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Paper Citation Record · LEDGER

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

As of 7 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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:37.801554Z digest=sha256:96e55fa97ae3fbf8e87c9c11e2f06be45405bdd61cfe13f1dfcfadfa11979f0b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:37.869669Z digest=sha256:0f7a231195f34a7a2e30d532cb1065abbce25ff084a992d406b1886c05e2e597

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:38.006453Z digest=sha256:714d3944bb454a5642eb347b2207b7e4bf4e0f7d0cc1eafdd1314c3a59165838

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:38.092173Z digest=sha256:8290a2ad36c0e25d00aaf170cb27186b18484d24d97cc906616387019994715b

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=sha256:4cbb977fad83c1b520df8e1ac06f89e092ad8948625a28258d59a511a1747fbb

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=sha256:9ef8ee8db74c6e5916db98bdb96ea907df23b0cfae7957e8ef724af5679b3610

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:38.311344Z digest=sha256:18c43ccc3e3a94e7a36c93265401642a6c41c3f23623312d758a87c9fe9fcb45

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:38.414953Z digest=sha256:63e4974741224ed5f009746f986014c86ac37756265249dbc6fb47d3f98b8b56

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:38.533038Z digest=sha256:cf907216138acf09c0c44c2f96ace73a96b3f05af5521aa7676c5c2c21158e64

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:38.617567Z digest=sha256:fb1224a09ad55e8aade6a9efae124f5acac9db33698aca1df88cb83f1ce5fcc8

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:38.686095Z digest=sha256:f4de74cdd170037ffc7d561a7c7d4ac7257c21db7648a20c73876a3f14b4d0e5

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:38.767766Z digest=sha256:ff4a9c93accaa4eec891b2f380e873062ae861ec3d7f30d390f50b8292bd1c7b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:38.852740Z digest=sha256:2d36786a9f038d03251fa2720f7607fbf97da7c443d8f39b97dadf240adea495

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:38.921080Z digest=sha256:739f476b2c0f7f720248bc1af4b84410c46f21b2d8b06da807ab592e6db35a2f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:39.040929Z digest=sha256:7f4cb0f1c0c16eb882e7a23a2cb91464d642faf87b57d301b9dbe8c065cf9d86

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:39.117436Z digest=sha256:f41d87751bde298bf7f447a22215329befe7e1c1c52826f0c60c04295d0c5b12

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:39.222820Z digest=sha256:e3d15436635c5a3c84c9b5ff642250ebfdfa694f21b9992dd0d6bcef5fb57fad

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:39.348295Z digest=sha256:05b23db6c7eb6759df20ccdbfef115e8df90868750303a5b58d0a6dd3378545c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:39.469217Z digest=sha256:960b389c69c790b942525b47f558527bb2b51b5b5412088eb00e68045eb04159

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:39.656385Z digest=sha256:7e5995c584e8f7f304f4f406f1f04b17289b826b74b154e4972197ff085d4974

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:39.797724Z digest=sha256:e0482b5a9668f5d521fdc2f8509ae80705a01e5f13c831bf0f2dde0ab1d07ea3

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:39.928683Z digest=sha256:1e72fbc7cb2a97137067ca3164abc8ba4b99884c37da7e6160ac33952a685810

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:40.097222Z digest=sha256:e1850620196810caf88df7de05b614c2551611d6608729c7b57f598d2a7c52a6

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:40.218722Z digest=sha256:aa19635d7f06f542cfaaa7410cc0c059beb061dd7b2d0ef93f0b105e69a38cee

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:40.350719Z digest=sha256:ebbe891ec011822c9c0dcecb383b908f872c9fba49bf50174267377725c45b6b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:40.490585Z digest=sha256:b2bc9a663aea86112c90ae965813a0d910ccd58c9fca54172ea2e2e2353dc5cd

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:40.596658Z digest=sha256:dd29bb660fb62e205379cc98a473fef45b15e869a5781082b5c98bc2eb63bb87

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:e037d9ad6eb63815047a0fde4ecde80a8e3ec650428419c241af9ea3b31f1dcc

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:40.812200Z digest=sha256:40d420ac320ddd4aba4c530482ab648516b05b99656e9de812b41bcb9f7d35ec

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:40.891312Z digest=sha256:dd18672debbfb03e10d0b0d10617812b63b53ed871001be901559e57de33828b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:40.984218Z digest=sha256:be51b6e18311ad83a6095d14a5ea23b45add8ec5a0eee08d28e8a8bcc21e76dc

