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Paper Citation Record · LEDGER

ComposeAnything: Composite Object Priors for Text-to-Image Generation

As of 18 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 1 inbound Pith citation observation for arXiv:2505.24086.

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

pith.paper-citation-record.v1
2505.24086 v1

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:40:43.911455Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T11:16:15.417396Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

64 of 64 outbound references displayed

  • verified exact1
  • verified fuzzy50
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 68034726-4471-4350-aad7-d7c6f1822622 · outbound

This paper cites A-star: Test-time attention segregation and retention for text-to-image synthesis.

ComposeAnything: Composite Object Priors for Text-to-Image Generation A-star: Test-time attention segregation and retention for text-to-image synthesis

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:55.301072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:37.801554Z digest=sha256:b35ccadfb29dda66dd7d357c8d125cd8dae486331e607568c87d6b3d6cab677f

Observation d65f9b27-2103-4f6f-b3ba-06fa55ef3167 · outbound

This paper cites Blended diffusion for text-driven editing of natural images.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Blended diffusion for text-driven editing of natural images

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:55.139993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:37.869669Z digest=sha256:2cdcfb95a135c245f91942a29b0e53a74235c2a5578e42f1b9e89f28f4a5b51d

Observation 2fe8b983-02f5-4a09-97d5-7740bf2b1bd8 · outbound

This paper cites an unresolved cited work.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:40:54.988323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:38.006453Z digest=sha256:0a2cfd0c09fae5cd0d38f09c20536b2c39587a4d0a17fb24c149ce4550be0229

Observation 9e0a6caa-924d-4a55-a9c8-cbc59e04f795 · outbound

This paper cites Attend-and-excite: Attention- based semantic guidance for text-to-image diffusion models.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Attend-and-excite: Attention- based semantic guidance for text-to-image diffusion models

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:54.866774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:38.092173Z digest=sha256:d4b2733750a77939a5169fd5d93666b724f636c1eb5967262a42e1ca060efd55

Observation 82645f13-2595-4ba5-a36c-c94a66c9e467 · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

ComposeAnything: Composite Object Priors for Text-to-Image Generation PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:38.168638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:38.168638Z digest=sha256:57427521c02a4d9e71588f0ed1694f24bdb6d8fc9c3074140a5e987c85990d7d

Observation e8d545d1-2154-4d08-9c91-575a54f48171 · outbound

This paper cites PIXART-{\delta}: Fast and Controllable Image Generation with Latent Consistency Models.

ComposeAnything: Composite Object Priors for Text-to-Image Generation PIXART-{\delta}: Fast and Controllable Image Generation with Latent Consistency Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:38.255445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:38.255445Z digest=sha256:58d5b6107e1f52370a0d947a103baf435c9ec8dc4048c30f7ff4fc54efad6728

Observation d8a42d9a-d423-4b2b-b618-02fdcec5bcfd · outbound

This paper cites Geodiffu- sion: Text-prompted geometric control for object detection data generation.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Geodiffu- sion: Text-prompted geometric control for object detection data generation

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:54.755805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:38.311344Z digest=sha256:67aed7c2ac4bcff62c2702cec88744361e25d5373a02ad64e858d2a87906a082

Observation 03e782f1-16fc-4cf4-b772-dd8bb9d97b77 · outbound

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

ComposeAnything: Composite Object Priors for Text-to-Image Generation Training-free layout control with cross-attention guidance

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:54.629326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:38.414953Z digest=sha256:3fd66eae1cf5c530408d998b7080656406d62368cce55aa095bd5519b62229de

Observation bb12308a-1d61-482d-a749-87f6c1db5053 · outbound

This paper cites Zero- shot spatial layout conditioning for text-to-image diffusion models.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Zero- shot spatial layout conditioning for text-to-image diffusion models

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:54.486001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:38.533038Z digest=sha256:aa655ee734fe88871435b1f9ca1e444efe27d63729db958fc2cdab03c5006eb8

Observation 3524a5a9-7d50-48f3-838b-05cc82ebca69 · outbound

This paper cites Be yourself: Bounded attention for multi-subject text-to-image generation.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Be yourself: Bounded attention for multi-subject text-to-image generation

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:54.345123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:38.617567Z digest=sha256:faa3bb9d2a34b040f6f65ae64fb9c2452ca25fb161d88bd72fd2206b0c801f29

