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Paper Citation Record · LEDGER

Scaling Group Inference for Diverse and High-Quality Generation

As of 6 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 6 inbound Pith citation observations for arXiv:2508.15773.

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

pith.paper-citation-record.v1
2508.15773 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:49:39.391815Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T23:33:07.790707Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:29:52.093437Z

Reference resolution

54 of 54 outbound references displayed

  • verified exact0
  • verified fuzzy19
  • unresolved35
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 71cc8e41-c605-4480-8d63-f5627528c7ff · outbound

This paper cites Classifier-free diffusion guidance.

Scaling Group Inference for Diverse and High-Quality Generation Classifier-free diffusion guidance

Reference 1

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Observation e2ec5621-9b8a-404a-8296-a51d5cd5c732 · outbound

This paper cites Inference-time scaling for diffusion models beyond scaling denoising steps.

Scaling Group Inference for Diverse and High-Quality Generation Inference-time scaling for diffusion models beyond scaling denoising steps

Reference 2

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raw_fallback, observed 2026-08-05T17:49:43.777943Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 05302eb2-f95f-4975-852a-80bb8344ee23 · outbound

This paper cites Zero-shot image-to-image translation.

Scaling Group Inference for Diverse and High-Quality Generation Zero-shot image-to-image translation

Reference 3

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 35641d02-d740-4652-93d6-1874af48eadb · outbound

This paper cites Midjourney Website.�������������������������������, 2024.

Scaling Group Inference for Diverse and High-Quality Generation Midjourney Website.�������������������������������, 2024

Reference 4

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:35.126969Z digest=sha256:374325da20b55683647b1d958a36f93cf0295f030391f439b31cfb62e7b50ebe

Observation 3e27c88c-67c4-4183-9c32-303ab34e711c · outbound

This paper cites Adobe Firefly: Generative AI for Creatives.��������������������������������������� ����, 2025.

Scaling Group Inference for Diverse and High-Quality Generation Adobe Firefly: Generative AI for Creatives.��������������������������������������� ����, 2025

Reference 5

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:35.220139Z digest=sha256:a28fd918461febf48f6a9d6702f1e384e1ab1114fd777fb255c5b67829e1af67

Observation 580db73d-bbc2-4dc9-aeeb-637eab08c041 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

Scaling Group Inference for Diverse and High-Quality Generation Deep unsupervised learning using nonequilibrium thermodynamics

Reference 6

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source=pdf_text observed=2026-08-05T17:49:35.280568Z digest=sha256:3e76872e9c42c90eca9b70c5b326caf79d9b2b20467a27afdfb3d68e132d31cd

Observation a4745e9b-448a-4bc3-9eda-7964b8e3eed9 · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

Scaling Group Inference for Diverse and High-Quality Generation Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 7

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source=pdf_text observed=2026-08-05T17:49:35.357285Z digest=sha256:2b06b52da5d29e93668338977b933c6cb8360d5df501d353c8ac5b30c1ec7050

Observation b28ef2dc-13e6-4d29-8132-9c6843641fd8 · outbound

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

Scaling Group Inference for Diverse and High-Quality Generation Score-Based Generative Modeling through Stochastic Differential Equations

Reference 8

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source=pdf_text observed=2026-08-05T17:49:35.422508Z digest=sha256:ab9aa505b441bacc18a0afac621a7d8f5d2d66b56911ced963a0d4a738c9f3b2

Observation 0221cf15-5a43-4b85-bd6d-f5073463f36a · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Scaling Group Inference for Diverse and High-Quality Generation High-resolution image synthesis with latent diffusion models

Reference 9

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raw_fallback, observed 2026-08-05T17:49:42.966069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:35.486646Z digest=sha256:53689c4cd9fd8ba7bebc161fd3c79dd1e26b9ad46e6de03d5788ecdd9b04bd33

Observation 7e23e2aa-6882-499f-843b-27e7545e6506 · outbound

This paper cites SDXL: Improving latent diffusion models for high-resolution image synthesis.

