Paper Citation Record · LEDGER

Improved Training Technique for Latent Consistency Models

As of 10 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 4 inbound Pith citation observations for arXiv:2502.01441.

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

pith.paper-citation-record.v1
2502.01441 v2

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:20:57.772970Z

measured 35 of 35 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:43:31.615735Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T23:48:19.353564Z

Reference resolution

31 of 31 outbound references displayed

verified exact2
verified fuzzy6
unresolved23
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1b58bbe3-c826-4d6a-891f-a86b4003c963 · outbound

This paper cites Self-corrected flow distillation for consistent one-step and few-step text-to-image generation.

Improved Training Technique for Latent Consistency Models Self-corrected flow distillation for consistent one-step and few-step text-to-image generation

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-08-09T15:20:59.411396Z

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 d931c44c-73c9-4665-b0b7-63ddb5e74975 · outbound

This paper cites Multistep Consistency Models.

Improved Training Technique for Latent Consistency Models Multistep Consistency Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.572858Z

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Observation 5a64b7be-06b0-4ba7-9241-c721967df208 · outbound

This paper cites ACT-Diffusion: Efficient Adversarial Consistency Training for One-step Diffusion Models.

Improved Training Technique for Latent Consistency Models ACT-Diffusion: Efficient Adversarial Consistency Training for One-step Diffusion Models

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-09T15:20:58.044609Z

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

Observation bc9f7c7a-ccfe-4407-99bf-0f9d9e37f1cb · outbound

This paper cites Multi-concept customization of text-to-image diffusion.

Improved Training Technique for Latent Consistency Models Multi-concept customization of text-to-image diffusion

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:20:59.500955Z

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

Observation 83b9fb2a-06fc-440a-8352-4bbc78e5e551 · outbound

This paper cites Minimizing Trajectory Curvature of ODE-based Generative Models.

Improved Training Technique for Latent Consistency Models Minimizing Trajectory Curvature of ODE-based Generative Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.606197Z

Source-reported events for the cited work

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Observation 007a99a9-326d-4d68-b574-7c8b3bba4a31 · outbound

This paper cites SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations.

Improved Training Technique for Latent Consistency Models SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.611217Z

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Observation 9d65057c-9e11-4789-8e9b-1c407741fb17 · outbound

This paper cites Reliable Fidelity and Diversity Metrics for Generative Models.

Improved Training Technique for Latent Consistency Models Reliable Fidelity and Diversity Metrics for Generative Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.615892Z

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Observation 0321ab73-6b40-43d8-b7c8-d2d1777eb41e · outbound

This paper cites DDMI: Domain-Agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations.

Improved Training Technique for Latent Consistency Models DDMI: Domain-Agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.620623Z

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Observation b5bea0f2-d4ed-4741-9637-f1e9789cb13b · outbound

This paper cites DiMSUM: Diffusion Mamba -- A Scalable and Unified Spatial-Frequency Method for Image Generation.

Improved Training Technique for Latent Consistency Models DiMSUM: Diffusion Mamba -- A Scalable and Unified Spatial-Frequency Method for Image Generation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.625514Z

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Observation 1db0df69-a7a7-4b45-a195-045acc03f433 · outbound

This paper cites Multisample Flow Matching: Straightening Flows with Minibatch Couplings.

Improved Training Technique for Latent Consistency Models Multisample Flow Matching: Straightening Flows with Minibatch Couplings

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.630435Z

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Observation b414525b-8957-471b-8f6d-5fc575c640c7 · outbound

This paper cites Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis.

Improved Training Technique for Latent Consistency Models Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.635217Z

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Observation 0eb120a5-9824-4423-9b60-27e5752e4088 · outbound

This paper cites Adversarial Diffusion Distillation.

Improved Training Technique for Latent Consistency Models Adversarial Diffusion Distillation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.648480Z

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Observation aa48c951-1b9c-44e8-bfdc-cf39b79fd7a6 · outbound

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

Improved Training Technique for Latent Consistency Models Score-Based Generative Modeling through Stochastic Differential Equations

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.692326Z

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Observation de642e40-2aad-4e73-9d0a-70a49204b668 · outbound

This paper cites Consistency Models.

Improved Training Technique for Latent Consistency Models Consistency Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.714155Z

Source-reported events for the cited work

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Observation 2186e0d5-ffee-487f-a51e-21137e03cdc5 · outbound

This paper cites Relay Diffusion: Unifying diffusion process across resolutions for image synthesis.

Improved Training Technique for Latent Consistency Models Relay Diffusion: Unifying diffusion process across resolutions for image synthesis

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.734244Z

Source-reported events for the cited work

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Observation 7cfe6197-9ad4-45d4-b737-42373a06cc19 · outbound

This paper cites Improving and generalizing flow-based generative models with minibatch optimal transport.

Improved Training Technique for Latent Consistency Models Improving and generalizing flow-based generative models with minibatch optimal transport

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.745792Z

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Observation c7fcb881-1201-4804-8ed5-8807d376e748 · outbound

This paper cites Pro- lificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation.

Improved Training Technique for Latent Consistency Models Pro- lificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:20:59.486477Z

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 0e8e0a83-80e6-49cd-9d02-2e3516c69ad8 · outbound

This paper cites Tackling the Generative Learning Trilemma with Denoising Diffusion GANs.

