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Paper Citation Record · LEDGER

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt

As of 11 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 3 inbound Pith citation observations for arXiv:2501.13554.

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

pith.paper-citation-record.v1
2501.13554 v3

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:53:51.323441Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:47:00.650209Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T05:49:40.853023Z

Reference resolution

39 of 39 outbound references displayed

  • verified exact3
  • verified fuzzy14
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fc6845f7-13fa-47c1-833c-8c34af16ca03 · outbound

This paper cites ORACLE: Leveraging Mutual Information for Consistent Character Generation with LoRAs in Diffusion Models.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt ORACLE: Leveraging Mutual Information for Consistent Character Generation with LoRAs in Diffusion Models

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.176731Z digest=sha256:25dded2f67e7b1adaf54873615a89d6b9822bdc387d5ded4232a5754b45eedd9

Observation 774f84a8-2dd6-4cc4-bfbc-9751485ca223 · outbound

This paper cites The Chosen One: Consistent Characters in Text-to-Image Diffusion Models.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt The Chosen One: Consistent Characters in Text-to-Image Diffusion Models

Reference 3

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unresolved
no resolver link, observed 2026-08-10T15:53:51.185569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.185569Z digest=sha256:8ac5b27a43885592bc51c71395571abf85b003946432c83718733eef95f57a79

Observation 62845794-e79d-43b7-9299-2825ae08110f · outbound

This paper cites Reproducible scaling laws for contrastive language-image learning.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Reproducible scaling laws for contrastive language-image learning

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.881835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.194119Z digest=sha256:7eb4270a356d1e9fbe404da5b6363c540c74e18875ffbf8f3ed4d92fe0441fa5

Observation cfdab819-25e2-4db6-91fe-952ad50bdb00 · outbound

This paper cites Jaemin Cho, Yushi Hu, Roopal Garg, Peter Anderson, Ranjay Krishna, Jason Baldridge, Mohit Bansal, Jordi Pont-Tuset, and Su Wang.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Jaemin Cho, Yushi Hu, Roopal Garg, Peter Anderson, Ranjay Krishna, Jason Baldridge, Mohit Bansal, Jordi Pont-Tuset, and Su Wang

Reference 6

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-10T15:53:51.686028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.197985Z digest=sha256:49c6873d2de41463fa8f43db8170391c098887ae56106ee7fd765d0848cd8110

Observation 322cb7eb-be7e-4086-9064-b4f68de41345 · outbound

This paper cites DreamArtist++: Controllable One-Shot Text-to-Image Generation via Positive-Negative Adapter.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt DreamArtist++: Controllable One-Shot Text-to-Image Generation via Positive-Negative Adapter

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.201883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.201883Z digest=sha256:6000d1112bd8d677c83742d983dfb18b46e76cb0b176c3b3f922dab6101b21d9

Observation efe65192-8c09-4e25-83df-02e20e086d17 · outbound

This paper cites Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.210081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.210081Z digest=sha256:d7d0f37b20cd61b14345c152b534a179ccac768a1ba2031f38594e2e6931078a

Observation 7fc6894b-3c21-4283-bbe2-d1f6c0b2cf52 · outbound

This paper cites Highly Personalized Text Embedding for Image Manipulation by Stable Diffusion.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Highly Personalized Text Embedding for Image Manipulation by Stable Diffusion

Reference 10

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unresolved
no resolver link, observed 2026-08-10T15:53:51.214030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.214030Z digest=sha256:4795a39ce7684dfcb4e06eb553ef93a282c0a10aa270336230236b543a338551

Observation 7e19a3e2-b09a-48d1-9fc2-a021c6b72357 · outbound

This paper cites Clipscore: A reference-free evaluation metric for image captioning.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Clipscore: A reference-free evaluation metric for image captioning

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.872265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.218453Z digest=sha256:4263c80edef8e67a426f99b8567c8303f3f8bf9acb9ba989dbd62adb5ce76b5e

Observation 059333a3-d376-476d-90e3-99b011060588 · outbound

This paper cites Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.222171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.222171Z digest=sha256:6ea954e9590214bd304ef94920766fc13a6305a1ebe783559f332d603c4d5eee

