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Paper Citation Record · LEDGER

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time

As of 9 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 0 inbound Pith citation observations for arXiv:2607.26647.

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

pith.paper-citation-record.v1
2607.26647 v1

Coverage vector

measured 80 of 80 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T11:42:04.371328Z

measured 80 of 80 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

80 of 80 outbound references displayed

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Outbound references

Observation e9edf986-4711-4211-8770-4a2ebc643e38 · outbound

This paper cites In: The Fourteenth International Conference on Learning Representations (2026), https://openreview.net/forum?id=xEWooSOgaz.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: The Fourteenth International Conference on Learning Representations (2026), https://openreview.net/forum?id=xEWooSOgaz

Reference 1

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This paper cites Qwen Technical Report.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Qwen Technical Report

Reference 2

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This paper cites In: The Thirteenth International Conference on Learning Representations (2024),https: //openreview.net/forum?id=MKvQH1ekeY.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: The Thirteenth International Conference on Learning Representations (2024),https: //openreview.net/forum?id=MKvQH1ekeY

Reference 3

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

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 4

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This paper cites In: Proceedings of the International Conference on Computer Vision (ICCV) (2021).

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the International Conference on Computer Vision (ICCV) (2021)

Reference 5

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This paper cites In: Findings of the Association for Computational Linguistics: EMNLP 2024.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Findings of the Association for Computational Linguistics: EMNLP 2024

Reference 6

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

Reference 7

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This paper cites ACM trans- actions on Graphics (TOG)42(4), 1–10 (2023).

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time ACM trans- actions on Graphics (TOG)42(4), 1–10 (2023)

Reference 8

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: The Thirteenth International Con- ference on Learning Representations (2025),https://openreview.net/forum?id= E77uvbOTtp

Reference 9

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This paper cites In: Forty-first international conference on machine learning (2024).

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Forty-first international conference on machine learning (2024)

Reference 10

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This paper cites In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Direct Ascent Synthesis: Revealing Hidden Generative Capabilities in Discriminative Models

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Advances in Neural Information Processing Systems36, 52132–52152 (2023)

Reference 15

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Text-to-Image Alignment in Denoising-Based Models through Step Selection

Reference 16

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 17

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: The Eleventh In- ternational Conference on Learning Representations (2023),https://openreview

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Advances in neural information processing systems33, 6840–6851 (2020)

Reference 20

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: NeurIPS 2021 Work- shop on Deep Generative Models and Downstream Applications (2021),https: //openreview.net/forum?id=qw8AKxfYbI

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Advances in Neural Information Processing Systems36, 78723–78747 (2023)

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the Computer Vision and Pattern Recognition Conference

Reference 24

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: European Conference on Computer Vision

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Advances in Neural Information Processing Systems38, 108999–109019 (2026)

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Zenodo (2021)

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Advances in Neural Information Processing Systems37, 76177–76209 (2024)

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Advances in neural information processing systems35, 26565–26577 (2022)

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recog- nition

Reference 30

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: The Fourteenth International Con- ference on Learning Representations (2026),https://openreview.net/forum?id= 11dzFZ2UM1

Reference 31

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Advances in neural information processing systems36, 36652–36663 (2023) 18 X

Reference 32

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: European Conference on Computer Vision (ECCV)

Reference 33

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 34

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: European conference on computer vision

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

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

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps

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This paper cites Transactions on Ma- chineLearningResearch(2024),https://openreview.net/forum?id=a68SUt6zFt, featured Certification.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Transactions on Ma- chineLearningResearch(2024),https://openreview.net/forum?id=a68SUt6zFt, featured Certification

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: The Twelfth International Conference on Learning Representa- tions (2024),https://openreview.net/forum?id=di52zR8xgf

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This paper cites In: The Eleventh International Conference on Learning Representations (2023),https://openreview.net/forum?id=FjNys5c7VyY Anchoring and Steering Diffusion 19.

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization

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Observation 2f56e103-62be-4333-825d-becf26801f66 · outbound

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: International conference on machine learning

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This paper cites Advances in Neural Information Processing Systems36, 3536–3559 (2023).

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Advances in Neural Information Processing Systems36, 3536–3559 (2023)

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the Fifth BlackboxNLP workshop on analyzing and interpreting neural networks for NLP

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Observation 649d332b-5fe2-4bbb-bd20-21c1d8f93042 · outbound

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

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: The Thirteenth International Confer- ence on Learning Representations (2024)

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This paper cites Advances in neural information processing systems35, 36479–36494 (2022).

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Advances in neural information processing systems35, 36479–36494 (2022)

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the AAAI Conference on Artificial Intelligence

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (2022),https://openreview.net/forum?id=M3Y74vmsMcY

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Interna- tional Conference on Learning Representations (2021),https://openreview.net/ forum?id=PxTIG12RRHS

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This paper cites In: Forty-second In- ternational Conference on Machine Learning (2025),https://openreview.net/ forum?id=JpbqiD7n9r 20 X.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Forty-second In- ternational Conference on Machine Learning (2025),https://openreview.net/ forum?id=JpbqiD7n9r 20 X

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Pro- ceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni- tion

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Observation 2eacb267-0bcd-4444-997e-0a38777a3636 · outbound

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

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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Observation 89e42825-193f-4e1d-8467-76305b2f1c92 · outbound

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

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Observation d01d8e68-346a-48fd-bd17-e467069dd6f1 · outbound

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the AAAI Conference on Artificial Intelligence

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Observation 3659f0ff-467d-47dc-b5fa-6219e52f566e · outbound

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Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Qwen-Image Technical Report

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Observation bf726995-3107-46cb-8a8f-2cdf2a790251 · outbound

This paper cites In: NeurIPS 2023 Workshop on Regu- latable ML (2023),https://openreview.net/forum?id=8WH2t9F0Ip.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: NeurIPS 2023 Workshop on Regu- latable ML (2023),https://openreview.net/forum?id=8WH2t9F0Ip

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Observation cc66d1d6-e453-4a7c-bece-c6e9ec8242fc · outbound

This paper cites In: European Conference on Computer Vision (ECCV) (2024).

