Pith. sign in

Paper Citation Record · LEDGER

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

As of 23 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 24 inbound Pith citation observations for arXiv:2502.09509.

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

pith.paper-citation-record.v1
2502.09509 v3

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T21:17:56.000091Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:51:23.270869Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

22 of 22 outbound references displayed

  • verified exact1
  • verified fuzzy4
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 3293cdab-b7d3-4552-a26b-78bb8481f3fb · outbound

This paper cites HexaConv.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling HexaConv

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.940817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.940817Z digest=sha256:d58eba337dc2cf382e0ab27913ddc1151e9091ce673d48d1f3c8f523b25e23c8

Observation f1c94546-7516-49c9-bef2-f5e81bda5552 · outbound

This paper cites Exploring the Representation Manifolds of Stable Diffusion Through the Lens of Intrinsic Dimension.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Exploring the Representation Manifolds of Stable Diffusion Through the Lens of Intrinsic Dimension

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.947624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.947624Z digest=sha256:18e673be76829901c15ee703545605df135fb15045f52e7b73290a573e91f404

Observation 6568808b-1e99-49bf-ba5e-39682e750b89 · outbound

This paper cites Autoregressive Image Generation without Vector Quantization.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Autoregressive Image Generation without Vector Quantization

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.950672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.950672Z digest=sha256:0dbf105263c659bb707e771d2d6805b91c91e698bd0c8969b7403429646e5826

Observation 10cd0c43-0c97-4a1f-becb-e3155bef9c2f · outbound

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

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.970546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.970546Z digest=sha256:79ecc7fee04321f47ee77704daa17cfb7388b313eb1ae0d8453130233ccd3c31

Observation 9a02b24a-7b41-4465-a473-9e6fcfb9b7c4 · outbound

This paper cites Scaling Autoregressive Models for Content-Rich Text-to-Image Generation.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.978646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.978646Z digest=sha256:550e05ef58b1cc2083b834b415f00eb227f60abf78503e6c20b81df18abf7257

Observation 001834eb-dab0-447b-82ee-3f5c530f4a75 · outbound

This paper cites Fast Training of Diffusion Models with Masked Transformers.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Fast Training of Diffusion Models with Masked Transformers

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.982594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.982594Z digest=sha256:332e3684b2303c163ecb835aa770a5b152f8f97730e0adca0e3683a5fe8c274c

Observation 4cf0365a-9643-40ff-9907-d344601d9ed7 · outbound

This paper cites Designing a Better Asymmetric VQGAN for StableDiffusion.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Designing a Better Asymmetric VQGAN for StableDiffusion

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.986404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.986404Z digest=sha256:1a64cc7076b659af2a0e78d1240eb0e2484d53a45b05f7dd46832ac7b205b57d

Observation 73733df8-a88e-4414-ac22-6006c465fc8d · outbound

This paper cites We perform two experiments, with lower (pα = 0.7) and higher (pα = 0.3) regularization strength.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling We perform two experiments, with lower (pα = 0.7) and higher (pα = 0.3) regularization strength

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:17:56.412527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T21:17:55.990161Z digest=sha256:fa534b6daa06b8eab55ecb77631c0c63d1b96ac8ed9c158af4cb0addf3a86b28

Observation 58016da2-31ca-4c92-93f0-f009d6ca9574 · outbound

This paper cites Further Pope et al.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Further Pope et al

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:17:56.401899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T21:17:55.993692Z digest=sha256:7a32881ccc2277a7fc8961c243bf0f5a19b4ae07ce04afdbd99f3e3c83f0a076

Observation e4c0cf14-4219-4aaf-864a-23b7cfb52b53 · outbound

This paper cites The distance is calculated based on the assumption that both feature distributions follow multivariate Gaussian distributions.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling The distance is calculated based on the assumption that both feature distributions follow multivariate Gaussian distributions

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:17:56.391326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T21:17:55.996870Z digest=sha256:8ee73dfeb632e8d6aa55e89f54135f450b7fe46c3cded2bfdc3519794c9e5461

Observation 0a4660fa-8b9f-49c9-84d1-ab148aade7d3 · outbound

This paper cites • LDM (Rombach et al.,.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling • LDM (Rombach et al.,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:17:56.380946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T21:17:56.000091Z digest=sha256:ca852aaaf4846a2babe45ec6f84c70a3315fceb544a7f1f4a7602010b087d2d6

Observation ac7da854-6c8f-475b-a44c-c7ba2572e9ee · outbound

This paper cites Besnier, V.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Besnier, V