Observation cdb36812-5f19-48fa-ad18-bea97a6f2362 · outbound

This paper cites Get what you want, not what you don’t: Image content suppression for text-to-image diffusion models.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Get what you want, not what you don’t: Image content suppression for text-to-image diffusion models

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.862338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.225891Z digest=sha256:12405328be8bd4f60c815ca70f101f770555c3a62bf2220c30039b7e1050fed6

Observation b8ba096e-6e7f-4b90-8542-7b6f17b551d9 · outbound

This paper cites Contextual Knowledge Pursuit for Faithful Visual Synthesis.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Contextual Knowledge Pursuit for Faithful Visual Synthesis

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.233075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.233075Z digest=sha256:f9f228102ae46751c3c70313a6b7a3a3a5fa2ec46b93dbc59bf2706f78fe11f7

Observation 8cad5956-31ef-4db3-97a9-c96186e46b8c · outbound

This paper cites Improving generation and evaluation of vi- sual stories via semantic consistency.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Improving generation and evaluation of vi- sual stories via semantic consistency

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.851669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.236409Z digest=sha256:8437a5c5da7230734d1abd4561ae4b5b8fab983ad098eb899926b57f751bedc0

Observation 1a80d23c-85cf-4a52-a098-e8179312d231 · outbound

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

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.239510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.239510Z digest=sha256:aa9f1540817ffea21a1e0f1e550a05e794fc5d8b4b6b1f7091b684e29144db06

Observation 361c453d-749f-488e-bb3f-67ed401ec487 · outbound

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

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 18

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unresolved
no resolver link, observed 2026-08-10T15:53:51.242860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.242860Z digest=sha256:6cb4a57a5e230e94cd28e16807b3ca2653269ef822684fc17db539bb28f448f9

Observation da41d3ce-90a0-4159-a932-be96dfcea1a3 · outbound

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

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.841258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.246420Z digest=sha256:d58827f7376c061fe15714e6f2715917cea385bb5eb1950edc03bfd46da26449

Observation 1a2a8e1a-6dfc-4530-b405-bb5f6cff3f6d · outbound

This paper cites Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.249543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.249543Z digest=sha256:c47f4327e2d10122c3f331932cfb9bab4eb484b391821d6516124a099d7bc48c

Observation 5f9d90cc-b744-493f-83b4-bb81bddbf676 · outbound

This paper cites InstantBooth: Personalized Text-to-Image Generation without Test-Time Finetuning.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt InstantBooth: Personalized Text-to-Image Generation without Test-Time Finetuning

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.252934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.252934Z digest=sha256:37dbab7c4b534871ffe6c7a061973a852eb9ae77e6cff4f62442024d4903ebb5

Observation 6bf6a840-afe4-4a59-97d3-37fb6d9cd267 · outbound

This paper cites StoryImager: A Unified and Efficient Framework for Coherent Story Visualization and Completion.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt StoryImager: A Unified and Efficient Framework for Coherent Story Visualization and Completion

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.256174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.256174Z digest=sha256:7abc24277761282183d689a5dd0a9454e362dcabd42c12c5426a9b57b6aaac4d

Observation bfebf185-0118-439e-a94e-79f687a40a51 · outbound

This paper cites Training-Free Consistent Text-to-Image Generation.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Training-Free Consistent Text-to-Image Generation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.259500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.259500Z digest=sha256:d5c91025725c01af635599eb69d2c04ca647dd32191fbaf22af9c419cfab01eb

Observation 446b7499-3aeb-4d20-a9ee-c5cede2c0e59 · outbound

This paper cites MagicScroll: Nontypical Aspect-Ratio Image Generation for Visual Storytelling via Multi-Layered Semantic-Aware Denoising.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt MagicScroll: Nontypical Aspect-Ratio Image Generation for Visual Storytelling via Multi-Layered Semantic-Aware Denoising

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-10T15:53:51.477793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.267076Z digest=sha256:889c36f7579707f4d209702aba392dba27cf44f3c38dd1bc16e0e845b070239c

Observation 0944f42b-7558-4a0c-affc-f07ec2f9673d · outbound

This paper cites CharacterFactory: Sampling Consistent Characters with GANs for Diffusion Models.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt CharacterFactory: Sampling Consistent Characters with GANs for Diffusion Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.270878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.270878Z digest=sha256:00dd05364f305f3f3207f4669be134931f2a84744d9e4a5f28927e2e36b886ed