Scaling Group Inference for Diverse and High-Quality Generation SDXL: Improving latent diffusion models for high-resolution image synthesis

Reference 10

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source=pdf_text observed=2026-08-05T17:49:35.581974Z digest=sha256:d149904016162639d285df37815ae1890de80c37b877605a01780f456061f1c4

Observation bd9a1bc9-8795-4fda-8de6-c8d0839ea388 · outbound

This paper cites Photorealistic text-to- image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022.

Scaling Group Inference for Diverse and High-Quality Generation Photorealistic text-to- image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022

Reference 11

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source=pdf_text observed=2026-08-05T17:49:35.687410Z digest=sha256:5bf20e99259db2d01ca8af73d882f155d2e4e7d1e99e81b376f6ab95f3327fb7

Observation d5b0dfd0-f2c4-4ba0-b038-cabb4af50f6f · outbound

This paper cites Video diffusion models.Advances in Neural Information Processing Systems, 35:8633–8646, 2022.

Scaling Group Inference for Diverse and High-Quality Generation Video diffusion models.Advances in Neural Information Processing Systems, 35:8633–8646, 2022

Reference 12

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source=pdf_text observed=2026-08-05T17:49:35.770528Z digest=sha256:db1c038f1231230ea6584fca7db919e7cfcddcac9f6fafe451c20db88f371d49

Observation 494a0727-a8cb-44ce-9ccb-8b8f18506823 · outbound

This paper cites Align your latents: High-resolution video synthesis with latent diffusion models.

Scaling Group Inference for Diverse and High-Quality Generation Align your latents: High-resolution video synthesis with latent diffusion models

Reference 13

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source=pdf_text observed=2026-08-05T17:49:35.852953Z digest=sha256:1105428255a0c0f1369c58545cfc1e7bfae4085dc4bc3bf743948078ef913ac5

Observation 196b4138-e959-40ce-adef-339b10fdb324 · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Scaling Group Inference for Diverse and High-Quality Generation Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 14

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source=pdf_text observed=2026-08-05T17:49:35.971319Z digest=sha256:b60f21ffc0201d7c2803ca31e9394f86cf98bf040287d3f7acb842c74d8ec37f

Observation e9c21503-122c-4019-83dd-772f88c5619a · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

Scaling Group Inference for Diverse and High-Quality Generation DreamFusion: Text-to-3D using 2D Diffusion

Reference 15

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source=pdf_text observed=2026-08-05T17:49:36.043578Z digest=sha256:e6d5af2c5ac00d5b4ab7194833ccb183587192e84cc0007070fbc0e5489cfe2b

Observation fa9e2f96-f1ba-4913-8acd-9678f50b3deb · outbound

This paper cites Magic3d: High-resolution text-to-3d content creation.

Scaling Group Inference for Diverse and High-Quality Generation Magic3d: High-resolution text-to-3d content creation

Reference 16

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source=pdf_text observed=2026-08-05T17:49:36.120950Z digest=sha256:7953ad137b31e0b0a05a2d323802f3ad7f046ed88f6b5f993c7b6562228741f1

Observation 062b02fb-d01e-4c5f-a6a8-376cf5383fe2 · outbound

This paper cites MVDream: Multi-view Diffusion for 3D Generation.

Scaling Group Inference for Diverse and High-Quality Generation MVDream: Multi-view Diffusion for 3D Generation

Reference 17

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source=pdf_text observed=2026-08-05T17:49:36.176988Z digest=sha256:2e478431c50571300a42a348d350934f30b1f44b399abc23f5ebda006dfef522

Observation ea320d7a-7828-482c-8ec6-4503b8469de9 · outbound

This paper cites Consistency-diversity-realism Pareto fronts of conditional image generative models.