Improved Training Technique for Latent Consistency Models Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.754574Z

Source-reported events for the cited work

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Observation a2b365f2-74dd-4976-85a8-b1f2053963c0 · outbound

This paper cites LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop.

Improved Training Technique for Latent Consistency Models LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.759908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86cd1421-8efd-4478-b62b-c43af3d1fa65 · outbound

This paper cites Huijie Zhang, Jinfan Zhou, Yifu Lu, Minzhe Guo, Peng Wang, Liyue Shen, and Qing Qu.

Improved Training Technique for Latent Consistency Models Huijie Zhang, Jinfan Zhou, Yifu Lu, Minzhe Guo, Peng Wang, Liyue Shen, and Qing Qu

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:20:59.471776Z

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 17d41b41-6792-4eea-ab75-af96df8df365 · outbound

This paper cites Trajectory Consistency Distillation: Improved Latent Consistency Distillation by Semi-Linear Consistency Function with Trajectory Mapping.

Improved Training Technique for Latent Consistency Models Trajectory Consistency Distillation: Improved Latent Consistency Distillation by Semi-Linear Consistency Function with Trajectory Mapping

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.768825Z

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Observation 3d3f59ba-4e0a-42b2-9d5c-6e78366cffc4 · outbound

This paper cites We also provide additional uncurated samples of our models on CelebaA-HQ trained with L2 loss (12) and E-LatentLPIPS loss (13).

Improved Training Technique for Latent Consistency Models We also provide additional uncurated samples of our models on CelebaA-HQ trained with L2 loss (12) and E-LatentLPIPS loss (13)

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:20:59.457418Z

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 ad1ee258-a005-426e-8104-f417a2468e52 · outbound

This paper cites Consistency Models Made Easy.

Improved Training Technique for Latent Consistency Models Consistency Models Made Easy

Reference 1986

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.543979Z

Source-reported events for the cited work

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Observation 5c56e939-d74b-4936-a2d5-41fa09e84e63 · outbound

This paper cites Improved Techniques for Training Consistency Models.

Improved Training Technique for Latent Consistency Models Improved Techniques for Training Consistency Models

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.665419Z

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Observation 53376941-f8be-4f59-8a69-f7c65aea3744 · outbound

This paper cites Inbar Huberman-Spiegelglas, Vladimir Kulikov, and Tomer Michaeli.

Improved Training Technique for Latent Consistency Models Inbar Huberman-Spiegelglas, Vladimir Kulikov, and Tomer Michaeli

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:20:59.515725Z

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 b935c1fb-1327-417f-aef3-d5e7c4d1b04b · outbound

This paper cites TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation.

Improved Training Technique for Latent Consistency Models TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.439955Z

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Observation 75c60ace-4881-408f-bb7a-731130cc0b26 · outbound

This paper cites Introvae: In- trospective variational autoencoders for photographic image synthesis.

Improved Training Technique for Latent Consistency Models Introvae: In- trospective variational autoencoders for photographic image synthesis

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:20:59.531437Z

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 8bedf3ff-82d5-48cc-8f62-cef11edb3ae7 · outbound

This paper cites Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion.

Improved Training Technique for Latent Consistency Models Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.592553Z

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Observation 915e723c-44fb-457a-9b67-c05583af4f8f · outbound

This paper cites Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation.

Improved Training Technique for Latent Consistency Models Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.587398Z

Source-reported events for the cited work

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Observation 8a81bfd6-8fd0-48a0-a897-d5171c2c6229 · outbound

This paper cites Flow Matching in Latent Space.

Improved Training Technique for Latent Consistency Models Flow Matching in Latent Space

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.486031Z

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Observation 2d6811b2-8400-490b-9f03-f432129fb741 · outbound

This paper cites Dice: Discrete inversion enabling controllable editing for multinomial diffusion and masked generative models.arXiv preprint arXiv:2410.08207,.

Improved Training Technique for Latent Consistency Models Dice: Discrete inversion enabling controllable editing for multinomial diffusion and masked generative models.arXiv preprint arXiv:2410.08207,

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-09T15:20:57.568240Z

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Pith citing papers

Observation ff8072be-53b3-4d3f-bbcd-f62107582bac · inbound

A Continuous-Time Consistency Model for 3D Point Cloud Generation cites this paper.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Improved Training Technique for Latent Consistency Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T12:43:31.615735Z

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Observation aa60b309-4459-4c29-8b14-257ee24980e2 · 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 Improved Training Technique for Latent Consistency Models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-14T23:48:19.359351Z

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

Observation dee5886e-a505-4206-92ef-a0cb14332d0f · inbound

Discrete Meanflow Training Curriculum cites this paper.

Discrete Meanflow Training Curriculum Improved Training Technique for Latent Consistency Models

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T05:10:55.581103Z

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 2afdef9f-3c79-49f7-a664-f06d82810aaa · inbound

Efficient Video Diffusion Models: Advancements and Challenges cites this paper.

Efficient Video Diffusion Models: Advancements and Challenges Improved Training Technique for Latent Consistency Models

Reference 250

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:03:26.086951Z

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