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Paper Citation Record · LEDGER

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning

As of 10 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2607.21591.

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

pith.paper-citation-record.v1
2607.21591 v1

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measured 58 of 58 reference resolution

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measured 58 of 58 standing notices

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measured 0 of 0 inbound itemization

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Reference resolution

58 of 58 outbound references displayed

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Outbound references

Observation 725fd625-7fb5-493d-97d6-b02e967e7bab · outbound

This paper cites In: International Conference on Learning Representations.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: International Conference on Learning Representations

Reference 1

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This paper cites In: Proceed- ings of the AAAI conference on artificial intelligence.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Proceed- ings of the AAAI conference on artificial intelligence

Reference 2

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This paper cites com/papers/dall-e-3.pdf, accessed: July 22, 2026.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning com/papers/dall-e-3.pdf, accessed: July 22, 2026

Reference 3

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This paper cites In: International Conference on Learning Represen- tations.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: International Conference on Learning Represen- tations

Reference 4

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This paper cites Finance and Stochastics13(4), 613–633 (Sep 2009).https://doi.org/10.1007/s00780-009-0098-8,http://link.springer.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Finance and Stochastics13(4), 613–633 (Sep 2009).https://doi.org/10.1007/s00780-009-0098-8,http://link.springer

Reference 5

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This paper cites In: The Eleventh International Con- ference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: The Eleventh International Con- ference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023

Reference 6

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This paper cites Training Verifiers to Solve Math Word Problems.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Training Verifiers to Solve Math Word Problems

Reference 7

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This paper cites Probability and its Applications, Springer New York, New York, NY (2004).https://doi.org/10.1007/978-1-4684-9393- 1,http://link.springer.com/10.1007/978-1-4684-9393-1.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Probability and its Applications, Springer New York, New York, NY (2004).https://doi.org/10.1007/978-1-4684-9393- 1,http://link.springer.com/10.1007/978-1-4684-9393-1

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This paper cites Emerging Properties in Unified Multimodal Pretraining.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Emerging Properties in Unified Multimodal Pretraining

Reference 9

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This paper cites Statistics and Computing31(6), 81 (2021).

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Statistics and Computing31(6), 81 (2021)

Reference 10

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This paper cites In: Forty-first international conference on machine learning (2024) Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning 17.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Forty-first international conference on machine learning (2024) Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning 17

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Unresolved cited work

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This paper cites Advances in neural information processing systems14(2001).

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in neural information processing systems14(2001)

Reference 13

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This paper cites Advances in Neural Information Processing Systems36, 52132–52152 (2023).

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in Neural Information Processing Systems36, 52132–52152 (2023)

Reference 14

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This paper cites In: IEEE/CVF Winter Conference on Appli- cations of Computer Vision, WACV 2026, Tucson, AZ, USA, March 6-10, 2026.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: IEEE/CVF Winter Conference on Appli- cations of Computer Vision, WACV 2026, Tucson, AZ, USA, March 6-10, 2026

Reference 15

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This paper cites Advances in neural information processing systems33, 6840–6851 (2020).

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in neural information processing systems33, 6840–6851 (2020)

Reference 16

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Artificial intelligence and statistics

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This paper cites CoRRabs/2512.16853(2025).https://doi.org/10.48550/ARXIV.2512.16853, https://doi.org/10.48550/arXiv.2512.16853.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning CoRRabs/2512.16853(2025).https://doi.org/10.48550/ARXIV.2512.16853, https://doi.org/10.48550/arXiv.2512.16853

Reference 18

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Dasgupta, S., McAllester, D

Reference 19

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in Neural Information Processing Systems38, 30830–30864 (2026)

Reference 20

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in neural information processing systems36, 36652–36663 (2023)

Reference 21

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Dynamic Search for Inference-Time Alignment in Diffusion Models

Reference 23

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Belgrave, D., Zhang, C., Montoya, L.N., Lin, H., Pascanu, R., Koniusz, P., Ghassemi, M., Chen, N., Ruíz, I.V.M., Loaiza-Bonilla, A

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: The Eleventh International Conference on Learning Rep- resentations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023

Reference 25

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: The Eleventh International Conference on Learn- ing Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023

Reference 26

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S

Reference 27

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps

Reference 28

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning OpenAI GPT-5 System Card

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in Neural Information Processing Systems38, 13170–13216 (2026)

Reference 30

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S

Reference 31

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: The Twelfth International Conference on Learning Represen- tations, ICLR 2024, Vienna, Austria, May 7-11, 2024

Reference 32

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization

Reference 33

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in Neural Information Processing Systems38, 87284–87317 (2026)

Reference 34

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Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Observation 79b97bec-60e8-4009-ac8a-00ded2c7479d · outbound

This paper cites In: Singh, A., Fazel, M., Hsu, D., Lacoste-Julien, S., Berkenkamp, F., Maharaj, T., Wagstaff, K., Zhu, J.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Singh, A., Fazel, M., Hsu, D., Lacoste-Julien, S., Berkenkamp, F., Maharaj, T., Wagstaff, K., Zhu, J

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Observation 32221853-3c69-4f04-b2cb-a1f8052c527c · outbound

This paper cites Advances in Neural Information Processing Systems35, 9460–9471 (2022).

