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Paper Citation Record · LEDGER

Exploring Representation-Aligned Latent Space for Better Generation

As of 23 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 6 inbound Pith citation observations for arXiv:2502.00359.

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

pith.paper-citation-record.v1
2502.00359 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:22:41.760051Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:58:17.682502Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:59:58.186578Z

Reference resolution

25 of 25 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 63cbf281-9170-40aa-bf99-e3ccdc974c76 · outbound

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

Exploring Representation-Aligned Latent Space for Better Generation Imagenet: A large-scale hierarchical image database

Reference 4

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source=pdf_text observed=2026-08-09T19:22:41.650688Z digest=sha256:fc9e31c64c5359312330a6fe383ec15eb63ba7cf3ee6ff20d5e5fe331693ce21

Observation 12504990-287a-457e-9c7b-49da76e247e1 · outbound

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

Exploring Representation-Aligned Latent Space for Better Generation LTX-Video: Realtime Video Latent Diffusion

Reference 6

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source=pdf_text observed=2026-08-09T19:22:41.662040Z digest=sha256:16349f5c31c2e5dcba28c1efda3c7945aa1b1ae07aaaeb568abff8a9ecb74196

Observation 93346924-916f-44d6-abdc-67dd1712b7ec · outbound

This paper cites Scalable Adaptive Computation for Iterative Generation.

Exploring Representation-Aligned Latent Space for Better Generation Scalable Adaptive Computation for Iterative Generation

Reference 8

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source=pdf_text observed=2026-08-09T19:22:41.672852Z digest=sha256:12492ac274c4e69a0c805c0d0589995d9b3cb632b0d67b7a4835292f48747333

Observation 674b5536-579b-4ed4-91fd-a7a17b211f10 · outbound

This paper cites Calculate the value by sampling 10,000 samples from the ImageNet 256 × 256, encoded by V AE aligned with DINOv2-base.

Exploring Representation-Aligned Latent Space for Better Generation Calculate the value by sampling 10,000 samples from the ImageNet 256 × 256, encoded by V AE aligned with DINOv2-base

Reference 10

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raw_fallback, observed 2026-08-09T19:22:42.149858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T19:22:41.760051Z digest=sha256:1f848554e51d201e4ae8c459825c88597669eb22168035bd99d4b8a12474806b

Observation 8bfeee68-77e3-478d-bb90-dc568424a771 · outbound

This paper cites Autoregressive Image Generation without Vector Quantization.

Exploring Representation-Aligned Latent Space for Better Generation Autoregressive Image Generation without Vector Quantization

Reference 11

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source=pdf_text observed=2026-08-09T19:22:41.685911Z digest=sha256:be9917be98019070be2e7c7523a170b5281f813fd34a2c1b59585c65fa4a2a5d

Observation a0957f55-e720-4c4d-8c9e-0928a8d7310c · outbound

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

Exploring Representation-Aligned Latent Space for Better Generation SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 12

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source=pdf_text observed=2026-08-09T19:22:41.690401Z digest=sha256:fc0dce046764d06d60bd31d5a608bcbab435249ec7ac5805daf842156439ba23

Observation f5d1bc16-f266-4f5f-951b-2d02b1d10de9 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Exploring Representation-Aligned Latent Space for Better Generation DINOv2: Learning Robust Visual Features without Supervision

Reference 13

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source=pdf_text observed=2026-08-09T19:22:41.696022Z digest=sha256:ecc978e84403f8e9537e8c569bfc942e30bdb222f269e7c0c072cc9230b9b6e1

Observation 0e9e8d0e-0033-4cea-922d-42ae26b01b28 · outbound

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

Exploring Representation-Aligned Latent Space for Better Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 14

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source=pdf_text observed=2026-08-09T19:22:41.701679Z digest=sha256:95c99335c0265bb40494be02ae65937006c69a215a61faf0db34d88f531572de

Observation 71d1aeb2-f071-4903-ab3b-9d00165b04e8 · outbound

This paper cites LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models.

Exploring Representation-Aligned Latent Space for Better Generation LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models

Reference 16

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source=pdf_text observed=2026-08-09T19:22:41.712378Z digest=sha256:56b9bf8746c64a5a2415eea7d92c3d9e4a00ad0ee41f062257c547b6b2819dc7

Observation 52dda38f-990b-4a26-97da-d0070d79705c · outbound

This paper cites Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation.

