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Paper Citation Record · LEDGER

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering

As of 7 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2505.23343.

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

pith.paper-citation-record.v1
2505.23343 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:52:52.248851Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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  • verified fuzzy8
  • unresolved26
  • parse uncertain0
  • malformed identifier0
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External citation measurements

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Outbound references

Observation 1df3eb9d-bf91-44f8-97e0-fe79eb4b1b23 · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Training Diffusion Models with Reinforcement Learning

Reference 1

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source=pdf_text observed=2026-08-07T12:52:48.909218Z digest=sha256:aac33dad837611d1461b36ee0617e18e064e52f14a1108b3caa7db246f3e522a

Observation 7f5b7c26-06a0-4ade-a142-051c3261adf8 · outbound

This paper cites Inference-Time Alignment of Diffusion Models with Direct Noise Optimization.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Inference-Time Alignment of Diffusion Models with Direct Noise Optimization

Reference 2

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source=pdf_text observed=2026-08-07T12:52:49.003765Z digest=sha256:d06dc7629f10168bc5035be6c2eff32ef0a3eedcde668bcd264a1bd5539d1765

Observation 0e9731f9-14fc-43e7-8e18-71aaea3e0583 · outbound

This paper cites Denoising diffusion probabilistic models.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Denoising diffusion probabilistic models

Reference 3

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Observation 11bdecac-2de3-4cbf-a352-858ec6081983 · outbound

This paper cites Denoising diffusion implicit models.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Denoising diffusion implicit models

Reference 4

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source=pdf_text observed=2026-08-07T12:52:49.178716Z digest=sha256:2057d5f0768c9716754bae1f425e13b4e9fca3329c541830a47c64bdb057491b

Observation 8cab8c19-e1b7-4722-9e7d-9f38fc6d527f · outbound

This paper cites Generative modeling by estimating gradients of the data distribution.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Generative modeling by estimating gradients of the data distribution

Reference 5

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source=pdf_text observed=2026-08-07T12:52:49.310823Z digest=sha256:8c1f726d0b39c07ce4331eed3fbbb11eb4aab0fd57dd96829eb102ffabff813b

Observation 93fb4aeb-2049-4f6a-aa55-fe3335eb9780 · outbound

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

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 6

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Observation 98f3ea66-188d-43f2-a2ad-48229894c180 · outbound

This paper cites Scalable diffusion models with transformers.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Scalable diffusion models with transformers

Reference 7

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Observation 128c7e82-d56d-48f0-ab08-8bd30b34cdf3 · outbound

This paper cites Diffusion models beat gans on image synthesis.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Diffusion models beat gans on image synthesis

Reference 8

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Observation 02a27826-6f4d-4693-8d82-42b34f79036d · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Wan: Open and Advanced Large-Scale Video Generative Models

Reference 9

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source=pdf_text observed=2026-08-07T12:52:49.759298Z digest=sha256:aa461588c763dec94ea7363b13ddb9f2b459c5e517a20cce158b30524db8fd79

Observation 62aab061-63c3-45d1-965a-701ab300f827 · outbound

This paper cites Viewdiff: 3d-consistent image generation with text-to-image models.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Viewdiff: 3d-consistent image generation with text-to-image models

Reference 10

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source=pdf_text observed=2026-08-07T12:52:49.853737Z digest=sha256:4721f1626e585168c3abbc33d9985f76a9587c66d94f8aabb88972285fcff696

Observation 0453a75e-aee5-4801-8208-49dd726ae19e · outbound

This paper cites Sv3d: Novel multi-view synthesis and 3d generation from a single image using latent video diffusion.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Sv3d: Novel multi-view synthesis and 3d generation from a single image using latent video diffusion

Reference 11

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source=pdf_text observed=2026-08-07T12:52:49.939531Z digest=sha256:817490a65abe1eedf907b16e42a816741c51cba0ff6aa6b3bc19d7a1f368933e

Observation 091fe385-3e6b-43cf-a0da-eefb3e5aa164 · outbound

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

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Score-Based Generative Modeling through Stochastic Differential Equations