Observation ae2da873-ff73-42d9-85e4-873a3369bb00 · outbound

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

ComposeAnything: Composite Object Priors for Text-to-Image Generation Scaling rectified flow transformers for high-resolution image synthesis

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:54.217967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:38.686095Z digest=sha256:5657cbaa316039bddec6394cbf47333e6e7569dc2b6bf3a872c40e7f8b7d16d4

Observation 9ab53847-8850-439d-936c-d7cef9d70aef · outbound

This paper cites Training-free structured diffusion guidance for composi- tional text-to-image synthesis.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Training-free structured diffusion guidance for composi- tional text-to-image synthesis

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:54.097333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:38.767766Z digest=sha256:66fe3a042432149177c68f7fba8c6728bca3822fa218870e3da2b48509a955d6

Observation c8810c1a-9ad1-49db-9238-692404325b30 · outbound

This paper cites LayoutGPT: Compositional visual planning and generation with large language models.

ComposeAnything: Composite Object Priors for Text-to-Image Generation LayoutGPT: Compositional visual planning and generation with large language models

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:53.964857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:38.852740Z digest=sha256:0a67cf82dcedc1efab96fdc82ddfb81d62a8cd846685bcc3751426cf51f82dcb

Observation cfcf495c-18e3-4899-a27f-63be290a5669 · outbound

This paper cites Ranni: Taming text-to-image diffusion for accurate instruction following.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Ranni: Taming text-to-image diffusion for accurate instruction following

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:53.834924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:38.921080Z digest=sha256:b491d1e2481ba04df23470da6d6b0ec0ccf9d336b4d5fdf269d78191e9f9d2e6

Observation 5b6ee1ba-681d-4c96-ae36-5af591acf226 · outbound

This paper cites LLM blueprint: Enabling text-to-image generation with complex and detailed prompts.

ComposeAnything: Composite Object Priors for Text-to-Image Generation LLM blueprint: Enabling text-to-image generation with complex and detailed prompts

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:53.693981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:39.040929Z digest=sha256:044fdff138afb41baf26e3464f18507eef5f55d5d1156a2f21f1677c7446a026

Observation 8b04f8f2-ce58-445f-bafd-901fe0d963bb · outbound

This paper cites Check locate rectify: A training-free layout calibration system for text-to-image generation.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Check locate rectify: A training-free layout calibration system for text-to-image generation

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:53.637076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:39.117436Z digest=sha256:748ef96dec4a3f759383494ce6c82016d60e71e3afdfe6015cba8f54c603c3ec

Observation 073ef09a-ef2b-4c7c-9ece-839bd938d4d4 · outbound

This paper cites Initno: Boosting text-to- image diffusion models via initial noise optimization.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Initno: Boosting text-to- image diffusion models via initial noise optimization

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:53.514090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:39.222820Z digest=sha256:474dba7821d9928f8054a1f8e88a1326ef10677f770939cf81b6689cd8b9a4cf

Observation feeb7962-c199-4ec0-9d31-ebb3c5dda594 · outbound

This paper cites Prompt-to- prompt image editing with cross-attention control.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Prompt-to- prompt image editing with cross-attention control

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:53.301968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:39.348295Z digest=sha256:5470367f74cd97fe523257bdb3f32aed42d5db97dadb140e136e0bd913ffe9d4

Observation c0904039-b6e5-4394-8e7a-fcd9ec691359 · outbound

This paper cites Ella: Equip diffusion models with llm for enhanced semantic alignment.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Ella: Equip diffusion models with llm for enhanced semantic alignment

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:53.062615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:39.469217Z digest=sha256:f28851d5e81c9d761860df166dd8217478dd36288fe6b4825bb890a112f2c4e0

Observation 1cb87800-740d-4912-890c-a33e8bd08eec · outbound

This paper cites Scenecraft: An LLM agent for synthesizing 3D scenes as blender code.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Scenecraft: An LLM agent for synthesizing 3D scenes as blender code

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:51.925212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:39.656385Z digest=sha256:e2e405a6c056c068e7ac843074f0e533741d4944955d1a02b011b1a802437b3b

Observation aeeaf5e4-eb27-45cc-b376-493722bce878 · outbound

This paper cites T2I-compBench: A comprehensive benchmark for open-world compositional text-to-image generation.