Scaling Group Inference for Diverse and High-Quality Generation Consistency-diversity-realism Pareto fronts of conditional image generative models

Reference 18

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source=pdf_text observed=2026-08-05T17:49:36.240821Z digest=sha256:bd1a3dd349123690dbb8e4fe03c3ccec079b7de8d534b4b7d55cb7a0325f5dbf

Observation 43e1c1c9-ee14-47e9-9560-6c12648f05ed · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

Scaling Group Inference for Diverse and High-Quality Generation Adding conditional control to text-to-image diffusion models

Reference 19

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source=pdf_text observed=2026-08-05T17:49:36.340988Z digest=sha256:85472ac755a89ec2fe9362a6ec209350016343cbc2b2a429cdca425079f25502

Observation ea2c7764-c5ea-4639-b934-bfcabe010ff1 · outbound

This paper cites IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models.

Scaling Group Inference for Diverse and High-Quality Generation IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Reference 20

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source=pdf_text observed=2026-08-05T17:49:36.415031Z digest=sha256:600ee393d362cec861d7441054c03ef3201e732745c635ea10df5898ba9a6d4c

Observation f9e641bd-7bef-47df-a53d-45fb979b48b1 · outbound

This paper cites Fast high-resolution image synthesis with latent adversarial diffusion distillation.

Scaling Group Inference for Diverse and High-Quality Generation Fast high-resolution image synthesis with latent adversarial diffusion distillation

Reference 21

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source=pdf_text observed=2026-08-05T17:49:36.483450Z digest=sha256:147c82a1159a8845b7de1a3a71741f99f7b088af9e2e8debf4d00aafda08f1cd

Observation 397eb27b-fe96-4b44-b269-c745196a91c1 · outbound

This paper cites Adversarial diffusion distillation.

Scaling Group Inference for Diverse and High-Quality Generation Adversarial diffusion distillation

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:36.571220Z digest=sha256:e1493e7823ae5c6e84c1d621eb10458362fa82fd4fcc5374e31cf64fc7de3df2

Observation fb3f2530-2a7b-4e1e-9678-85d02883a605 · outbound

This paper cites Distilling diffusion models into conditional gans.

Scaling Group Inference for Diverse and High-Quality Generation Distilling diffusion models into conditional gans

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:36.639560Z digest=sha256:89d355995ec37cdf1bed5e88db8fa18ce47dcf63e65cd269bb92aa8c43edc2d2

Observation ef97ed6d-5bdb-47d3-95bd-4e35b19c9db2 · outbound

This paper cites One-step diffusion with distribution matching distillation.

Scaling Group Inference for Diverse and High-Quality Generation One-step diffusion with distribution matching distillation

Reference 24

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Observation c7e1a709-9383-4523-b7f8-473fb30b85d3 · outbound

This paper cites Diffusion models beat GANs on image synthesis.

Scaling Group Inference for Diverse and High-Quality Generation Diffusion models beat GANs on image synthesis

Reference 25

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:36.830780Z digest=sha256:2306b00610a53a76b8d035033e99688401ddde05fb2fb1789b1922cfe82e6876

Observation 0dc992a2-39ce-444b-8b64-fe2f1b157586 · outbound

This paper cites Training-free layout control with cross-attention guidance.

Scaling Group Inference for Diverse and High-Quality Generation Training-free layout control with cross-attention guidance

Reference 26

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raw_fallback, observed 2026-08-05T17:49:42.176696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:36.907899Z digest=sha256:e18ef97749e9cf25025f59e1b26ca0c84ae3c8ac4b2d12150f4417fca9393b12

Observation 5600c090-cf93-45d7-b652-26dc372cb21a · outbound

This paper cites Dense text-to-image generation with attention modulation.

Scaling Group Inference for Diverse and High-Quality Generation Dense text-to-image generation with attention modulation

Reference 27

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raw_fallback, observed 2026-08-05T17:49:41.996830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:36.979489Z digest=sha256:72f4c9717bd7f710e0e088c0eff4dfa9b02f706525ce85da12b8a9164b427128

Observation b4e92062-8f3d-4144-8660-2b5fa3703351 · outbound

This paper cites Grounded text-to-image synthesis with attention refocusing.