Exploring Representation-Aligned Latent Space for Better Generation Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 17

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source=pdf_text observed=2026-08-09T19:22:41.717956Z digest=sha256:8c636f361cf58c195b0a8a31a559a12df51a5c649d6e97bd0598712734fc4f2a

Observation c67b4aee-f6e5-4bd8-b5a9-42e83c91cf93 · outbound

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

Exploring Representation-Aligned Latent Space for Better Generation Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 18

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source=pdf_text observed=2026-08-09T19:22:41.723340Z digest=sha256:69035eedf4e38c44ba6e43aa85d1ab2493e1777c91e22e4dfc6e1743ec7c71da

Observation 439dde91-1c3f-44a8-b470-9bf9dcc2a380 · outbound

This paper cites MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision.

Exploring Representation-Aligned Latent Space for Better Generation MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision

Reference 19

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source=pdf_text observed=2026-08-09T19:22:41.729335Z digest=sha256:c3d3059a1b73d6dced224a933fb369fc00d878a3c8844e0a7b0639debd1433d8

Observation 31528f0d-28b1-4a7f-84f0-173a35c0179a · outbound

This paper cites Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation.

Exploring Representation-Aligned Latent Space for Better Generation Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation

Reference 20

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source=pdf_text observed=2026-08-09T19:22:41.734531Z digest=sha256:54a139b1915e6ee5c5aa99026370b4c42c10936917640f410b6c81ca3cc160f5

Observation 03242a35-2836-41b3-9c80-66e4d92f781d · outbound

This paper cites Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think.

Exploring Representation-Aligned Latent Space for Better Generation Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think

Reference 21

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source=pdf_text observed=2026-08-09T19:22:41.740025Z digest=sha256:1fde9220eaff16160424de7a2e2d9295636f14b142057dcf2cb19af6ab6d2aa2

Observation 0d0e2bee-3335-45e8-9081-02557826392b · outbound

This paper cites Diffusion Models Need Visual Priors for Image Generation.

Exploring Representation-Aligned Latent Space for Better Generation Diffusion Models Need Visual Priors for Image Generation

Reference 22

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source=pdf_text observed=2026-08-09T19:22:41.744781Z digest=sha256:d54b0ca5ab22956f20a99eb2803733ec3fbc74f1148a62eb4c8297b793bc2959

Observation 16d2aec5-6f51-4f94-80f1-1848dff47a24 · outbound

This paper cites JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling.

Exploring Representation-Aligned Latent Space for Better Generation JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling

Reference 23

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source=pdf_text observed=2026-08-09T19:22:41.749891Z digest=sha256:b73a7303ee1dcd2fd262f56c9a57c752c69dc760f706df83889915a01e3cb97d

Observation eea0c7b9-9832-46ec-9bed-6bf4cc9eda5d · outbound

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

Exploring Representation-Aligned Latent Space for Better Generation Fast Training of Diffusion Models with Masked Transformers

Reference 24

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source=pdf_text observed=2026-08-09T19:22:41.755072Z digest=sha256:52235f728eb31d2e56e62895a722e823de9a95d81dac2b2be52d4c28378fef98

Observation f72f7fe7-501b-424b-99c2-7919a3b51070 · outbound

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

Exploring Representation-Aligned Latent Space for Better Generation Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models

Reference 2013

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source=pdf_text observed=2026-08-09T19:22:41.681542Z digest=sha256:35dcfeeb415d233e092bd3dfcf874bd11475dbac5030da41de93799205f79839

Observation aec24685-9e55-41d0-ab9a-c43d6a855762 · outbound

This paper cites Video Diffusion Models.

Exploring Representation-Aligned Latent Space for Better Generation Video Diffusion Models

Reference 2017

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source=pdf_text observed=2026-08-09T19:22:41.667667Z digest=sha256:d9bfd08dfcb72cac527d2646888fc67a343992d0b8cc70a71395627627b659cb

Observation 0120051d-4919-4507-9805-ac357a9835a3 · outbound

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

Exploring Representation-Aligned Latent Space for Better Generation Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

Reference 2018

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source=pdf_text observed=2026-08-09T19:22:41.644873Z digest=sha256:03e6ce10dc64a2faad3068a824daa228141478d92cb2bc6c93a079847aa1363a

Observation 4bcd7db4-3eca-4331-9add-4844bfe52a34 · outbound

This paper cites Scaling Properties of Diffusion Models for Perceptual Tasks.

Exploring Representation-Aligned Latent Space for Better Generation Scaling Properties of Diffusion Models for Perceptual Tasks

Reference 2019

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source=pdf_text observed=2026-08-09T19:22:41.707119Z digest=sha256:0d31c3c05d595dc0d647c1179dfc6da04f6141b752542dcaeecd953620850072

Observation 33e15fe3-6a11-4d0d-bf30-f4ea7eee12a4 · outbound

This paper cites Tutorial on Variational Autoencoders.