Reference 1969

Resolution
metadata mismatch
raw_fallback, observed 2026-08-07T21:17:56.370645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T21:17:55.922123Z digest=sha256:18a2a6743a8ff5e870f5797c7a42c98a70a3476bf5fdb766f87865e86b5a1881

Observation 62814c16-2e6c-4c5a-ab26-87ca0b9aa6fd · outbound

This paper cites Weiler, M.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Weiler, M

Reference 2004

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.974389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.974389Z digest=sha256:95f2df7a7d76bb89eeecaae1ca2a8ad81ad58c296b2346ca090a09dd5b93fbcc

Observation 7ff020ed-d55a-477b-a37c-882e363541fa · outbound

This paper cites Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.933753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.933753Z digest=sha256:9924258c35fc1a01a234b59056d39cb161883208c8f3789e2cfcbfa635042284

Observation 2b34da8c-626a-442d-b5c6-c4c3a1f8c517 · outbound

This paper cites Generating Images with Sparse Representations.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Generating Images with Sparse Representations

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.958323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.958323Z digest=sha256:bbe0c737cae9cd681d8f971c850353890a98e2680d9671cc218e0e4030400694

Observation fd14b472-53b0-4821-87b9-d8ac08e0460a · outbound

This paper cites N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials

Reference 2018

Resolution
verified exact
local_arxiv, observed 2026-08-07T21:17:56.232786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T21:17:55.944200Z digest=sha256:79f9e6b7f623a0138870eb638e502e0a84aad1fb7ce8df6d40d897bfd3f45258

Observation d4c6711a-02bc-4e77-adfd-7dee15b838fa · outbound

This paper cites Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.966350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.966350Z digest=sha256:ab6835e4aab33f9aa6f5b35ec7115d1b451bc574ba017ce00b5fdf126aec13d8

Observation 26375865-157e-497d-b98b-78cb5325ba9d · outbound

This paper cites Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.937448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.937448Z digest=sha256:fd50b7eec9935e8b4409823074ba2977c8d0e81eb3b18ec65b062d03626cc3bf

Observation 5010beac-9d75-43f1-b87d-1b20e8261e29 · outbound

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

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.962163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.962163Z digest=sha256:52507fcf433837367a1a2c6de2e35e0a5afc2cdc77c0f202a94a2da15c1b4d49

Observation 008983d2-3813-452e-aa2e-f52cdcbabe89 · outbound

This paper cites Does equivariance matter at scale?.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Does equivariance matter at scale?

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.926114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.926114Z digest=sha256:de53595a3fe1068327976f7d188c7eea13e384f22589fb5a0d90e11e82566753

Observation ee675217-16af-47b0-9cff-bc8ee61fa08e · outbound

This paper cites Adversarial Autoencoders.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Adversarial Autoencoders

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.954574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.954574Z digest=sha256:58a8bea6adaeaed50ebae38cb9b7774d432cd6e041e78065cb628b1d6e8bd023

Observation 970ba31e-105c-4228-a100-be60b69572e4 · outbound

This paper cites Bridging Information-Theoretic and Geometric Compression in Language Models.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Bridging Information-Theoretic and Geometric Compression in Language Models

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-07T21:17:55.929976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.929976Z digest=sha256:f0b80560d5fe515b4cdd8dc4ac4b2d6a5b373fe737e89fae4338a7f7e034c47e

Pith citing papers

Observation dcd4fb3c-42a0-40cb-a11d-d6321688b666 · inbound

Guiding a diffusion model using sliding windows cites this paper.

Guiding a diffusion model using sliding windows EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T19:51:59.191836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:51:59.191836Z digest=sha256:9265ab9cff3c7ae6aeb8deca18e64b259e802b62aa03679d7c604cb3f4a78737

Observation 742b78d0-1f0e-4998-9da2-cd7fb19cf4d7 · inbound

Enhancing Variational Autoencoders with Smooth Robust Latent Encoding cites this paper.

Enhancing Variational Autoencoders with Smooth Robust Latent Encoding EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-16T10:51:23.270869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:51:23.270869Z digest=sha256:efe0091815094a63c6335efd5fa97d3ccc66a655ede3261faa3d5ae788c4e5e6

Observation 2c85a68d-de1e-4786-9369-901e2dfd9854 · inbound

gen2seg: Generative Models Enable Generalizable Instance Segmentation cites this paper.

gen2seg: Generative Models Enable Generalizable Instance Segmentation EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-22T14:31:40.534490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T14:31:30.651144Z digest=sha256:9d8c4ee9a219b3c44afebf3fd2b223a5d30e409c468eadf1e5fa19c8a496836f

Observation 0673e2a8-10d0-4dda-87d0-87f2219cf382 · inbound

Latent Wavelet Diffusion For Ultra-High-Resolution Image Synthesis cites this paper.