ComposeAnything: Composite Object Priors for Text-to-Image Generation T2I-compBench: A comprehensive benchmark for open-world compositional text-to-image generation

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:51.414312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:39.797724Z digest=sha256:be968a081d00778cc78a2768b1c5ea570658a5a17773b3e97829269392786acc

Observation a55476c4-6ae5-4b06-9459-a1b86d00acf6 · outbound

This paper cites Composite diffusion: whole >= sparts.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Composite diffusion: whole >= sparts

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:51.269413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:39.928683Z digest=sha256:9f95dc8cb468f1619ea0dc6e84a0905d7b2ea726c734a3f6de28f15f26287acc

Observation 4b10b3e0-3272-4f8d-a446-7fe0b630b896 · outbound

This paper cites Comat: Aligning text-to-image diffusion model with image-to-text concept matching.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Comat: Aligning text-to-image diffusion model with image-to-text concept matching

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:51.070049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:40.097222Z digest=sha256:76ae8c1a347496f7c9305838da9f7cef901e966dd7442e2a0d66c8b870204ff6

Observation fd1a662e-6a5f-47b7-b041-03df0f8bfaa2 · outbound

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

ComposeAnything: Composite Object Priors for Text-to-Image Generation Dense text-to-image generation with attention modulation

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:50.911265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:40.218722Z digest=sha256:e22a28bed285531b3d2c9734b9ab385f9aac11b6ea4af3e3535d910b98dfebb5

Observation 0f4e2416-22ac-4bbc-857c-6dabb588e666 · outbound

This paper cites Evaluating and improving compositional text-to-visual generation.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Evaluating and improving compositional text-to-visual generation

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:50.768601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:40.350719Z digest=sha256:2abdaf311bf1a8c61b14f8612098089282d23cffec60579dd59074c0bbc7dd03

Observation 5dd47991-9fb0-4f94-901b-4cd2cdb0476f · outbound

This paper cites Grounded language- image pre-training.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Grounded language- image pre-training

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:50.621728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:40.490585Z digest=sha256:294840f92924d3ca5e52c82a26e4688b832dfe320010cd8ee242c75c3dfec75d

Observation eb1259b7-ee4c-4208-8e00-4c0ca3320c11 · outbound

This paper cites Con- trolnet ++: Improving conditional controls with efficient consistency feedback.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Con- trolnet ++: Improving conditional controls with efficient consistency feedback

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:50.472757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:40.596658Z digest=sha256:335be9c0924482c3ab817235efeba0b44d11b9a3dafd4c15df0668fbc84e888e

Observation ec9a4110-170b-4211-8556-9f4143272d4d · outbound

This paper cites MuLan: Multimodal-LLM Agent for Progressive and Interactive Multi-Object Diffusion.

ComposeAnything: Composite Object Priors for Text-to-Image Generation MuLan: Multimodal-LLM Agent for Progressive and Interactive Multi-Object Diffusion

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:40.732637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:40.732637Z digest=sha256:167d27ed8ce6a8ab8536910fc550b62dbd773b818f4d473331460867d22a0e8d

Observation 090d0a2d-d84e-49fc-b931-5fe882b57807 · outbound

This paper cites Gligen: Open-set grounded text-to-image generation.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Gligen: Open-set grounded text-to-image generation

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:50.323841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:40.812200Z digest=sha256:7b1f4b9f774042501d0afb491868df5292ca225af15dde5dd5d29a7359855e86

Observation 91127520-46ee-4e50-8bae-810e866f3470 · outbound

This paper cites Divide & bind your attention for improved generative semantic nursing.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Divide & bind your attention for improved generative semantic nursing

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:50.166925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:40.891312Z digest=sha256:030452c67ef5666ec44a70996c4a3fc67b0e951f5b9f4e2e1ac07ea82c0e14e7

Observation 4bcfab99-14c1-4f27-801b-f066b46fb840 · outbound

This paper cites LLM-grounded diffusion: Enhancing prompt understanding of text-to-image diffusion models with large language models.