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: European Conference on Computer Vision (ECCV) (2024)

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Observation 400b9bdb-b2cc-444f-8175-dfc411372fe3 · outbound

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

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

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Observation 7d810b4f-c898-455e-8aff-7d49bd013f57 · outbound

This paper cites In: Proceedingsofthe37thInternationalConferenceonNeuralInformationProcessing Systems.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedingsofthe37thInternationalConferenceonNeuralInformationProcessing Systems

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Observation 0061446d-843a-4116-829a-f6a7bc1fadaa · outbound

This paper cites In: Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2025).

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2025)

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Observation 704bc3e4-de5c-4d93-82a7-3e2ab94b4521 · outbound

This paper cites Determinism of Randomness: Prompt-Residual Seed Shaping for Diffusion Generation.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Determinism of Randomness: Prompt-Residual Seed Shaping for Diffusion Generation

Reference 72

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source=pdf_text observed=2026-08-01T11:42:04.338889Z digest=sha256:65651939032e4155898b5ebc9d6656e1b7ff0286ff567250ceb21a33bea5799b

Observation 7b5a7178-0516-4de5-88e0-570ad7f5e757 · outbound

This paper cites an unresolved cited work.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

Reference 73

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source=pdf_text observed=2026-08-01T11:42:04.342991Z digest=sha256:5b072cae7972b6e3dc792196982bcf993c3372e19b5dd7f240d1547dea2496e3

Observation ee7ef870-2b83-4898-a19d-8c632b92cf3b · outbound

This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: Proceedings of the AAAI Conference on Artificial Intelligence

Reference 74

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source=pdf_text observed=2026-08-01T11:42:04.346663Z digest=sha256:4fb1133f4ac251848291d0ae742c5b759d469850cad4eb358eb9f62d29199ce3

Observation 520ad7a9-ef5c-4dda-8086-996293f82701 · outbound

This paper cites an unresolved cited work.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time Unresolved cited work

Reference 75

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source=pdf_text observed=2026-08-01T11:42:04.350578Z digest=sha256:d553fb533b8f5ca7e8dae6214c0d649356fa133aa574bd8944bfd8b08e67119c

Observation 272c4991-1607-48a1-bede-7a2561b59c1f · outbound

This paper cites In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 76

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source=pdf_text observed=2026-08-01T11:42:04.354691Z digest=sha256:e495bdeaee4e036782d6518f7d454f05c94242a8afead62b7ba0e4826166ed9c

Observation 14785e13-c499-4934-8054-7ddb675e0bc3 · outbound

This paper cites In: International Conference on Computer Vision (2025).

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time In: International Conference on Computer Vision (2025)

Reference 77

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source=pdf_text observed=2026-08-01T11:42:04.358555Z digest=sha256:a00927fa963156e8434d294064c4f9088e4a6cd6acfafb0ebfcd9f4015b80d5e

Observation e65867a9-e216-4ada-9cf4-ff3f08bd7efe · outbound

This paper cites 2w(t) ∂zt ∂z ⊤ ∂ˆϵϕ(zt;c, t) ∂zt ⊤ (ˆϵϕ(zt;c, t)−ϵ) # . (S3) Sincez t =α tz+σ tϵ, we have ∂zt ∂z =α tI. (S4) Substituting yields ∇zLDiff =E t,ϵ.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time 2w(t) ∂zt ∂z ⊤ ∂ˆϵϕ(zt;c, t) ∂zt ⊤ (ˆϵϕ(zt;c, t)−ϵ) # . (S3) Sincez t =α tz+σ tϵ, we have ∂zt ∂z =α tI. (S4) Substituting yields ∇zLDiff =E t,ϵ

Reference 78

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source=pdf_text observed=2026-08-01T11:42:04.362442Z digest=sha256:67fa2a9b9e7a7529185713c7ace5389cea348fbc04ca53737f073150082e5629

Observation 392fcd14-2f88-4e2a-b8b8-ecbf1940ccaa · outbound

This paper cites As shown in Table S2 (top), the CLIP-only prior (Nlp=0) improves the standard baseline, while apply- ing LP-SDS optimization (Nlp >0) further boosts performance.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time As shown in Table S2 (top), the CLIP-only prior (Nlp=0) improves the standard baseline, while apply- ing LP-SDS optimization (Nlp >0) further boosts performance

Reference 79

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source=pdf_text observed=2026-08-01T11:42:04.367066Z digest=sha256:efeb6c3f9f8addac9b0c080f69a0cec8359183b4fd76ee3a77f9c1696cdb5ce2

Observation 5a0eb241-8c53-432e-b663-7fbfbbb0b5fc · outbound

This paper cites and", "or.

Anchoring and Steering Diffusion: Enhancing the Faithfulness of Text-to-Image Generation at Inference Time and", "or

Reference 80

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source=pdf_text observed=2026-08-01T11:42:04.371328Z digest=sha256:9040b11f83afc64e0f6518cb91a6958f6087fbfcc3501e97cd90263c941099d9

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