Latent Wavelet Diffusion For Ultra-High-Resolution Image Synthesis EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-19T12:02:16.774116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-19T12:00:37.025335Z digest=sha256:a3c4231edfe4318a02856b339c5be3a8c0c61e24637320ab041abd7445f6c58a

Observation bd5e9a2a-7a40-4abb-afe2-c15c61c7db04 · inbound

Improving Progressive Generation with Decomposable Flow Matching cites this paper.

Improving Progressive Generation with Decomposable Flow Matching EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T18:32:57.085748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:32:57.085748Z digest=sha256:c9c5d600ddf4f8fdd24843c57df49bdbd85e30d99469339d841980c1ba1dc0f6

Observation e67ccd6d-7d0e-4b40-a0d8-b9e0fb5d1ec2 · inbound

Re-Bottleneck: Latent Re-Structuring for Neural Audio Autoencoders cites this paper.

Re-Bottleneck: Latent Re-Structuring for Neural Audio Autoencoders EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T18:36:58.824650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:36:58.824650Z digest=sha256:6c30cddb33c654c9e434920614cb48fc00d645817239816d93bfd8cfc554a21d

Observation 41df94a4-bf91-4780-aea3-c3af2880343a · inbound

Decoupling High and Low Frequencies for Faithful Image Generation with Fine Details cites this paper.

Decoupling High and Low Frequencies for Faithful Image Generation with Fine Details EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-05T05:27:34.250710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T05:27:34.250710Z digest=sha256:a23af8c8f4c44d69d5557f7facca9b2f873066d85adb78c303fec2d2d7d0bcba

Observation 41e8d3c3-e335-4503-94a8-2a90d50b1526 · inbound

Home-made Diffusion Model from Scratch to Hatch cites this paper.

Home-made Diffusion Model from Scratch to Hatch EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-05T04:34:36.948415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T04:34:36.948415Z digest=sha256:0ac0963c37425648a8e7a0df8adf9c631ef452edeb7750f9ab992fd84257870f

Observation 10d6f050-1204-424c-980a-507656d3a696 · inbound

VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models cites this paper.

VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-18T05:22:23.984698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T05:22:05.125849Z digest=sha256:404579064c052edf6742edcb120b26df478c4886600ec2fedc23c7b7fbaf9e5f

Observation 1a1f90c5-dde6-43fc-a18b-2cd940f0d3ea · inbound

Cloning Deterministic Worlds: The Critical Role of Latent Geometry in Long-Horizon World Models cites this paper.

Cloning Deterministic Worlds: The Critical Role of Latent Geometry in Long-Horizon World Models EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-18T02:50:48.250448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T02:50:32.870296Z digest=sha256:2be888a6ec71272a663e8d9366e46ae931cb0062571d69284e730f5cb073b355

Observation cd994553-0ebe-4463-99dc-22920d7adb13 · inbound

MPDiT: Multi-Patch Global-to-Local Transformer Architecture For Efficient Flow Matching and Diffusion Model cites this paper.

MPDiT: Multi-Patch Global-to-Local Transformer Architecture For Efficient Flow Matching and Diffusion Model EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-14T23:48:19.351048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-14T23:46:25.197344Z digest=sha256:ebb1d785ff7bce1279447236ba259768b61a650d0f9c1aea3e5b618b7af7b282

Observation 961d1a1c-bc94-4681-b79d-a4240b50a5b8 · inbound

Representations Before Pixels: Semantics-Guided Hierarchical Video Prediction cites this paper.

Representations Before Pixels: Semantics-Guided Hierarchical Video Prediction EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:45:58.589165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T16:30:53.578491Z digest=sha256:e356990df00a5e68e17bb676916a7d8748482eaab8688017d881b5b3e53c1a2e

Observation 8df6adfa-b8a8-4906-a868-be8d7c4269c5 · 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 EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:05:57.569516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-11T01:57:24.033068Z digest=sha256:ec07601b2cc697752c25cff415fa835244f8b4cf0a3859f91ba5ee27486df9b0

Observation 3b05c9b0-5605-4a84-88e4-5ebb2c8a3ead · inbound

Transforming the Use of Earth Observation Data: Exascale Training of a Generative Compression Model with Historical Priors for up to 10,000x Data Reduction cites this paper.

