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Paper Citation Record · LEDGER

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization

As of 13 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2412.14174.

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

pith.paper-citation-record.v1
2412.14174 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:43:51.855934Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

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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

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

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  • verified fuzzy8
  • unresolved26
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7ee7f2e3-0041-4fc5-841a-385233597ab0 · outbound

This paper cites an unresolved cited work.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Unresolved cited work

Reference 1

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Unresolved cited work

Reference 2

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Observation 1eb45aff-a1e0-491f-b1a4-423b8e7efc06 · outbound

This paper cites In: Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization In: Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T

Reference 3

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Observation 60350135-3996-4b34-ac6e-71fe28aff178 · outbound

This paper cites Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis

Reference 4

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Unresolved cited work

Reference 5

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Observation 7927ae61-eaae-455a-acaf-544ab61f2328 · outbound

This paper cites In: Proceed- ings of the sixth annual conference on Computational learning theory - COLT ’93.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization In: Proceed- ings of the sixth annual conference on Computational learning theory - COLT ’93

Reference 6

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Observation 814ec2c7-3b23-4522-aca7-987640b11886 · outbound

This paper cites Optimizing Prompts for Text-to-Image Generation.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Optimizing Prompts for Text-to-Image Generation

Reference 7

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Observation cd2ded41-56f3-4697-99c5-4af9b066dead · outbound

This paper cites MIT Press (Apr 1992), google-Books-ID: 5EgGaBkwvWcC.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization MIT Press (Apr 1992), google-Books-ID: 5EgGaBkwvWcC

Reference 8

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Observation acd6a5ab-320c-470a-b6f3-e84612715346 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization LoRA: Low-Rank Adaptation of Large Language Models

Reference 9

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Observation 40f279b5-663e-4ec1-882f-a9ab19e071c2 · outbound

This paper cites Dover Publications, Inc (1977).

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Dover Publications, Inc (1977)

Reference 10

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Observation 6829dd30-6610-4333-aa41-25b2c5053b1c · outbound

This paper cites Courier Corporation (1979).

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Courier Corporation (1979)

Reference 11

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Unresolved cited work

Reference 12

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Unresolved cited work

Reference 13

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Observation 872f8fb3-deab-4d30-8a4f-2e9deeb2a353 · outbound

This paper cites International Journal of Machine Learning and Computing 7(1), 9–12 (Feb 2017).

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization International Journal of Machine Learning and Computing 7(1), 9–12 (Feb 2017)

Reference 14

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Observation 8d70b5a4-8ae3-4581-9841-fcd8c1b9e739 · outbound

This paper cites Beyond Prompts: Exploring the Design Space of Mixed-Initiative Co-Creativity Systems.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Beyond Prompts: Exploring the Design Space of Mixed-Initiative Co-Creativity Systems

Reference 15

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Observation 3af5ff54-d44b-4453-a7c4-97bab2539422 · outbound

This paper cites In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Reference 16

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Unresolved cited work

Reference 17

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This paper cites Leonardo47(2), 135–141 (Apr 2014).

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Leonardo47(2), 135–141 (Apr 2014)

Reference 18

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Observation a4053358-e5ca-40f8-b72b-d361fcabcabb · outbound

This paper cites Leonardo42(5), 476–477 (Oct 2009).

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Leonardo42(5), 476–477 (Oct 2009)

Reference 19

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Observation bd5a4147-d32e-4e26-8ff4-340155f9cdbb · outbound

This paper cites In: Proceedings of the 25th International Academic Mindtrek Conference.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization In: Proceedings of the 25th International Academic Mindtrek Conference

Reference 20

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Observation c3fc7e74-f777-46bc-ac74-f1eb410ce34c · outbound

This paper cites In: Proceedings of the 46th International ACM SIGIR Confer- ence on Research and Development in Information Retrieval.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization In: Proceedings of the 46th International ACM SIGIR Confer- ence on Research and Development in Information Retrieval

Reference 21

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Observation 19bc88ef-545c-4abb-8cdf-0b7817f9bd1f · outbound

This paper cites In: Proceedings of the 38th International Conference on Machine Learning.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization In: Proceedings of the 38th International Conference on Machine Learning

Reference 22

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Observation b196cf59-fff0-4718-bc7d-41669a9a0c9c · outbound

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

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 23

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization In: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems

Reference 24

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Unresolved cited work

Reference 25

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Models

Reference 26

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation

Reference 27

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Unresolved cited work

Reference 28

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization In: Koyejo, S., Mohamed, S., Agar- wal, A., Belgrave, D., Cho, K., Oh, A

Reference 29

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This paper cites In: Proceedings of the 32nd International Conference on Machine Learning.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization In: Proceedings of the 32nd International Conference on Machine Learning

Reference 30

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Zeroth-Order Optimization Meets Human Feedback: Provable Learning via Ranking Oracles

Reference 31

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Reference 32

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Unresolved cited work

Reference 33

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Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization FABRIC: Personalizing Diffusion Models with Iterative Feedback

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:43:51.839944Z digest=sha256:eb398803407805c44e3ede864d3ecebe23492df92f57e3a1720480645f4ac479

Observation e46424b5-4ece-438d-b9b1-15237378cba7 · outbound

This paper cites ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T18:43:51.844097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:43:51.844097Z digest=sha256:9804549d8f8d63c43a1a9091718152f23deed10ca39bd20d85fe8c0bf73711d0

Observation 324217a0-d968-4c78-85c5-ca877bbe76d8 · outbound

This paper cites Human Preference Score: Better Aligning Text-to-Image Models with Human Preference.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Human Preference Score: Better Aligning Text-to-Image Models with Human Preference

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-12T18:43:51.848176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:43:51.848176Z digest=sha256:0d0f92a0f408c24dbef1efcbec3bd3c70d0765191388f097116e0c44e5d15171

Observation c18a323f-3a7c-4b42-b4bf-6aeea607f239 · outbound

This paper cites Transactions on Machine Learning Research (2022),\url{https:// openreview.net/forum?id=AFDcYJKhND}, featured Certification.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Transactions on Machine Learning Research (2022),\url{https:// openreview.net/forum?id=AFDcYJKhND}, featured Certification

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:43:52.430864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T18:43:51.852502Z digest=sha256:2a0badd00345dd7305b4fd11f363baf99beffabe353b289d913f4d8ecc443512

Observation 30e07c84-6747-4cd2-b80b-b4f295628d48 · outbound

This paper cites Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners.

Steering Large Text-to-Image Model for Abstract Art Synthesis: Preference-based Prompt Optimization and Visualization Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T18:43:51.855934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:43:51.855934Z digest=sha256:c34618fbd7021edd9c6db8485a5cfb341c98dc24c8f7ba03d8c0297e1106731a

Pith citing papers

No inbound Pith citation observations are available.