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Paper Citation Record · LEDGER

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

As of 16 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 2026-08-15T06:32:42.880941+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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:37.801554Z digest=sha256:8b75835c17f3537a4ecd2b708ea0bba44f0b33439593e64bf66cf61b1055d1ac

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:37.869669Z digest=sha256:0d94ad4e0fca6921f6b4124a788d40a147a6c24d9c7ee9c5e57ef7277b94935d

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:38.006453Z digest=sha256:a643f057d7008700b141211aec717c5a2d5c7ab66ec1cb5cf543a786dc3502f1

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:38.092173Z digest=sha256:aa0566c8d5c7d04b027fbcbeda56dabe0abe6a04171cfa56822ca1189e9d7323

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=sha256:939b7d46b2d7b1dd7f610bbf6b34af1c9ba575038a8063d9d41570f0bde5654b

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:38.311344Z digest=sha256:a9229512636c8de986bba14bbe78ff9ae999375fff9fdec123c981c1a75afce5

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:38.414953Z digest=sha256:97bad99aab52b1e4791a09b0f5638d83678f27a4849f123cfb9cafc243c86fe8

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:38.533038Z digest=sha256:b1e9fa9f538a659db784973a73f03cb926c3dbadcae8ba6916f1cfee94644ac9

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:38.617567Z digest=sha256:34c246e7532a0beb873a525d0d4c700b1b644fc1aa77aae81ffa73c845d613f6

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:38.686095Z digest=sha256:22f790f7eb9b3e342ca2324257c48bbb00d486d7e235bb239b02236fbd3dc0e5

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:38.767766Z digest=sha256:8eabd911cdb5d3476b99930a2ffabe85300ee7a36710c545156ebd47700bf42c

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:38.852740Z digest=sha256:3e526197b708cae551099204b842d56a80189541b6532e93c71a1ca15420f729

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:38.921080Z digest=sha256:0229ad4519f3de5c3c90b0280d8e348d50a5c5180914f0f9d3af5fe88493700f

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:39.040929Z digest=sha256:12652eefbb3ed30f0f539d0e2c525c8898d9913f5a31547d2b83454ddc0eb9b8

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:39.117436Z digest=sha256:e96a68c79153e62e572696e9ef19b3e47532e5a156a51d3767ea39ecd0df7cca

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:39.222820Z digest=sha256:fd2ea920bcfbe3a963bb29dd89d12afd1e62272afb05a9e23e72209079b3a0dc

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:39.348295Z digest=sha256:49df37d5b6450eb017e564a9e86deb0760b24d1d5c1299e2bb2ed99c72b842a3

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:39.469217Z digest=sha256:b9cbb32eb6b519d5ee14b5815527257f1a95b85646fa24c6290140a39e6b433d

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:39.656385Z digest=sha256:2c3b6a7073df2544032e2edb4011036be67bfb779cf789dfc3b500ac07da4c77

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:39.797724Z digest=sha256:95a88a172667cabdfc921700abe837ce9f131cb0f1e15a4514ccaf25fd3f9e73

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:39.928683Z digest=sha256:a74020578695e38d7eac0127b2c32b2d2a0ae9647752cb45b2749a9fe5fff44e

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:40.097222Z digest=sha256:8065863c94c8c7af109d815103f5a40c2fca60075373b5a2d2e6c9295d6fef73

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:40.218722Z digest=sha256:55115d7a302ed20c7eaa0f763f936804efdf04f1a6a80ca02d729c9d287e2d67

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:40.350719Z digest=sha256:677b2a06b4a71665783e0841f8cbf4cde90565671640d718cc35a84cb601ebb2

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:40.490585Z digest=sha256:4eee7e41db4d87d2a5309f467e9757b204100d3b19e22428d11d6e842683c862

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:40.596658Z digest=sha256:c6907a5b06337e89559e8c20b923e0dc97b7fc76c11ea6993178abfb196a62cf

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=sha256:8374894f27afa02d68f4470d4747d49edcff93452adb95fabfb281a96685ca16

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:40.812200Z digest=sha256:9170b2d9d1e30d1baf5554ceba415517dc76bcf9d0dbae9d4ef7a7ebff508d83

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:40.891312Z digest=sha256:4fd4431ce89948ac7e18beec7ae6ad9e78104a179b340e3d8544bd07b31531f9