Scaling Group Inference for Diverse and High-Quality Generation Grounded text-to-image synthesis with attention refocusing

Reference 28

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raw_fallback, observed 2026-08-05T17:49:41.823252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:37.054736Z digest=sha256:e5a98a1337458bb72f462e633a5232995b29b23da02c77ed2d2f48303cf7bf97

Observation 2b5737ae-711b-41bc-8fdc-566dadc16ed7 · outbound

This paper cites Sketch-guided text-to-image diffusion models.

Scaling Group Inference for Diverse and High-Quality Generation Sketch-guided text-to-image diffusion models

Reference 29

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raw_fallback, observed 2026-08-05T17:49:41.626052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:37.111820Z digest=sha256:fa1c510f51378b415516c87f126acf8583f59650a1cb56d97f878bab487f2efd

Observation e91ede85-e4dd-4d04-a9c6-f0983d607e4e · outbound

This paper cites Localized Text-to-Image Generation for Free via Cross Attention Control.

Scaling Group Inference for Diverse and High-Quality Generation Localized Text-to-Image Generation for Free via Cross Attention Control

Reference 30

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source=pdf_text observed=2026-08-05T17:49:37.205595Z digest=sha256:8bc8e064cbae6004678ed929ff4a0483e485812e9a60e97d2496a60e63842f63

Observation c297594c-4cd5-48fe-9eb1-f7d9997b328e · outbound

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

Scaling Group Inference for Diverse and High-Quality Generation Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models

Reference 31

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source=pdf_text observed=2026-08-05T17:49:37.293865Z digest=sha256:5b47b200e9db8e3722f620f3f5a0dd5ec68016f364a85fa16257ced7b8f1ada8

Observation 090c6d01-008c-457c-9b21-3d63fb7d745d · outbound

This paper cites Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models.

Scaling Group Inference for Diverse and High-Quality Generation Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models

Reference 32

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source=pdf_text observed=2026-08-05T17:49:37.372051Z digest=sha256:c90b593dec1de28c442a85720ed64e39f9d50cdc324d2f240d7e844ff1414d1b

Observation c0acdbbc-478c-4c43-87c2-62da16440807 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022.

Scaling Group Inference for Diverse and High-Quality Generation Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022

Reference 33

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source=pdf_text observed=2026-08-05T17:49:37.447147Z digest=sha256:eb21b330d1f9d56b9b6f757694fb90f1036485385c52021f102ab3b7335f323a

Observation cfebaea6-5461-40f5-800f-9c1d93aa90a9 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Scaling Group Inference for Diverse and High-Quality Generation Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 34

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source=pdf_text observed=2026-08-05T17:49:37.510024Z digest=sha256:4ebd0ee39a518e856e7fe8c45b8e26d2ed4e2fda6ec4a2359edc2235b35ae0f8

Observation f9513086-4bc7-4c1a-ab43-80498656a556 · outbound

This paper cites s1: Simple test-time scaling.

Scaling Group Inference for Diverse and High-Quality Generation s1: Simple test-time scaling

Reference 35

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source=pdf_text observed=2026-08-05T17:49:37.571540Z digest=sha256:43289df34c4b323c90b3eee5289c0152c3b76808aaf4c852d02bcee2cc515e6c

Observation 52f20cec-44bd-4e26-bcd3-410e41de233f · outbound

This paper cites Svdqunat: Absorbing outliers by low-rank components for 4-bit diffusion models.arXiv preprint arXiv:2411.05007, 2024.

