366749Z

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Observation 053c4ca8-c933-48e5-b03b-5a8c7e27cd38 · outbound

This paper cites Decoupled Weight Decay Regularization.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Decoupled Weight Decay Regularization

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.376382Z

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Observation 0a433903-6052-4c93-b615-41bf8acf14fb · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.385806Z

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Observation 2ee4a99d-0bbd-494a-9b1a-e028a53457a1 · outbound

This paper cites Improved Denoising Diffusion Probabilistic Models.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Improved Denoising Diffusion Probabilistic Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.390516Z

Source-reported events for the cited work

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Observation 1676abbe-ba08-44e0-820a-fb3536d78cfd · outbound

This paper cites Scalable Diffusion Models with Transformers.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Scalable Diffusion Models with Transformers

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.395192Z

Source-reported events for the cited work

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Observation bfbc628b-1402-4466-848a-af856d58595a · outbound

This paper cites TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.399979Z

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Unavailable: canonical work link unavailable.

Observation 2be2b9d3-15af-4ebb-b77f-ac0de51c7674 · outbound

This paper cites Generating Diverse High-Fidelity Images with VQ-VAE-2.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Generating Diverse High-Fidelity Images with VQ-VAE-2

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.404988Z

Source-reported events for the cited work

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Observation 0c90efcd-9360-477c-823a-011764809218 · outbound

This paper cites Deep Unsupervised Learning using Nonequilibrium Thermodynamics.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.410224Z

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Observation 7845f076-7985-4bf3-b12a-2c0f6a261ec7 · outbound

This paper cites Denoising Diffusion Implicit Models.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Denoising Diffusion Implicit Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.415234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0042ac06-01d5-435c-9301-8887c412a26f · outbound

This paper cites Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.420636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ae13516-c185-4215-a967-7403ede333d0 · outbound

This paper cites Regularizing Generative Adversarial Networks under Limited Data.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Regularizing Generative Adversarial Networks under Limited Data

Reference 30

Resolution: metadata mismatch; local_arxiv, observed 2026-08-09T04:47:30.672090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9c516e76-6e6f-4fdd-b728-951fc1a6e7c9 · outbound

This paper cites Score-based Generative Modeling in Latent Space.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Score-based Generative Modeling in Latent Space

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.429558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7d35cb9-8cda-4fba-b775-fdecb24ba814 · outbound

This paper cites Attention Is All You Need.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Attention Is All You Need

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.433779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bdb1c11-5e51-44e8-889d-93ead04943f4 · outbound

This paper cites VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.442646Z

Source-reported events for the cited work

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Observation 4975f68d-d73b-4453-ba8e-dd1a490ff62e · outbound

This paper cites Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.447243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 789bfca7-de10-42f5-9113-b2459896a84b · outbound

This paper cites Vector-quantized Image Modeling with Improved VQGAN.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Vector-quantized Image Modeling with Improved VQGAN

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.452091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f9e08ab-7385-45d3-8d59-89606488a16e · outbound

This paper cites Randomized Autoregressive Visual Generation.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Randomized Autoregressive Visual Generation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.456843Z

Source-reported events for the cited work

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Observation e9a29faf-4e30-48b8-973d-ebf8d3f21bbf · outbound

This paper cites The Unreasonable Effectiveness of Deep Features as a Perceptual Metric.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.461611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d3811b7-d03b-4fa6-9681-480d2b127e50 · outbound

This paper cites Scaling the Codebook Size of VQGAN to 100,000 with a Utilization Rate of 99%.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Scaling the Codebook Size of VQGAN to 100,000 with a Utilization Rate of 99%

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.466469Z

Source-reported events for the cited work

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Observation 6e725b27-a52b-4da1-883d-cbc5aafd01f2 · outbound

This paper cites We use a classifier-free guidance scale of 2.0.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models We use a classifier-free guidance scale of 2.0

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:47:31.336142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ea03c417-bd11-4343-8e02-e564b5aab4e5 · outbound

This paper cites The maximum mean norm of the GMM in GMM 9 is bounded as: maxi ∥µi∥ ≤B.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models The maximum mean norm of the GMM in GMM 9 is bounded as: maxi ∥µi∥ ≤B

Reference 42

Resolution: malformed identifier; raw_fallback, observed 2026-08-09T04:47:31.320117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a53ad343-15a8-4942-b1db-7bb10809d55d · outbound

This paper cites In the practical sampling process, we adopt an early stopping strategy to improve the generation quality.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models In the practical sampling process, we adopt an early stopping strategy to improve the generation quality

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:47:31.304732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5d3181e5-2e0c-4a4a-9cf4-19b46a46baba · outbound

This paper cites Training Details of Diffusion Models We present the training details of SiT-XL and LightningDiT in Tables 8 and 9, which mainly follows their original setup.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Training Details of Diffusion Models We present the training details of SiT-XL and LightningDiT in Tables 8 and 9, which mainly follows their original setup

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:47:31.289147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8e55d054-6c21-4d98-9a48-7c40f22e0da3 · outbound

This paper cites However, it is still extremely difficult to tune the guidance scale.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models However, it is still extremely difficult to tune the guidance scale

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:47:31.273750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a20dbb75-36c4-4e3b-9cae-5272442fb366 · outbound