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in Neural Information Processing Systems35, 9460–9471 (2022)

Reference 37

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Observation 5b541d41-5576-4c0b-a04a-8e5953865c47 · outbound

This paper cites In: International conference on machine learning.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: International conference on machine learning

Reference 38

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Observation 9e15c690-e4ab-4ee3-98e3-e19fd95d55ee · outbound

This paper cites In: 9th Inter- national Conference on Learning Representations, ICLR 2021, Virtual Event, Aus- tria, May 3-7, 2021.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: 9th Inter- national Conference on Learning Representations, ICLR 2021, Virtual Event, Aus- tria, May 3-7, 2021

Reference 39

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Observation 960c5b4e-fbfa-4b33-a8e6-8199ff386c84 · outbound

This paper cites In: 9th Inter- national Conference on Learning Representations, ICLR 2021, Virtual Event, Aus- tria, May 3-7, 2021.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: 9th Inter- national Conference on Learning Representations, ICLR 2021, Virtual Event, Aus- tria, May 3-7, 2021

Reference 40

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Observation a5c94524-f4e2-4e9a-a8e2-cf97bcdb5f05 · outbound

This paper cites In: Singh, A., Fazel, M., Hsu, D., Lacoste-Julien, S., Berkenkamp, F., Maharaj, T., Wagstaff, K., Zhu, J.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Singh, A., Fazel, M., Hsu, D., Lacoste-Julien, S., Berkenkamp, F., Maharaj, T., Wagstaff, K., Zhu, J

Reference 41

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Observation 93f1ae12-55cc-4e8a-bdd3-64ee4197e9df · outbound

This paper cites Advances in neural information processing systems36, 75993–76005 (2023).

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in neural information processing systems36, 75993–76005 (2023)

Reference 42

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Observation 2989190c-cb23-4d8b-967e-4b53b7b51aa4 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 43

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Observation a9e7bca3-ac07-4cb9-ba7e-b6593e6de462 · outbound

This paper cites Advances in Neural Infor- mation Processing Systems36, 31372–31403 (2023).

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in Neural Infor- mation Processing Systems36, 31372–31403 (2023)

Reference 44

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Observation 32d6327a-22be-4e6b-bda8-a1ecd1aa93a4 · outbound

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

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 45

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Observation 559289c7-4a1e-4a2a-9528-2252eea142a4 · outbound

This paper cites Advances in Neural Information Processing Systems36, 15903–15935 (2023).

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in Neural Information Processing Systems36, 15903–15935 (2023)

Reference 46

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Observation 4693a3fe-c4a1-4bd9-8229-4eb83a55e3bb · outbound

This paper cites In: 2025 IEEE/CVF Winter Conference on Ap- plications of Computer Vision (WACV).

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: 2025 IEEE/CVF Winter Conference on Ap- plications of Computer Vision (WACV)

Reference 47

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Observation a4ed1894-8f90-4f80-8eaf-0db581ebc61a · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 48

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Observation bf46cfa7-1f03-4cd8-bd23-cb57bd8b77f5 · outbound

This paper cites Advances in Neural Information Processing Systems35, 20744–20757 (2022).

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in Neural Information Processing Systems35, 20744–20757 (2022)

Reference 49

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Observation 01e2278e-8517-4e6b-9d31-027f084a72bb · outbound

This paper cites Advances in neural information processing systems36, 11809–11822 (2023).

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Advances in neural information processing systems36, 11809–11822 (2023)

Reference 50

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Observation d347d1f9-5bb2-4f98-a204-6df54605b45c · outbound

This paper cites In: Proceedings of the IEEE/CVF international conference on computer vision.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning In: Proceedings of the IEEE/CVF international conference on computer vision

Reference 51

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Observation e2b4b0f1-d9ef-4987-a140-f3b3465eb7dc · outbound

This paper cites prompt_id.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning prompt_id

Reference 52

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Observation 36dbfd03-ccd4-4e2e-89f0-dde07f3e3cbb · outbound

This paper cites an unresolved cited work.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Unresolved cited work

Reference 53

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Observation bfaf4e2c-5963-4544-b7ca-9093b6ab94dc · outbound

This paper cites an unresolved cited work.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Unresolved cited work

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Observation 474f0044-868e-439f-969c-9c14d888d5d9 · outbound

This paper cites an unresolved cited work.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Unresolved cited work

Reference 55

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Observation f85b62b6-4b25-40be-abab-426691062343 · outbound

This paper cites an unresolved cited work.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Unresolved cited work

Reference 56

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Observation 025bb381-6f79-46b7-9e4d-21683a7c4c44 · outbound

This paper cites an unresolved cited work.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning Unresolved cited work

Reference 57

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Observation b6b3d894-53e9-45bd-b732-a2872a94ba72 · outbound

This paper cites a photo of a cow left of a stop sign.

Inference-Time Scaling of Diffusion Models via Progressive Seed Pruning a photo of a cow left of a stop sign

Reference 58

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Pith citing papers

No inbound Pith citation observations are available.