ComposeAnything: Composite Object Priors for Text-to-Image Generation LLM-grounded diffusion: Enhancing prompt understanding of text-to-image diffusion models with large language models

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:49.971259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:40.984218Z digest=sha256:b16997f58275acd75fc104b5ca8f5c4d9068adffb9a4021bc331776d42bc4cc1

Observation b3124cde-9f18-4e14-9323-af69588c0bfe · outbound

This paper cites Ctrl-adapter: An efficient and versatile framework for adapting diverse controls to any diffusion model.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Ctrl-adapter: An efficient and versatile framework for adapting diverse controls to any diffusion model

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:49.762586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:41.081311Z digest=sha256:e63b3605e79a73a0ffbfc5625054eedc220ce9afdeda6b04f937495a036cb0c4

Observation cda6dede-d791-452b-acd4-6a87897e5872 · outbound

This paper cites Flow Matching for Generative Modeling.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Flow Matching for Generative Modeling

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:41.167945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:41.167945Z digest=sha256:4b740015ca0a150ed9fa3f466c7deaafde9eb4f805500a99d286b83ba5a6b4f8

Observation 4ae7f091-c2e0-4375-98bd-22b4d38eb5f2 · outbound

This paper cites Tenenbaum.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Tenenbaum

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:49.608495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:41.213668Z digest=sha256:3c218922ea8fab092a1f84f0de4dc66a9a024802018f02c41049fe265c8ad52d

Observation 5d873c44-0a0c-418d-9be5-3de11d1abd74 · outbound

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

ComposeAnything: Composite Object Priors for Text-to-Image Generation Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:41.259858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:41.259858Z digest=sha256:4b46bf93d92a4ae0e5daf190e40035b8a48d16c902f77afb99978d8fe4e299af

Observation 54ee920c-4c19-4870-a971-6ff7ecdd67ca · outbound

This paper cites Lewis, Thomas Leung, and W.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Lewis, Thomas Leung, and W

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:49.459542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:41.312373Z digest=sha256:197a95763c3d9655e342f3f415da977d47654fc9ed6e7297356ea19d7569a460

Observation f2ea001d-33a2-41c3-9c70-cb7d0220e42c · outbound

This paper cites Guided image synthesis via initial image editing in diffusion model.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Guided image synthesis via initial image editing in diffusion model

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:49.245890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:41.418479Z digest=sha256:e3aa974782f31495fad32feb475bead6056ecafc4142af5895c98123d64b290c

Observation fc9cffb3-16eb-413f-abba-34326dd0e712 · outbound

This paper cites SDEdit: Guided image synthesis and editing with stochastic differential equations.

ComposeAnything: Composite Object Priors for Text-to-Image Generation SDEdit: Guided image synthesis and editing with stochastic differential equations

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:49.040833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:41.513574Z digest=sha256:b1f20e55e7b7e743fa1036125885249afe76d2f85e68a2f5aca940b3517ec85f

Observation b520383a-2eca-4b8e-b914-2f4979d48d7f · outbound

This paper cites Conform: Contrast is all you need for high-fidelity text-to-image diffusion models.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Conform: Contrast is all you need for high-fidelity text-to-image diffusion models

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:48.825268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:41.602652Z digest=sha256:348f5a4589bcaebc5e76d1be2487696507dd2d8dcae4c2166c27e4f190641182

Observation 4b2a59a2-0603-4c06-a242-5f2440224df4 · outbound

This paper cites T2i- adapter: learning adapters to dig out more controllable ability for text-to-image diffusion models.

ComposeAnything: Composite Object Priors for Text-to-Image Generation T2i- adapter: learning adapters to dig out more controllable ability for text-to-image diffusion models

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:48.504919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:41.659963Z digest=sha256:5baddd06d5c6a368966e9b3f298d0f9881e1f7d11e1d4232f8e86df14f541aeb

Observation 5346d8ee-738a-4304-a71a-7236b7ea0c2c · outbound

This paper cites Compositional text-to-image generation with dense blob representations.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Compositional text-to-image generation with dense blob representations

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:48.228431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:41.749052Z digest=sha256:63c0752eedd08fb9b897cb7a0229341651e440701ccf8a36feb9cb8b27c6c5f3

Observation 5e26fe21-89d2-4974-a2a0-4082312db42d · outbound

This paper cites an unresolved cited work.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:40:47.957166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:41.802344Z digest=sha256:7edc08ad96c0d3382adf46542d84260881ff8194187da153d55f114b6d287ffa

Observation 7694aea0-5f20-4b06-8e30-35e8c34c01b1 · outbound

This paper cites Wuerstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Wuerstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:41.897086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:41.897086Z digest=sha256:0019646931f7ea0ccee0aee2514c666228df670d163a6242c728753174b5deca

Observation a3b029a5-a63a-4501-af56-afb9b898e22a · outbound

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

ComposeAnything: Composite Object Priors for Text-to-Image Generation Grounded text-to-image synthesis with attention refocusing

