Paper Citation Record · LEDGER

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

As of 23 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 10 inbound Pith citation observations for arXiv:2602.10099.

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

pith.paper-citation-record.v1
2602.10099 v2

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T01:25:20.669732Z

measured 40 of 40 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:05:03.106403Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T15:38:33.091132Z

Reference resolution

30 of 30 outbound references displayed

verified exact0
verified fuzzy0
unresolved30
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c414567e-6bd5-4d0b-b158-59f04d859ef3 · outbound

This paper cites Building Normalizing Flows with Stochastic Interpolants.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Building Normalizing Flows with Stochastic Interpolants

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:17.458196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58183840-cbc9-43e1-9211-a898cf2618d1 · outbound

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

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders MDTv2: Masked Diffusion Transformer is a Strong Image Synthesizer

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:17.988811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b9c539e-fd14-451c-b761-35959c8aebef · outbound

This paper cites Scalable Adaptive Computation for Iterative Generation.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Scalable Adaptive Computation for Iterative Generation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:18.304484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 930a2b28-873c-4d75-af8e-f76aed292e40 · outbound

This paper cites Auto-Encoding Variational Bayes.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Auto-Encoding Variational Bayes

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:18.471858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7700bd73-61a1-45da-8724-23139655ff59 · outbound

This paper cites Repa-e: Unlocking vae for end-to-end tuning with latent diffusion transformers.arXiv preprint arXiv:2504.10483,.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Repa-e: Unlocking vae for end-to-end tuning with latent diffusion transformers.arXiv preprint arXiv:2504.10483,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:18.844250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4022457-828c-43ca-979b-e36958b2a273 · outbound

This paper cites Flow matching meets biology and life science: a survey.arXiv preprint arXiv:2507.17731,.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Flow matching meets biology and life science: a survey.arXiv preprint arXiv:2507.17731,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:18.948817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 962d1c2c-0165-4a7d-ae2f-22ae7dcc4871 · outbound

This paper cites Flow Matching for Generative Modeling.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Flow Matching for Generative Modeling

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:19.044725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ddad068-87fb-4570-a681-3ca918980259 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:19.211343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43c44386-2072-4e4d-919f-13637c9ba042 · outbound

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

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders DINOv2: Learning Robust Visual Features without Supervision

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:19.298369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c85c86d4-7caf-4f1d-b37d-d48721fe8789 · outbound

This paper cites Semantics lead the way: Harmonizing semantic and texture modeling with asynchronous latent diffusion.arXiv preprint arXiv:2512.04926,.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Semantics lead the way: Harmonizing semantic and texture modeling with asynchronous latent diffusion.arXiv preprint arXiv:2512.04926,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:19.376198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4f08cea-1ab8-47ce-a24f-041952cfa32d · outbound

This paper cites The Intrinsic Dimension of Images and Its Impact on Learning.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders The Intrinsic Dimension of Images and Its Impact on Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:19.486213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63c912a2-0d18-46ff-8ba1-2209d3fe4efb · outbound

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

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Score-Based Generative Modeling through Stochastic Differential Equations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:19.654186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd63506a-1ecf-4069-97fa-70108a5772f9 · outbound

This paper cites Represen- tation entanglement for generation: Training diffusion transformers is much easier than you think.arXiv preprint arXiv:2507.01467,.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Represen- tation entanglement for generation: Training diffusion transformers is much easier than you think.arXiv preprint arXiv:2507.01467,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:19.809711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e601d539-2c0d-4786-a7fa-29b5e976a89f · outbound

This paper cites Fast protein backbone generation with SE(3) flow matching.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Fast protein backbone generation with SE(3) flow matching

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:19.975899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fc8c8bc-3666-447b-a5b4-0bf62c2af5fe · outbound

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

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:20.038005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 053033eb-5afa-478c-a1b3-5fc4a8dd9a1f · outbound

This paper cites an unresolved cited work.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:20.162558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 489428bc-d619-4cc6-b733-425431578899 · outbound

This paper cites Diffusion Transformers with Representation Autoencoders.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Diffusion Transformers with Representation Autoencoders

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:20.278991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de8052a5-d3d6-4468-a7ba-8a3cf75730a6 · outbound

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

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Fast Training of Diffusion Models with Masked Transformers

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:20.415023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 980aa1fb-c98e-4f79-aaa1-aa3f53ba27a0 · outbound

This paper cites an unresolved cited work.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:20.488954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20927835-6509-4759-899a-a454d5e62652 · outbound

This paper cites an unresolved cited work.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:20.603230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3166030-8cae-4a42-8e17-1e7c93511d02 · outbound