Reference 12

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source=pdf_text observed=2026-08-07T12:52:50.052790Z digest=sha256:75940982acb32dad1adbbbe3bc7a1483e79490a5136f8b90b486695c4f28c0d6

Observation 4b7caf33-2061-476c-a2ef-038845b29d0e · outbound

This paper cites Loraclr: Contrastive adaptation for customization of diffusion models.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Loraclr: Contrastive adaptation for customization of diffusion models

Reference 13

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source=pdf_text observed=2026-08-07T12:52:50.145828Z digest=sha256:b6e8a551980b9bcf50cd5ebbb392d3f526b82c590f9717d8a5745b1a47351f9d

Observation 7158a3d4-d9f4-48f7-ad89-010d37166bfe · outbound

This paper cites Diffusion model alignment using direct preference optimization.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Diffusion model alignment using direct preference optimization

Reference 14

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Observation 2b908c4a-6b72-4f4a-b131-857eea1eed88 · outbound

This paper cites RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment

Reference 15

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source=pdf_text observed=2026-08-07T12:52:50.359893Z digest=sha256:bd841a95d1d91e520f5fe261ec29ef8f087cac000617b81658db52ca62b54ff0

Observation f9074d29-51f3-437e-ae2c-fe09bfd24a53 · outbound

This paper cites Dpok: Reinforcement learning for fine-tuning text-to-image diffusion models.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Dpok: Reinforcement learning for fine-tuning text-to-image diffusion models

Reference 16

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Observation b021fcc4-99dd-4dcc-8583-07f039fc35d1 · outbound

This paper cites End-to-end diffusion latent optimization improves classifier guidance.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering End-to-end diffusion latent optimization improves classifier guidance

Reference 17

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source=pdf_text observed=2026-08-07T12:52:50.526678Z digest=sha256:4d6c3634ab27fe57601fb8bc12f0d9a6a5babbe5545944727605ca6ceb5a7f6b

Observation 47773be4-0f1c-4a81-bff3-bdf9e2c5ece9 · outbound

This paper cites Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps

Reference 18

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source=pdf_text observed=2026-08-07T12:52:50.643517Z digest=sha256:92307f24bc4455c23e164ad86004343beb5e45683930bd0ab16bd3b18bc5b586

Observation 17462dfc-a565-4b60-ac5a-6e1fcfd39ad1 · outbound

This paper cites D-Flow: Differentiating through Flows for Controlled Generation.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering D-Flow: Differentiating through Flows for Controlled Generation

Reference 19

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Observation 218048d4-398a-4daf-931d-bcd04ad7f22a · outbound

This paper cites Pick-a-pic: An open dataset of user preferences for text-to-image generation.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Pick-a-pic: An open dataset of user preferences for text-to-image generation

Reference 20

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source=pdf_text observed=2026-08-07T12:52:50.812221Z digest=sha256:beb30207a9e0b47b8e89a2fae219ddf973fe23c1ac676a5fe92d0a5267cd69bc

Observation 48185646-ca5f-42ac-b507-e47d8c6459ad · outbound

This paper cites Classifier-Free Diffusion Guidance.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Classifier-Free Diffusion Guidance

Reference 21

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Observation bcd421a6-dc78-49d5-9321-bf3f1b8d25ce · outbound

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

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Imagenet: A large- scale hierarchical image database

Reference 22

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Observation 2e98496c-5a03-452a-8ead-4872814fc46f · outbound

This paper cites Geneval: An object-focused framework for evaluating text-to-image alignment.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Geneval: An object-focused framework for evaluating text-to-image alignment

Reference 23

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source=pdf_text observed=2026-08-07T12:52:51.106169Z digest=sha256:173b1a9ee80d5800fcb954f913015ad8d0197fdbfac030f7bacc3e7d730b756c

Observation bef65c03-03f4-4345-9018-27b09d0f2359 · outbound

This paper cites ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment

Reference 24

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source=pdf_text observed=2026-08-07T12:52:51.174204Z digest=sha256:a1b8cc01df0a8b6fb8a9ba9c99585f6344366024b9a6179afa2ef960411dbd3d