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:47.649704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:41.942719Z digest=sha256:48f3c6997d8db6bcf6b061a44313e0983b9cfe7a2e747fabd76366e9ea99c532

Observation 9a0a080e-06e1-40fe-85dc-c1284452c161 · outbound

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

ComposeAnything: Composite Object Priors for Text-to-Image Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:42.047049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:42.047049Z digest=sha256:84a8b14e60cf849233becd4b1a5dc038424f96e9938bcf3cff01e57ac516a154

Observation d24b75a6-9660-4d02-b172-94c5b5c60009 · outbound

This paper cites Linguistic binding in diffusion models: Enhancing attribute correspondence through attention map alignment.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Linguistic binding in diffusion models: Enhancing attribute correspondence through attention map alignment

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:47.378735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:42.116848Z digest=sha256:8363aa2320d3835a346f25df1da069203b0508141211d22e0152ec38cc2af0f6

Observation 15550932-8ce3-4d19-8d49-61e0c2fb4ff3 · outbound

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

ComposeAnything: Composite Object Priors for Text-to-Image Generation High-resolution image synthesis with latent diffusion models

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:47.132162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:42.202578Z digest=sha256:ccfd8f6eb569b11de117d5f88a66fbba42753ab30be21ff2a689de798f446ff4

Observation 1508fafa-7444-46c0-9dea-4efdedfc431f · outbound

This paper cites Denoising diffusion implicit models.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Denoising diffusion implicit models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:42.277942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:42.277942Z digest=sha256:8be68d6ea76ff0ded7b32667c222ad91c45fdd8c3ef4e22abe54d8a407a084a6

Observation 48a49361-eed4-41aa-a44f-78257cbe5173 · outbound

This paper cites Object-Attribute Binding in Text-to-Image Generation: Evaluation and Control.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Object-Attribute Binding in Text-to-Image Generation: Evaluation and Control

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:42.368674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:42.368674Z digest=sha256:b55c42d511a2ee156973edb28e6946e63cf886c30830bb5ed65121e9d011577d

Observation bbe460ca-581f-4b72-9e21-c97c5bcedc58 · outbound

This paper cites Plug-and-play diffusion features for text- driven image-to-image translation.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Plug-and-play diffusion features for text- driven image-to-image translation

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:46.871086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:42.426137Z digest=sha256:b7f20a2a972283e2eff25784a5bc09f154a7d515200144c6f783c1a6a6d5a605

Observation e5526c10-5e3a-49af-8f5f-0d868ad041e6 · outbound

This paper cites Dynamic prompt learning: Addressing cross-attention leakage for text-based image editing.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Dynamic prompt learning: Addressing cross-attention leakage for text-based image editing

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:46.660889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:42.498501Z digest=sha256:370cad6db574727c05b8aa80c0204889907d8f2e6200dfdbfc7bdac7b7032a2a

Observation f1437715-5091-4ac5-b53a-a5d2a255be9f · outbound

This paper cites Instancediffusion: Instance-level control for image generation.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Instancediffusion: Instance-level control for image generation

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:46.512652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:42.580342Z digest=sha256:a1398bb42debc19e869bcc8cd5a228a7114571d6e9d73ac5bb00cfe96600bb6f

Observation 9bf73694-fcb1-473d-8d23-a2231c0c542d · outbound

This paper cites Tokencompose: Text-to-image diffusion with token-level supervision.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Tokencompose: Text-to-image diffusion with token-level supervision

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:46.345106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:42.656050Z digest=sha256:2a3edbd7a9983232c2a41c0f22e13b4cc15a0a09542a013cb48e518d219b614a

Observation 95bb1b3f-68c5-4e46-98de-8d2086cdb67a · outbound

This paper cites Hyperseg: Towards universal visual segmentation with large language model, 2024.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Hyperseg: Towards universal visual segmentation with large language model, 2024

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:46.169244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:42.745695Z digest=sha256:875c7f747d68dd7a2ea9de556610f3700110667f361a51fa469b5574f859002f

Observation eff1c02e-1391-4259-8801-1602411f0ff4 · outbound

This paper cites Boxdiff: Text-to-image synthesis with training-free box-constrained diffusion.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Boxdiff: Text-to-image synthesis with training-free box-constrained diffusion