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:40.984218Z digest=sha256:98821dcc68caefb36f9912bcaf7adb09dce2c22932089fbd34019b3962f6f695

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:41.081311Z digest=sha256:762f6e39857cc5a5a59c9a796368aa0059a32a08516fe8786c339d8a8b5ab0d7

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:b4bfbed83333f85b17e1b65b733c60031b955074561011483e120cf6c68b6e83

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:41.213668Z digest=sha256:db7882f35d734d6024df8fbd50210af13efb088013688107e0f15cc544a2e377

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=sha256:806de6d71557790e46ffb91433b3a49084e8c6174f8624780e7e6265fafb76b5

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:41.312373Z digest=sha256:8be7fe2c3f7aed951300d0bd73ee2b737d887c5c1cf411ca7e4cf56c083518f6

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:41.418479Z digest=sha256:575a80f6f2cb02e730d5d8ebaaa07553e9e21330feebbcab2e12b3f7801d5d1b

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:41.513574Z digest=sha256:f7d133838288e6f3fb45e986c155ccfe1d61ae248610e6e562597300859bdbe5

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:41.602652Z digest=sha256:54ed877c8fe93d900fa6a50d66b48d7f9dfeb87e2f17b1ac7182f0bd814d3815

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:41.659963Z digest=sha256:8eab73a4082ec61b967d8bb86a5124bff4cef0970e018eb4e30fbfe9d93ca493

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:41.749052Z digest=sha256:3e0c0d00292542b9b7ab061c9efec5cab3e6e14f1f3d6915e334f46a52391052

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:41.802344Z digest=sha256:9816d3effecd1cb2ed052bbc3e44fd705bd2a510952474d660f05d1e2245e49d

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:a381779b5913fa0fb7364237083c19db8c7edfad7e7e472ac97535cf72cb7a41

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:41.942719Z digest=sha256:16678f746cec9eec7f911044ed166aff68fe0942489a8724c925ee34ac688de2

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:42.116848Z digest=sha256:93c193e06bf5e2cb2d2458073971b8964cf426d73dbf2ed466a27fa97f3a1664

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:42.202578Z digest=sha256:6a2e06078ef501ae90b74ad837fb307c4b8de8e06b43c849d1e2468a2762b286

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=sha256:79cc279123466127ae6fb3bf656f73d6261ad11f743eb4ce0ab39823446ee685

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:42.426137Z digest=sha256:2c9f737f4b70021ed6d80ae1f8568c53a7044978d6e877d00c0c69429e54d1a1

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:42.498501Z digest=sha256:5debe61c78bd7d1592891353c5ad8d60256bf1d89a9534e6ead9adb3ab15a16b

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:42.580342Z digest=sha256:87858823ce19a32ab7e2965a2be4b0c9aca18b68f06d9bc658f7e7053621e664

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:42.656050Z digest=sha256:18a75b018e4be7e65fc739997c60b17afbb7633d951d12f5094b2e4bb3e0efc7

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:42.745695Z digest=sha256:fbb7f7cf79f60be50447e0eacd392394ea5e241b5de5ef9dd450f3ca60e3601f

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:42.828176Z digest=sha256:4943bec0c4dc04ad73155854f27a627c108499464d602f1cb49b8a16d20926c0

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:42.913181Z digest=sha256:d5f99238843ce500321eb45b91090c8ad7548ca0e2bdd1124b73779768aad992

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:43.008111Z digest=sha256:a14378b0a8a9a5b8a73003c5fe0c1a0d9ff06d6e8a3e547601ab9552c29f86d1

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:43.320114Z digest=sha256:bab14c2a30e158594ce0997135fdeded886d938a2b4e84ec5f0bd60fdbdb70d6

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:43.483636Z digest=sha256:e556ac8b9be97e0b9339655b6ec50c45a357038e13c05e1e23d39c33aa6cdadd

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:43.635422Z digest=sha256:bdb2199087a26f5d580aaf46747ab3704b6fd17f30f0cbbd5852ebe6d0d6bd0b

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:43.782344Z digest=sha256:d012367a3ed67e3ec7f815ef714f6507fcbf4f7585040c497e9e904fc6928601

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:40:43.911455Z digest=sha256:04066a129d1dab03c9bcd5c7fa01b6d395c287cec9d8001b1cecbde80d3cd58d

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