Scaling Group Inference for Diverse and High-Quality Generation Svdqunat: Absorbing outliers by low-rank components for 4-bit diffusion models.arXiv preprint arXiv:2411.05007, 2024

Reference 36

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no resolver link, observed 2026-08-05T17:49:37.639866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:49:37.639866Z digest=sha256:eb33223f819a2f732e9d125d0e6f173b75e07a0509afda4c88b6ddd24c3ad3ac

Observation 2c02abea-8d6e-41fb-97fa-24c6a4b5aced · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Scaling Group Inference for Diverse and High-Quality Generation Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 37

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no resolver link, observed 2026-08-05T17:49:37.735986Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:49:37.735986Z digest=sha256:1e7cab55cee5192a18cc2d93fe8ae22b468eaaf102ec1d9a9cae215227038215

Observation ebf60d77-44a6-4b5c-b052-c1d368f7012c · outbound

This paper cites Dinov2: Learning robust visual features without supervision.Transactions on Machine Learning Research, 2023.

Scaling Group Inference for Diverse and High-Quality Generation Dinov2: Learning robust visual features without supervision.Transactions on Machine Learning Research, 2023

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:49:41.428151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:37.830298Z digest=sha256:6e8eb2390fbdaa813d8ab490bf0f858480e2638a4bd0c39fb7ce49ac697bb707

Observation a1f3e294-1bf0-4dd7-a412-8ca7c1830eb9 · outbound

This paper cites Gurobi Optimizer Reference Manual, 2025.

Scaling Group Inference for Diverse and High-Quality Generation Gurobi Optimizer Reference Manual, 2025

Reference 39

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no resolver link, observed 2026-08-05T17:49:37.915693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:49:37.915693Z digest=sha256:4c98be834b25bda4e9e99fe39197eb5fc7d6437ec16cdefa9ac5bb701c8690d3

Observation 88ef8c59-6364-41a1-ad6f-1ecd6c9a6340 · outbound

This paper cites Flux.�����������������������������������������, 2024.

Scaling Group Inference for Diverse and High-Quality Generation Flux.�����������������������������������������, 2024

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:49:41.219070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:37.989299Z digest=sha256:c3257ade765a29ff8a005586ca220f33f8779cb9c3706d2267f51be016176ee2

Observation 1744443e-73b8-4863-ad7f-ea4c36cad84c · outbound

This paper cites Geneval: An object-focused framework for evaluating text-to-image alignment.Advances in Neural Information Processing Systems, 36:52132–52152, 2023.

Scaling Group Inference for Diverse and High-Quality Generation Geneval: An object-focused framework for evaluating text-to-image alignment.Advances in Neural Information Processing Systems, 36:52132–52152, 2023

Reference 41

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no resolver link, observed 2026-08-05T17:49:38.091341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:49:38.091341Z digest=sha256:f5abe8694950ae434e1670fa6c647465d9f235eb7eba7a11ca4b0b9b56974715

Observation 94d29e2e-a75c-47ab-8829-48a6107ede8c · outbound

This paper cites Microsoft coco: Common objects in context.

Scaling Group Inference for Diverse and High-Quality Generation Microsoft coco: Common objects in context

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:49:41.001500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:38.185351Z digest=sha256:cee0f7bc07417b7f6ac2b1ddc35a9911cdbb3c9339b72442db11f01476f3b6d7

Observation ad35f037-ba54-47d1-ac6b-b6fc4f07e76d · outbound

This paper cites Dream- booth: Fine tuning text-to-image diffusion models for subject-driven generation.

Scaling Group Inference for Diverse and High-Quality Generation Dream- booth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-05T17:49:38.269195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:49:38.269195Z digest=sha256:baaf07ff8d3e1738066f2287fba5b18dd39c03fa36dd0194cb7c2b54c77ad37c

Observation 0f305966-7999-41b8-b4b5-3a21904f7e77 · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

Scaling Group Inference for Diverse and High-Quality Generation Depth anything: Unleashing the power of large-scale unlabeled data

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-05T17:49:38.341613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:49:38.341613Z digest=sha256:a4aa60c2f7bc3c4e43c9fb315c42b04c4e3f134c866c2bb69d20b5a887fe4d5c

Observation efb0d809-3724-4b46-9403-0863863bcf45 · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis.