Exploring Representation-Aligned Latent Space for Better Generation Tutorial on Variational Autoencoders

Reference 2021

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source=pdf_text observed=2026-08-09T19:22:41.656173Z digest=sha256:c85eda7863ded168de1259085068e3e63b44d49f59cf799f4645fa78b530a1a0

Observation 6365c104-0626-4fcb-9981-b5cb951e9c31 · outbound

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

Exploring Representation-Aligned Latent Space for Better Generation Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models

Reference 2022

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source=pdf_text observed=2026-08-09T19:22:41.638981Z digest=sha256:3b06bb0df7825da8c3e32e105aaedcf19351f1192f81199e2ba303a0ab826eaf

Observation 27fa7a92-5543-44eb-b20c-d7e44b0de7cc · outbound

This paper cites Large Scale GAN Training for High Fidelity Natural Image Synthesis.

Exploring Representation-Aligned Latent Space for Better Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 2023

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source=pdf_text observed=2026-08-09T19:22:41.632902Z digest=sha256:d5c1f064926cca4928660425dd1defbc46a1dbda135d4f9ee28f1e8392dd83ab

Observation 38f0bdc0-8870-41ab-a8b4-96e014cfc2c4 · outbound

This paper cites Auto-Encoding Variational Bayes.

Exploring Representation-Aligned Latent Space for Better Generation Auto-Encoding Variational Bayes

Reference 2024

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source=pdf_text observed=2026-08-09T19:22:41.677178Z digest=sha256:05aa51accdb7aae0e894cb370e39af909fc80b5b70f4ad041e980ebba3b63784

Pith citing papers

Observation 0dd6dc30-0fe0-444c-b6ca-3130e387073a · inbound

Transition Models: Rethinking the Generative Learning Objective cites this paper.

Transition Models: Rethinking the Generative Learning Objective Exploring Representation-Aligned Latent Space for Better Generation

Reference 82

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source=pdf_text observed=2026-08-05T10:19:54.512634Z digest=sha256:f322b18e35b553b0d8965367eaf37ccd0b8fbfde03b4e215385b69527a5f620c

Observation 17175a59-0d92-4d26-b05f-4bb7254613a3 · 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 Exploring Representation-Aligned Latent Space for Better Generation

Reference 52

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source=arxiv_source observed=2026-08-05T05:27:34.339306Z digest=sha256:0ace76914e113405e34f4c2132035c343051d2e6907c550b69388bc49a9bb42e

Observation ea181610-5f1c-45d1-8912-b40ee9430c2c · inbound

InfGen: A Resolution-Agnostic Paradigm for Scalable Image Synthesis cites this paper.

InfGen: A Resolution-Agnostic Paradigm for Scalable Image Synthesis Exploring Representation-Aligned Latent Space for Better Generation

Reference 38

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source=pdf_text observed=2026-08-15T15:58:17.682502Z digest=sha256:8cb44ad246d5a92c21c53025abaf180de3b7ede5aefdf8bcd36c0fef5d09a826

Observation 59914ac4-4221-446a-a6eb-ef12ec9abfc4 · inbound

Align & Invert: Solving Inverse Problems with Diffusion and Flow-based Models via Representation Alignment cites this paper.

Align & Invert: Solving Inverse Problems with Diffusion and Flow-based Models via Representation Alignment Exploring Representation-Aligned Latent Space for Better Generation

Reference 15

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source=pdf_text observed=2026-08-03T21:07:15.084222Z digest=sha256:1a071a736dc92e44edac5aa16ad5ecc1a69486d2a9358d8828189ab98ae11899

Observation 57b58dde-6d0b-4931-9320-869291269e00 · inbound

Improved Baselines with Representation Autoencoders cites this paper.

Improved Baselines with Representation Autoencoders Exploring Representation-Aligned Latent Space for Better Generation

Reference 59

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arxiv_id, observed 2026-05-20T11:43:15.310707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-20T11:40:14.358108Z digest=sha256:1d9904f66588c0d9b4570d58a4abe1ece203f3fc821837c0639db8732ea2fe4b

Observation 14e7363e-f3cc-48bd-a964-02cf52b1e026 · inbound

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

DiffusionBench: On Holistic Evaluation of Diffusion Transformers Exploring Representation-Aligned Latent Space for Better Generation

Reference 156

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arxiv_id, observed 2026-07-04T16:59:58.188120Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-26T00:06:11.951205Z digest=sha256:88c4ecdae08c389d816bfdbe12f5cae6d41f792a245ea29ea27a7a71a5fc3fd0