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:45.987633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:42.828176Z digest=sha256:272ccd66cad4ffc6a693e2af3afef3563464797c8f83237570af714a1e67f496

Observation 374eb3bb-b39a-457a-8b90-59c588d812ac · outbound

This paper cites Mastering text- to-image diffusion: Recaptioning, planning, and generating with multimodal LLMs.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Mastering text- to-image diffusion: Recaptioning, planning, and generating with multimodal LLMs

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:45.814538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:42.913181Z digest=sha256:a49352713773a608dba553d4030a2b581afa4a14c9f468efa5cb1238147b4642

Observation bd3743a4-2b16-476d-9a03-5e1bfb2180dd · outbound

This paper cites Reco: Region-controlled text-to-image generation.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Reco: Region-controlled text-to-image generation

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:45.624952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:43.008111Z digest=sha256:9261d88ee2b86697355ffa409cebcf82e6fcdee62259cf6e010c921f0bf724bd

Observation 089b1b99-3426-4303-bf25-1d647def6bff · outbound

This paper cites CreatiLayout: Siamese Multimodal Diffusion Transformer for Creative Layout-to-Image Generation.

ComposeAnything: Composite Object Priors for Text-to-Image Generation CreatiLayout: Siamese Multimodal Diffusion Transformer for Creative Layout-to-Image Generation

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:43.078627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:43.078627Z digest=sha256:b61dba13fc417d842e361729145ddb980b623c0884680920c4d0d3bb9ee833ee

Observation 97c859d1-4ae9-4a4a-8d04-666c22f844dd · outbound

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

ComposeAnything: Composite Object Priors for Text-to-Image Generation Adding conditional control to text-to-image diffusion models

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:43.180221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:43.180221Z digest=sha256:cb3c1343ac35ce2b693781f10c1c5db84b4028d8235a3c7000107ed699ba817c

Observation b2eeaa32-5763-4148-b041-41d873250f9b · outbound

This paper cites Realcompo: Balancing realism and compositionality improves text- to-image diffusion models.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Realcompo: Balancing realism and compositionality improves text- to-image diffusion models

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:45.411207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:43.320114Z digest=sha256:314f9e39478284c2d73f15c853bd21fed260f26af6ebafa83bf81a45ef0d0b2f

Observation d867baac-bc1d-4e27-a2d7-b86e219854ba · outbound

This paper cites Local Conditional Controlling for Text-to-Image Diffusion Models.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Local Conditional Controlling for Text-to-Image Diffusion Models

Reference 61

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:40:44.171990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:43.483636Z digest=sha256:32f6df8cab385c0836d225b35dab3121bbb14f75422fb96043ce0fdd8932e565

Observation e91162e9-cf7f-4726-a32a-aa1b5c773ab5 · outbound

This paper cites Layoutdiffusion: Controllable diffusion model for layout-to-image generation.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Layoutdiffusion: Controllable diffusion model for layout-to-image generation

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:45.189048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:43.635422Z digest=sha256:deb4db7faaadeb36482960df354b4a2bd68519655eef9e1ecf9d15e8d8bbab22

Observation a07c59b3-44df-40fe-8f52-4bb13522d67f · outbound

This paper cites = 3 𝑡!= 0.79 𝑁!.

ComposeAnything: Composite Object Priors for Text-to-Image Generation = 3 𝑡!= 0.79 𝑁!

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:44.990025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:43.782344Z digest=sha256:4cd8a75a81b50044b66f4267861a5da318de2edad7965e670ec9370f4192aa99

Observation 679378dc-3b58-4263-8d02-6352eaf7678d · outbound

This paper cites Objects:.

ComposeAnything: Composite Object Priors for Text-to-Image Generation Objects:

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:40:44.794805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T12:40:43.911455Z digest=sha256:0a3652bc62511d62509586f69865fff7f0960e395491ba632b890e5b18de97f6

Pith citing papers

Observation 9d0ec3a6-6afb-46bf-b667-df7690f4e7f1 · inbound

ETPDesigner: Multi-Agent Orchestration for Interactive Multimodal Electronic Theater Program cites this paper.

ETPDesigner: Multi-Agent Orchestration for Interactive Multimodal Electronic Theater Program ComposeAnything: Composite Object Priors for Text-to-Image Generation

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-01T11:16:15.417396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T11:16:15.417396Z digest=sha256:45b6b035cd7520ba77a77fbfb5ec5da841db6159832c4f370b043e384505ab68