Scaling Group Inference for Diverse and High-Quality Generation Scaling rectified flow transformers for high-resolution image synthesis

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-05T17:49:38.461441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:49:38.461441Z digest=sha256:21bd534cc25f72082488bb2c47982c0cefb3b8b9c16c5b395b979dfd2b5d86b4

Observation e3aa717f-e0ff-4ba3-90c8-30e8ec5dcdf6 · outbound

This paper cites Generating multi-image synthetic data for text-to-image customization.ArXiv, 2025.

Scaling Group Inference for Diverse and High-Quality Generation Generating multi-image synthetic data for text-to-image customization.ArXiv, 2025

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:49:40.769990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:38.554684Z digest=sha256:6c02007abcfc29eb76e152c1266b217347fef79418e6f4d64718cdae6a167924

Observation f7bd4964-7a07-466b-becb-56782218e1c3 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Scaling Group Inference for Diverse and High-Quality Generation Learning transferable visual models from natural language supervision

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-05T17:49:38.645776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:49:38.645776Z digest=sha256:decec6db20c0964d4a3ae2b5afda2ab58bd094d35b108e1980de2cd66796b1c8

Observation 9587fea7-af73-4dfa-acbe-e1d2574de517 · outbound

This paper cites Toward multimodal image-to-image translation.Conference on Neural Information Processing Systems (NeurIPS), 30, 2017.

Scaling Group Inference for Diverse and High-Quality Generation Toward multimodal image-to-image translation.Conference on Neural Information Processing Systems (NeurIPS), 30, 2017

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:49:40.589116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:38.743340Z digest=sha256:3ae236786e85f71ddeaf6055603df748f41ccfa995df7b168b51d85ab59ab9b5

Observation fa6ca9e2-7884-4502-9861-6f3dd9129eec · outbound

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

Scaling Group Inference for Diverse and High-Quality Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-05T17:49:38.859683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:49:38.859683Z digest=sha256:044758d3e5da819fa084ce064aca18504bb121c1dc28e60cca27e5c4903192f8

Observation 316c5eb1-010e-414b-8b82-07c65d0851d0 · outbound

This paper cites Tiny autoencoder for stable diffusion.Retrieved May, 22:2024, 2023.

Scaling Group Inference for Diverse and High-Quality Generation Tiny autoencoder for stable diffusion.Retrieved May, 22:2024, 2023

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:49:40.426463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:38.999059Z digest=sha256:acc401bb19148c72f0e97814fa8725c98055c52f67444045ba3bcf769d768238

Observation 87565289-1616-4a1f-abb7-c760c0ad63f1 · outbound

This paper cites Imagereward: Learning and evaluating human preferences for text-to-image generation.Advances in Neural Information Processing Systems, 36:15903–15935, 2023.

Scaling Group Inference for Diverse and High-Quality Generation Imagereward: Learning and evaluating human preferences for text-to-image generation.Advances in Neural Information Processing Systems, 36:15903–15935, 2023

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-05T17:49:39.108545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:49:39.108545Z digest=sha256:fab6cc5590300fa4effecf5b548f53da88ecb9f3d9306195dc7a558ae95986c8

Observation acbbc3f6-2df3-44f5-864e-05f55c569b9c · outbound

This paper cites Depth anything v2.Advances in Neural Information Processing Systems, 37:21875–21911, 2024.

Scaling Group Inference for Diverse and High-Quality Generation Depth anything v2.Advances in Neural Information Processing Systems, 37:21875–21911, 2024

Reference 52

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unresolved
no resolver link, observed 2026-08-05T17:49:39.193447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:49:39.193447Z digest=sha256:18be6201fff82d31edd8e9f96c778e810b3f2cc30fcc041c81c7e3fe7481b10d

Observation e34868b6-d545-471d-a9bd-a446b500e47f · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Scaling Group Inference for Diverse and High-Quality Generation Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:49:40.215726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:39.284461Z digest=sha256:ca8d67198a5f576789b668363389534cc0210847df4adc57cd425768e98686bb

Observation a60e2eb9-e348-41cb-b975-b4240f14714c · outbound

This paper cites an unresolved cited work.