This paper cites Standard FM constructs probability paths via linear interpolation in Euclidean space, regressing a velocity field to guide samples from a source distribution to the data.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Standard FM constructs probability paths via linear interpolation in Euclidean space, regressing a velocity field to guide samples from a source distribution to the data

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:20.666077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb4c80f8-39b5-4109-ac79-b95ecf17e053 · outbound

This paper cites an unresolved cited work.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:20.669732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 739e2641-4995-4230-b847-f52a23c84321 · outbound

This paper cites 9 Kouzelis, T., Karypidis, E., Kakogeorgiou, I., Gidaris, S., and Komodakis, N.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders 9 Kouzelis, T., Karypidis, E., Kakogeorgiou, I., Gidaris, S., and Komodakis, N

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:18.600301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6185bba6-5d86-4144-a674-ab4700807a58 · outbound

This paper cites Latent diffusion model without variational autoencoder.arXiv preprint arXiv:2510.15301,.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Latent diffusion model without variational autoencoder.arXiv preprint arXiv:2510.15301,

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:19.569478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2bb4f0e-3be0-4f65-8f2e-70ad8a9a946f · outbound

This paper cites Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:18.188399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eda630be-4b6e-4800-ad88-7fa0895801be · outbound

This paper cites PixNerd: Pixel Neural Field Diffusion.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders PixNerd: Pixel Neural Field Diffusion

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:19.705115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0caa131-570b-445a-89ad-9b7ad40d240f · outbound

This paper cites SE(3)-Stochastic Flow Matching for Protein Backbone Generation.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders SE(3)-Stochastic Flow Matching for Protein Backbone Generation

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:17.591097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39c7df84-4c10-46fe-a1a4-c25de5e9be75 · outbound

This paper cites PixelFlow: Pixel-Space Generative Models with Flow.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders PixelFlow: Pixel-Space Generative Models with Flow

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:17.920187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02b7d741-2aa1-48d3-8647-843c9bdeb8a1 · outbound

This paper cites Flow Matching on General Geometries.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Flow Matching on General Geometries

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:17.735813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9f3d890-97e3-4883-9133-d3000e38b020 · outbound

This paper cites A., Hu, V.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders A., Hu, V

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T01:25:18.724656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 0e727666-8cc9-48e4-aa3a-65241a5f8d23 · inbound

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

Aligning Latent Geometry for Spherical Flow Matching in Image Generation Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:18.364333Z

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.

Observation 13d7dae4-76bf-4b83-badd-41cdbafc3715 · inbound

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

RiT: Vanilla Diffusion Transformers Suffice in Representation Space Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:18.364333Z

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.

Observation 01986bf7-1538-4c38-9d6c-09f08596eb7c · inbound

RADAR: Relative Angular Divergence Across Representations cites this paper.

RADAR: Relative Angular Divergence Across Representations Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:18.364333Z

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.

Observation c629e20b-65d6-4f6f-98b7-687a8b94dcb9 · inbound

Geometry-Aware Representation Denoising for Robust Multi-view 3D Reconstruction cites this paper.

Geometry-Aware Representation Denoising for Robust Multi-view 3D Reconstruction Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:18.364333Z

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.

Observation baa6197c-38c9-4c47-a7f3-f5b2268596a4 · inbound

Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry cites this paper.

Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:18.364333Z

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.

Observation fa13c96b-2a64-4fe7-932c-01fabdcbf9f5 · inbound

Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry cites this paper.

Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:18.364333Z

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.

Observation 05f948e6-456a-4b1f-8e7d-1a416b52507b · inbound

STREAM: Stochastic Riemannian Flow Matching with Anisotropic Decoder for Digital Histopathology Image Generation cites this paper.

STREAM: Stochastic Riemannian Flow Matching with Anisotropic Decoder for Digital Histopathology Image Generation Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:18.364333Z

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.

Observation 0bffc623-12ab-479c-8529-707d76fd3664 · inbound

Understanding Geometric Representations in Self-Supervised Vision Transformers via Subspace Intervention cites this paper.

Understanding Geometric Representations in Self-Supervised Vision Transformers via Subspace Intervention Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:18.364333Z

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.

Observation b1c7e787-9e28-4427-9497-f7eb3f79c8a0 · inbound

Orbis 2: A Hierarchical World Model for Driving cites this paper.

Orbis 2: A Hierarchical World Model for Driving Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T22:05:03.106403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88c9440e-8d78-49ac-bb48-08962577f69a · inbound

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models cites this paper.

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T13:27:14.205124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.