Paper Citation Record · LEDGER

Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 28 inbound Pith citation observations for arXiv:2112.07804.

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

pith.paper-citation-record.v1
2112.07804 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:11:54.445934Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:29:45.256333Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0f516002-3b44-48c1-9288-7a306d8a37cb · inbound

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning cites this paper.

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:55:15.782473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 91d0e56d-d6d3-4f81-8e7b-f33537a3eb13 · inbound

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

Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 91

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:17:51.664048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bba59302-b0c3-456d-b249-635f2829a82d · inbound

Rectified Flow: A Marginal Preserving Approach to Optimal Transport cites this paper.

Rectified Flow: A Marginal Preserving Approach to Optimal Transport Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-18T03:03:13.975794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 08809f5c-61c1-499b-9a82-1df9d79d33d6 · inbound

The Score-Difference Flow for Implicit Generative Modeling cites this paper.

The Score-Difference Flow for Implicit Generative Modeling Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-24T08:59:14.762793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5d0cddde-8336-4304-b12f-5cd605d90bf0 · inbound

DOLLAR: Few-Step Video Generation via Distillation and Latent Reward Optimization cites this paper.

DOLLAR: Few-Step Video Generation via Distillation and Latent Reward Optimization Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-23T07:02:41.946971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 111df363-baec-49e0-898b-d4da4cfbe5de · inbound

Conditional diffusion model with spatial attention and latent embedding for medical image segmentation cites this paper.

Conditional diffusion model with spatial attention and latent embedding for medical image segmentation Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T14:11:54.445934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ed5f373-0ae7-4bc4-a159-f55f1e5d0ac5 · inbound

IMPLICITSTAINER: Resolution Agnostic Data-Efficient Virtual Staining Using Neural Implicit Functions cites this paper.

IMPLICITSTAINER: Resolution Agnostic Data-Efficient Virtual Staining Using Neural Implicit Functions Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:44:55.232410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a20ce9c6-56fc-40ff-a931-122c9e46c33e · inbound

Dual-Expert Consistency Model for Efficient and High-Quality Video Generation cites this paper.

Dual-Expert Consistency Model for Efficient and High-Quality Video Generation Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T11:14:09.657306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36a94131-da85-4349-8db8-d42984d445af · inbound

A Robust Local Fr\'echet Regression Using Unbalanced Neural Optimal Transport with Applications to Dynamic Single-cell Genomics Data cites this paper.

A Robust Local Fr\'echet Regression Using Unbalanced Neural Optimal Transport with Applications to Dynamic Single-cell Genomics Data Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T01:09:46.416990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 539aca7f-4579-4796-8a6e-6d4012b487d3 · inbound

WaFusion: A Wavelet-Enhanced Diffusion Framework for Face Morph Generation cites this paper.

WaFusion: A Wavelet-Enhanced Diffusion Framework for Face Morph Generation Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T17:09:21.801522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9c7931e-c766-4b5f-bf8a-d6ddaa55ca84 · inbound

fastWDM3D: Fast and Accurate 3D Healthy Tissue Inpainting cites this paper.

fastWDM3D: Fast and Accurate 3D Healthy Tissue Inpainting Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T16:35:28.752722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c295d35-cdb9-4c99-849b-64d00d4f924c · inbound

Turbulent Injection assisted by Diffusion Models for Scale Resolving Simulations cites this paper.

Turbulent Injection assisted by Diffusion Models for Scale Resolving Simulations Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T00:48:19.228197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6da39ede-b95a-4213-959b-5bfd1185d728 · inbound

Inference Time Debiasing Concepts in Diffusion Models cites this paper.

Inference Time Debiasing Concepts in Diffusion Models Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T18:47:20.825673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bdbf90e-032d-431f-9e62-92b35b2e4f32 · inbound

Quantum latent distributions in deep generative models cites this paper.

Quantum latent distributions in deep generative models Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-05T15:33:13.293815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 271f6304-8b54-4a8a-b82c-21f1957a3b3b · inbound

Friend or Foe cites this paper.

Friend or Foe Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-05T14:23:13.647639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f80a022f-8f06-4f89-93bd-2b909bf2e8ad · inbound

MiAD: Mirage Atom Diffusion for De Novo Crystal Generation cites this paper.

MiAD: Mirage Atom Diffusion for De Novo Crystal Generation Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T21:42:05.372038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ecd5d4b-1a6c-4aef-bc49-b849fb441aa4 · inbound

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation cites this paper.

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-02T23:59:17.581662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f80179ca-352f-43e2-9a19-4a23de118ed1 · inbound

DAG-STL: A Hierarchical Framework for Zero-Shot Trajectory Planning under Signal Temporal Logic Specifications cites this paper.

DAG-STL: A Hierarchical Framework for Zero-Shot Trajectory Planning under Signal Temporal Logic Specifications Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 80

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:21:03.234371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ddd1cb09-695e-4c79-9f18-098e8482683f · inbound

Efficient Diffusion Distillation via Embedding Loss cites this paper.

Efficient Diffusion Distillation via Embedding Loss Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:01:19.520441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 09e66cc3-a120-474d-b25e-2baf9058b394 · inbound

A Systematic Benchmark of Intraoperative Ultrasound-to-MR Synthesis for Brain Tumour Surgery cites this paper.

A Systematic Benchmark of Intraoperative Ultrasound-to-MR Synthesis for Brain Tumour Surgery Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:22:35.247868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7e236d92-e765-4165-b88b-eda91f87b8fe · inbound

The Reward Was in Your Data All Along: Correcting Flow Matching with Discriminator-Guided RL cites this paper.

The Reward Was in Your Data All Along: Correcting Flow Matching with Discriminator-Guided RL Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 162

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:49:19.327774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 289d70c7-9664-4fdd-ac00-7f2f4f4a4006 · inbound

Safe Few-Step Generation via Velocity Editing cites this paper.

Safe Few-Step Generation via Velocity Editing Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:29:45.257990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6b4119e8-cd42-4ae9-9c19-b151fde46af4 · inbound

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers cites this paper.

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-11T13:03:39.236118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93ebe841-75ab-4681-b6e2-e8e12d7b3456 · inbound

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers cites this paper.

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-14T16:21:05.570023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43624415-12f6-49d1-b532-1c88ff79247d · inbound

Efficient Difficulty-Aware Dynamic Routing for Diffusion-Based Real-World Image Super-Resolution cites this paper.

Efficient Difficulty-Aware Dynamic Routing for Diffusion-Based Real-World Image Super-Resolution Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 287

Resolution: unresolved; no resolver link, observed 2026-08-01T22:34:59.016446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b3bd8df-17fb-4530-a197-33c541c6eaad · inbound

Reinforcement Learning: From Algorithms To Foundation Models cites this paper.

Reinforcement Learning: From Algorithms To Foundation Models Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-01T17:45:05.050814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca17a4fe-3c62-41b0-bdcd-c92d8802278e · 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 Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-01T12:48:19.704759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7cf0faf-d03f-403c-bf84-3c6363b7cd9a · inbound

Explorative Modeling: Unlocking a Third Pretraining Axis and End-to-End Generation cites this paper.

Explorative Modeling: Unlocking a Third Pretraining Axis and End-to-End Generation Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-01T08:41:05.827379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.