Observation bb60d439-d560-4de3-b934-d4ace2b59239 · outbound

This paper cites Laion- 5b: An open large-scale dataset for training next generation image-text models.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Laion- 5b: An open large-scale dataset for training next generation image-text models

Reference 25

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source=pdf_text observed=2026-08-07T12:52:51.236657Z digest=sha256:33f0f139404d8b249fbe0caa7323b90f8ede37eaa1f917a6804c7daa6c06ec7b

Observation a64fa191-1e75-435b-8269-b7c258255add · outbound

This paper cites Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 26

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source=pdf_text observed=2026-08-07T12:52:51.353542Z digest=sha256:122f9673e6bed2b7aff1e35bfbfe511cadc64618fd0bb8903664eb107b37ec86

Observation fa980655-7518-410d-b14b-b24d2592a4a9 · outbound

This paper cites Elucidating the design space of diffusion-based generative models.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Elucidating the design space of diffusion-based generative models

Reference 27

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source=pdf_text observed=2026-08-07T12:52:51.426878Z digest=sha256:b72679241faf60d2b8993471b77e2fd8798a30ac9b9e4079cfc6234f4dab3783

Observation a928482e-2037-477b-a9f6-c668d9d1af48 · outbound

This paper cites Guiding a diffusion model with a bad version of itself.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Guiding a diffusion model with a bad version of itself

Reference 28

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Observation 7280384e-2cb9-4837-971c-8401f7341894 · outbound

This paper cites Reno: Enhancing one-step text-to-image models through reward-based noise optimization.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Reno: Enhancing one-step text-to-image models through reward-based noise optimization

Reference 29

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Observation 1c229474-b10b-43f7-816d-afcee5962e20 · outbound

This paper cites Loss-guided diffusion models for plug-and-play controllable generation.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Loss-guided diffusion models for plug-and-play controllable generation

Reference 30

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source=pdf_text observed=2026-08-07T12:52:51.759233Z digest=sha256:6c6fcde408fba6cfdc0fb94f9679a2f490836a87827998d4f584767f17f4db62

Observation 2fb1e799-c049-424d-a906-1c1e4d60fe26 · outbound

This paper cites Verifying the Union of Manifolds Hypothesis for Image Data.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Verifying the Union of Manifolds Hypothesis for Image Data

Reference 31

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Observation 88f8f15c-7cfc-4ae5-918c-ce752288406d · outbound

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

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering The Intrinsic Dimension of Images and Its Impact on Learning

Reference 32

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source=pdf_text observed=2026-08-07T12:52:51.959202Z digest=sha256:e7c6196ced060172e09a4482b1a5985e4f51649ae21d25a7d6c60698b94b77ab

Observation b6e1385a-04ab-4832-af10-fe286c3b0571 · outbound

This paper cites Analyzing and improving the training dynamics of diffusion models.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Analyzing and improving the training dynamics of diffusion models

Reference 33

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source=pdf_text observed=2026-08-07T12:52:52.078319Z digest=sha256:a903f46f95310ce68398c9109c08a04fd18952fb07b7596cc4f0e0a294404fbe

Observation 8504fe7a-bca6-403d-ba8a-87155e7f41d9 · outbound

This paper cites Lof: identifying density-based local outliers.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering Lof: identifying density-based local outliers

Reference 34

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:52:52.165725Z digest=sha256:6ff0598a7c291b7ca486484afdb14f5665a75f7a874be17dab52bceee6a8c65d

Observation f4bcc3b0-9536-4ffd-8d10-f84f89bbe6cf · outbound

This paper cites A beach with shells organized to form the words ’Every grain of sand holds a universe of endless possibilities’.

Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample Filtering A beach with shells organized to form the words ’Every grain of sand holds a universe of endless possibilities’

Reference 35

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:52:52.248851Z digest=sha256:0949e0d52f200495caf8c4971410ef930dd7f84bc816d63cb124a57f54947d21

Pith citing papers

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