Observation a0e16d60-5f0d-4563-b1fa-a0d19c91b1f6 · outbound

This paper cites SEED-Story: Multimodal Long Story Generation with Large Language Model.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt SEED-Story: Multimodal Long Story Generation with Large Language Model

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.274934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.274934Z digest=sha256:ce7fbfe734a340130c62986bff5792ef9b85ce722cb56abf700460658a9ffc4e

Observation 02b608d5-d45c-4f54-92db-9998115d9ae9 · outbound

This paper cites StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.278768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.278768Z digest=sha256:0bef0763d36b3f914102a3915934614921a2486909959fa7c25f897e3041854a

Observation 62f77ced-b7d6-4faf-a975-00f68fddc8a2 · outbound

This paper cites an unresolved cited work.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-10T15:53:51.828947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.282763Z digest=sha256:8ba3b8b02cdc4cfbc573185d7a749539bf9622f724e1549acc1b5ca12cb517dd

Observation fa214e74-5bbd-414b-80e7-e29343f6def1 · outbound

This paper cites an unresolved cited work.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-10T15:53:51.806425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.289898Z digest=sha256:5a59cbc42147784ff8f09059cb73a9c9d990ab7537d3454a993fc4d93ea286c8

Observation 31606e8c-772d-46b5-93e4-1f140d45aeaa · outbound

This paper cites All generated images based on SDXL are produced at a resolution of 1024 × 1024 using a Quadro RTX 3090 GPU with 24GB VRAM.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt All generated images based on SDXL are produced at a resolution of 1024 × 1024 using a Quadro RTX 3090 GPU with 24GB VRAM

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.796042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.293859Z digest=sha256:b656260a2d52d9baf22faf396e4cc916c71a1bc0642c4e7222c7beb31e2c89ab

Observation 5c9d997e-80d5-4ba4-9395-a9f21c4cf8ee · outbound

This paper cites • The official implementation of PhotoMaker (Li et al., 2023b) at https://github.com/ TencentARC/PhotoMaker.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt • The official implementation of PhotoMaker (Li et al., 2023b) at https://github.com/ TencentARC/PhotoMaker

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.785745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.298775Z digest=sha256:3a64f367874320a951fbb1052588743fc6451ed00dad477a5f8008c8253f4a04

Observation e629ec19-c21d-4926-b56c-bcc00892c1c3 · outbound

This paper cites a photo of a beautiful girl walking on the street.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt a photo of a beautiful girl walking on the street

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.775029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.302735Z digest=sha256:f3f5151220094875ce92c330ca38521b4a997e21366fdcbcfc1266a68f4b278e

Observation 1bae477a-d43b-4cf5-b031-7a0445939a17 · outbound

This paper cites Specifically, we kept the cEOT part of the text embedding unchanged during the SVR process and used this text embedding to generate images.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Specifically, we kept the cEOT part of the text embedding unchanged during the SVR process and used this text embedding to generate images

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.764726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.307270Z digest=sha256:5f7341bc1c9d1cc31659992de2c5c1d52a4c0a1c5a5ee082878895b3f5db8710

Observation c2c758b9-a864-49f7-923e-61a71a4c7dfe · outbound

This paper cites By using different seeds, our method 1Prompt1Story can generate images with diverse backgrounds while maintaining a consistent identity.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt By using different seeds, our method 1Prompt1Story can generate images with diverse backgrounds while maintaining a consistent identity

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.752923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.311301Z digest=sha256:8843ce1bad75ad30fa6ef8a23446e737821b70adbf0f9e70b1927ef82b4081f3

Observation 3ec1f21a-d65e-4aea-9fb2-4915e464c7c4 · outbound

This paper cites By defining multiple subjects in the identity prompt, our method generates images featuring multiple characters, each maintaining good identity consistency.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt By defining multiple subjects in the identity prompt, our method generates images featuring multiple characters, each maintaining good identity consistency

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.741387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.315302Z digest=sha256:3988365cf1fceac396e3e78e208a653b2c536c1091f5260460caccbe5b4c485c