Scaling Group Inference for Diverse and High-Quality Generation Unresolved cited work

Reference 200

Resolution
unresolved
raw_fallback, observed 2026-08-05T17:49:40.058841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-08-05T17:49:39.391815Z digest=sha256:10ccd91723c2c83a8d749be2803ffaf21f94af30c2c6cddc12b6e3f712e104fa

Pith citing papers

Observation 819e4c7c-4fcd-4ec1-9619-168e0f7736e6 · inbound

It's Never Too Late: Noise Optimization for Collapse Recovery in Trained Diffusion Models cites this paper.

It's Never Too Late: Noise Optimization for Collapse Recovery in Trained Diffusion Models Scaling Group Inference for Diverse and High-Quality Generation

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-16T17:53:11.703309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T17:51:32.439732Z digest=sha256:a84cb78fce6dcb5844e9643429b32c975163710231780988b731a63c6b0aa3e9

Observation 7e097c74-db0e-4654-b9a6-d80941db227e · inbound

STRIDE: Training-Free Diversity Guidance via PCA-Directed Feature Perturbation in Single-Step Diffusion Models cites this paper.

STRIDE: Training-Free Diversity Guidance via PCA-Directed Feature Perturbation in Single-Step Diffusion Models Scaling Group Inference for Diverse and High-Quality Generation

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T02:57:09.252632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-13T02:53:35.519419Z digest=sha256:8717d0782394dee7a78a046dbd0b7707a48fabeec936a556f7a4ed197d27630d

Observation c7078997-e7aa-4f5a-b6e1-3ac78abe01b4 · inbound

Composing People Together: Iterative Pose-Image Generation for Multi-Person Interaction Scenes cites this paper.

Composing People Together: Iterative Pose-Image Generation for Multi-Person Interaction Scenes Scaling Group Inference for Diverse and High-Quality Generation

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:10:22.295892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-05-25T05:07:14.227821Z digest=sha256:c4b6468c175434876ccdbb144280ab43390a6905b006192274383cf3e62b5daa

Observation 58558ae5-9f49-4476-853c-02de4776277a · inbound

Semantic Browsing: Controllable Diversity for Image Generation cites this paper.

Semantic Browsing: Controllable Diversity for Image Generation Scaling Group Inference for Diverse and High-Quality Generation

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-07-04T10:09:45.488529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-06-26T09:03:48.337833Z digest=sha256:4ba021115360257c8e7836e87c86954e4cb54e125609e4e4c362d72c488cf722

Observation f567193d-89f0-42ec-b010-3959d2b59292 · inbound

Don't Settle at the Mode! Mitigating Diversity Collapse in Pretrained Flow Models via Feature Self-Guidance cites this paper.

Don't Settle at the Mode! Mitigating Diversity Collapse in Pretrained Flow Models via Feature Self-Guidance Scaling Group Inference for Diverse and High-Quality Generation

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:29:52.094775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-26T05:07:59.556667Z digest=sha256:a02ed7f6836a1e82cd38b798f2361e2d5097e6e2b04b6cef8a9ddfa469dfe798

Observation 39254490-d99e-4930-bce1-d10cf948f7a4 · inbound

Manifold-Constrained Noise Optimization for Diverse Diffusion Sampling cites this paper.

Manifold-Constrained Noise Optimization for Diverse Diffusion Sampling Scaling Group Inference for Diverse and High-Quality Generation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-31T23:33:07.790707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:33:07.790707Z digest=sha256:2bdf467d4711da67b1fb68c82757ff1371462b5b2347ac3550449ce7bc8726f3