This paper cites Causal Diffusion Transformers for Generative Modeling.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Causal Diffusion Transformers for Generative Modeling

Reference 2005

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.310301Z

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Observation e36ec6ca-3dd3-4f37-a2c6-5abd453e03b0 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Classifier-Free Diffusion Guidance

Reference 2006

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.338682Z

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Observation 9a160977-3b0c-4400-874c-3912974a14f7 · outbound

This paper cites MaskBit: Embedding-free Image Generation via Bit Tokens.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models MaskBit: Embedding-free Image Generation via Bit Tokens

Reference 2008

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.438125Z

Source-reported events for the cited work

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Observation 51b913ed-3f84-47ad-ac19-9eda566c17f7 · outbound

This paper cites Customize Your Visual Autoregressive Recipe with Set Autoregressive Modeling.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Customize Your Visual Autoregressive Recipe with Set Autoregressive Modeling

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.371836Z

Source-reported events for the cited work

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Observation 7a95c3cd-3a25-4e98-a7a1-e6a11eefd6d4 · outbound

This paper cites SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.381159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31e2148c-9c66-4b9c-a47c-a060c0486208 · outbound

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

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Image-to-Image Translation with Conditional Adversarial Networks

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.342780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5eaf9259-0ec0-4663-813e-57d3c40d5615 · outbound

This paper cites Guiding a Diffusion Model with a Bad Version of Itself.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Guiding a Diffusion Model with a Bad Version of Itself

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.347845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8cca33ac-068e-4140-9d17-48f02b7732b5 · outbound

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

Masked Autoencoders Are Effective Tokenizers for Diffusion Models An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.320373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83404af6-721b-4943-aeed-36ae6ac0d05f · outbound

This paper cites MaskGIT: Masked Generative Image Transformer.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models MaskGIT: Masked Generative Image Transformer

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.283979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be54b425-21eb-4843-b885-592c25502b3c · outbound

This paper cites SoftVQ-VAE: Efficient 1-Dimensional Continuous Tokenizer.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models SoftVQ-VAE: Efficient 1-Dimensional Continuous Tokenizer

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.290200Z

Source-reported events for the cited work

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Observation 71d0b6c1-6bc6-4407-bb9f-b9a987532ae2 · outbound

This paper cites and Triggs, B.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models and Triggs, B

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:47:31.378624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3cd3ba6e-4080-43b1-828f-b5e18f19838f · outbound

This paper cites Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models.

Masked Autoencoders Are Effective Tokenizers for Diffusion Models Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-09T04:47:30.295488Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation 09e89c9d-4461-4f07-b14a-1ef1dc47bfe1 · inbound

Physics-Informed Distillation of Diffusion Models for PDE-Constrained Generation cites this paper.

Physics-Informed Distillation of Diffusion Models for PDE-Constrained Generation Masked Autoencoders Are Effective Tokenizers for Diffusion Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T13:12:35.779135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc96ed1b-a237-4583-bd10-bb1af9f6da46 · inbound

Adaptive Mask-guided K-space Diffusion for Accelerated MRI Reconstruction cites this paper.

Adaptive Mask-guided K-space Diffusion for Accelerated MRI Reconstruction Masked Autoencoders Are Effective Tokenizers for Diffusion Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T23:28:32.384911Z

Source-reported events for the cited work

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Observation 137e2f05-51d3-4712-84a0-7b96c1511d17 · inbound

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer cites this paper.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Masked Autoencoders Are Effective Tokenizers for Diffusion Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T19:41:23.628002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c09e4615-7060-4e87-b943-575ace00a510 · inbound

VibeToken: Scaling 1D Image Tokenizers and Autoregressive Models for Dynamic Resolution Generations cites this paper.

VibeToken: Scaling 1D Image Tokenizers and Autoregressive Models for Dynamic Resolution Generations Masked Autoencoders Are Effective Tokenizers for Diffusion Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:11.648909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f8443c64-a3fa-43e1-811f-321cf04f6d35 · inbound

What Matters for Diffusion-Friendly Latent Manifold? Prior-Aligned Autoencoders for Latent Diffusion cites this paper.

What Matters for Diffusion-Friendly Latent Manifold? Prior-Aligned Autoencoders for Latent Diffusion Masked Autoencoders Are Effective Tokenizers for Diffusion Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:05:57.608936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3f86571b-014d-4824-af0c-f2585530ecbe · inbound

Structure over Pixels: Learning Variable-Length Visual Programs cites this paper.

Structure over Pixels: Learning Variable-Length Visual Programs Masked Autoencoders Are Effective Tokenizers for Diffusion Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-06-29T18:13:49.025604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6ab563c2-edc8-4d08-a21e-3afb9d76a152 · inbound

BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation cites this paper.

BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation Masked Autoencoders Are Effective Tokenizers for Diffusion Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-04T01:19:21.135295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5bc0004d-beb8-490a-84fe-e00b9c9924c4 · inbound

BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation cites this paper.

BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation Masked Autoencoders Are Effective Tokenizers for Diffusion Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T10:53:54.467279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab64295f-cce5-480c-a75a-0eaca0356265 · inbound

MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation cites this paper.

MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation Masked Autoencoders Are Effective Tokenizers for Diffusion Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-04T20:50:11.467934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.