Observation f1cbaca9-08eb-44e4-b985-f92789cf204e · outbound

This paper cites an unresolved cited work.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Unresolved cited work

Reference 38

Resolution
verified exact
raw_fallback, observed 2026-08-10T15:53:51.424373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.319559Z digest=sha256:c78b58aecd065a441f81a7a5b02b4d0705c1b83795379c3f8af7904ff22adcff

Observation ee085a30-49fb-4f2e-9fc2-eb337b83f5f7 · outbound

This paper cites sliding window.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt sliding window

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.728874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.323441Z digest=sha256:9d8cbff9bfda4e40caf48ab1e5b62839ab8f3dd16f1473bbd9b0099cc8f22568

Observation 3abae216-a666-4222-aa09-61a486479c4f · outbound

This paper cites P+: Extended Textual Conditioning in Text-to-Image Generation.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt P+: Extended Textual Conditioning in Text-to-Image Generation

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.262950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.262950Z digest=sha256:243fe37845762fec1fa6171d967c70e07f21790ab02fc53ce366bea708912e6a

Observation f0094f7c-6ef1-456d-977a-f58c9f1c4436 · outbound

This paper cites PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.229741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.229741Z digest=sha256:e64cb4f4dc287f20136876057c5991e592f59c73f3f5f6431615543377a41309

Observation f64a7736-b697-4800-a38b-c7e9363e4e34 · outbound

This paper cites We separately update the text embeddings produced by each encoder.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt We separately update the text embeddings produced by each encoder

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.817590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.286338Z digest=sha256:f347b6dddefc50ac3654402c9c2d7581a5a2e92730a64285a46fd079c1e0261e

Observation 19e9b0cf-c3da-4cfc-be31-e70b9e6e208e · outbound

This paper cites DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.205906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.205906Z digest=sha256:85e829ca39e5951fecc94611ef1a57ee7c819fdcffff28ebac580509f7ac395b

Observation 8723eb07-4343-4d08-995e-03afdc83cc98 · outbound

This paper cites AutoStudio: Crafting Consistent Subjects in Multi-turn Interactive Image Generation.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt AutoStudio: Crafting Consistent Subjects in Multi-turn Interactive Image Generation

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-10T15:53:51.189938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:53:51.189938Z digest=sha256:be8d449ef40cbbdb19b1b2fbdccbb9abd7ed2f67271b5d61afbc7f29cb0ee026

Observation 0be53bb5-1be4-4466-a220-d9de6c7099c8 · outbound

This paper cites Cross- image attention for zero-shot appearance transfer.

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt Cross- image attention for zero-shot appearance transfer

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:53:51.891430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T15:53:51.181415Z digest=sha256:d23f810a5fdf602ca23980ffed5c24bc8a5984dd5e46c3785ab20ed0ce8d27dc

Pith citing papers

Observation f27955d2-1ff9-4e2d-a38a-b1021b68719d · inbound

StorySync: Training-Free Subject Consistency in Text-to-Image Generation via Region Harmonization cites this paper.

StorySync: Training-Free Subject Consistency in Text-to-Image Generation via Region Harmonization One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T10:47:00.650209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:47:00.650209Z digest=sha256:fbaaa80379b9d26bc5e6b75f7caecf6ba5302af99fba353c5f63b636ff32fd99

Observation 48ed00b0-51ee-4e4c-b896-f05bc8aee780 · inbound

RealDiffusion: Physics-informed Attention for Multi-character Storybook Generation cites this paper.

RealDiffusion: Physics-informed Attention for Multi-character Storybook Generation One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:27:24.743033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-13T06:24:23.155286Z digest=sha256:9dc89b89ffa26d5e1e1f4ad9a379a5d11c9b4cd2d7eaaf1d831620c0505873fa

Observation d6ed79e4-23c9-4958-959c-4195115b0b7d · inbound

AttriStory: Fine-grained Attribute Realization for Visual Storytelling with Diffusion Models cites this paper.

AttriStory: Fine-grained Attribute Realization for Visual Storytelling with Diffusion Models One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:49:40.854764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T05:47:49.309008Z digest=sha256:ae70c81b3d30365d41cc032a574148315cddc9d7d9d28e615c7dd573e12fdc39