Transforming the Use of Earth Observation Data: Exascale Training of a Generative Compression Model with Historical Priors for up to 10,000x Data Reduction EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-12T01:16:13.786880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-12T01:14:17.332353Z digest=sha256:63562f27e74adf8eb5702ce8e4ff555cfc1d4f95864f829d54dd8e67ca5c7e26

Observation 87935eb5-9b95-4163-9130-d0404adef319 · inbound

Aligning Latent Geometry for Spherical Flow Matching in Image Generation cites this paper.

Aligning Latent Geometry for Spherical Flow Matching in Image Generation EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-06-30T20:35:02.184746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T20:34:54.023368Z digest=sha256:f38569d572df6efc3d90cfbaff935466da6ce1f883ba7e43f87670fc6cb9697f

Observation c029ead1-642e-473d-8cc9-581b4d1971e7 · inbound

Vision Foundation Models as Generalist Tokenizers for Image Generation cites this paper.

Vision Foundation Models as Generalist Tokenizers for Image Generation EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:03:13.461031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T11:01:24.738195Z digest=sha256:8d56b52575bc8d9cb5e5ade7ca18176534870f9710c6764f6a1a853ad53901f7

Observation 0d4879a1-b83b-45bd-a588-3253e3c82fb2 · inbound

RiT: Vanilla Diffusion Transformers Suffice in Representation Space cites this paper.

RiT: Vanilla Diffusion Transformers Suffice in Representation Space EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-22T07:51:15.870921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T07:50:29.461854Z digest=sha256:1c15af4528a33d5ca9add6349902e71ec570684349aef91b7005edfdf93dc881

Observation caf9af1b-c7be-4667-b332-d70d7d5320d7 · inbound

How Neural Losses Shape VAE Latents cites this paper.

How Neural Losses Shape VAE Latents EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-06-28T19:42:35.983708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-28T18:54:10.394076Z digest=sha256:cf006676ba8e35be475080570e57d25af607dc88038cdf7ee875a2ea16e9e18f

Observation c3811cf6-6891-448a-9fee-d1f44aa90a4d · inbound

Diffusing in the Right Space: A Systematic Study of Latent Diffusability cites this paper.

Diffusing in the Right Space: A Systematic Study of Latent Diffusability EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:36:27.617939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-28T10:44:24.318786Z digest=sha256:753d6e53f9fa866970b2fbd769e34bf084b477df882228f9dd65ef1f832c146f

Observation 3ea43fca-cf87-44da-bcf8-8daffcc9ee77 · inbound

VOID: Defeating Unauthorized Mimicry in Latent Diffusion Models cites this paper.

VOID: Defeating Unauthorized Mimicry in Latent Diffusion Models EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-07-03T10:07:56.159940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-27T10:14:10.924755Z digest=sha256:b277449423d3209d9a5c85a9d5c99e874dd70a810c7c8f8349c024e0c382c048

Observation c7a48dc5-825c-4867-b020-687260a69c32 · inbound

DiffusionBench: On Holistic Evaluation of Diffusion Transformers cites this paper.

DiffusionBench: On Holistic Evaluation of Diffusion Transformers EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:59:58.014472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-26T00:06:11.951205Z digest=sha256:e27a3ee637ffb70bcbffc1c1ed9d4c464050708f79ad39a43e5dce7858726be5

Observation c9d88efc-8042-41fe-b144-27d5684158ab · inbound

ROMS-IMLE: A Minimalist Approach to Competitive Single-Step Generative Modelling cites this paper.

ROMS-IMLE: A Minimalist Approach to Competitive Single-Step Generative Modelling EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-01T12:48:16.605643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:48:16.605643Z digest=sha256:8dced4b84a287b91d11d3d3b1f571f84cbbbd6e1d9fad2264d263ea0d2168f1a

Observation 671b67c1-da57-4d1d-ae5c-3008ddd8b330 · inbound

AnchorMark: Robust Diffusion Watermarking via Latent-Space Rotation Synchrony cites this paper.

AnchorMark: Robust Diffusion Watermarking via Latent-Space Rotation Synchrony EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-01T05:53:54.980035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T05:53:54.980035Z digest=sha256:cc65d2d6b4b2445ae140fa82b52fe6e04c074c6eda4acc93ce405dfffbea32ec

Observation e35f4549-467c-4539-8475-c4a8a2511863 · inbound

SPAE: Spectrally Guided Autoencoder for Pretrained Visual Latents cites this paper.

SPAE: Spectrally Guided Autoencoder for Pretrained Visual Latents EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T00:24:07.114827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:24:07.114827Z digest=sha256:1489b134ac4b2d810fc18eec966945fbc7f66ffe4371d0f85c76c03853739ccf