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:41.081311Z digest=sha256:24cf35bd8e8542a308f69e5f94ccec6d47b83e772911506765c4a5784163fd86

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=sha256:189d579363a9cd97994c7f9b366798bcc1c2fc1a9e6e664481d4368106d6aa2c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:41.213668Z digest=sha256:ea1253888ac13d6570a6417c3c29d49ef81e345a00a2d82082510f45f654b66f

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:a64ea49a37277ddb04e9bf432d32049b8c0ae52205be1fd26004987dd28f1dae

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:41.312373Z digest=sha256:cad3ce506b4499e8a3e41373b4e58d5da4cf3b7c78f4f3386c517a54efcff5d8

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:41.418479Z digest=sha256:942ff42fa73ed9de2b8aae926c338866928935793d087c170f9351468fcd2ecb

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:41.513574Z digest=sha256:7c3b22b41f9384ae98be8921aad06afac90b8abd294e444782c8198371184c88

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:41.602652Z digest=sha256:887fec26e271f5e5b902be170f9f2cc3433738d30a8b5ae4e77f8d2ef84d89f2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:41.659963Z digest=sha256:353422e2a73aafe54c2e637fd50150d747daafc9d27421440e9c4b1a4922617d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:41.749052Z digest=sha256:c4f9e48b378978a44086adfdf06520240080d486799d6d45ff1228ce4de29470

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:41.802344Z digest=sha256:a5fec783b5ac3e0ab8f0330e802ab70468936a817df93d53e38fca28311ea1f9

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=sha256:71d54bbdfefa04393e97ff5c562d37781f43c1ad8b7aa34efefdf5e3df8ae3ef

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:41.942719Z digest=sha256:393b2eb48a14779fbbbda1e089bf93abb858b592290bfd7c570f1a02c5ff5cff

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=sha256:4b214d709656b1c9dc6e4ed12c53740be7d792e185963a8f738351903bb6a316

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:42.116848Z digest=sha256:bec1af47d9a9489eee77356e6eac3e3d307de79f5e40d43f8e73ed9f2bb658eb

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:42.202578Z digest=sha256:e4e7fed67f6a1fc6107367f80386facb930cd7d7400bd60e260d034f5f05654d

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:c2f6ce1695d83f257d55c6f5ad1c7bdda10ae5b55d0783cd76535abbe10f017a

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:f302ea668697b49004dfccebe5ac2b79f658d617c3c9e2a1c5a676fa0a848f5a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:42.426137Z digest=sha256:8073b7df170e878a5c92d359537d6e045e50b9fb8f8b98b319dc6830ffe045e0

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:42.498501Z digest=sha256:a8c670f3d1aae688a511d9c23b106fcdec3c12415ad50a39dacd62371ebca2dc

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:42.580342Z digest=sha256:a69a10ab4b814066aa4df05396445869d2b3416634fc6878c56255a398bd3b5c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:42.656050Z digest=sha256:9c9e742f643c11896ad0c9584b306e4589c2535edb1cf6f9cc790b4571d63728

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:42.745695Z digest=sha256:8f961d04fc12b2786c41e9e391957c50a05d4c68c290ace55d69dea4906f3455

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:42.828176Z digest=sha256:2190929ac546444d8c621e5c3f05d033138324046275d0d85b723b85e869951c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:42.913181Z digest=sha256:da5713d6f6b10f54ee41fc6e91f00ba42634e757b7aa4c1a67325fe11f3111ac

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:43.008111Z digest=sha256:f507f9641426050380dceec13cdbfd0487c5cbd9600e3087708a6c6819d42403

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:d6f45d527b76c614594b9e2ca3f98e9b5d72df0d68c19180c74c840b9a3e21c9

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=sha256:6664dd38f625be6b54471e3f7aa2a363d0f7ff8c02ab8995408ea5f0c4311066

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:43.320114Z digest=sha256:82d738057c74a9d3071ad04f922c10216f3393826acbfa5bd9acc254345d63de

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:43.483636Z digest=sha256:cfcdba24500e2d6611d41fbb3c306df0f1938bb4515d0ea3c88c0bf042a2a3f2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:43.635422Z digest=sha256:c277b8470c95ded24f8691c4ee0b44f605ac4b5da0a799fdd60ca73c2542a09e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:43.782344Z digest=sha256:38f924fc84435ef3bdac53d752be2564a9e25870dc1aecbf1890505982a791b3

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:40:43.911455Z digest=sha256:2e85064688d00a1d11929cbc29eeee3353d7179248d934c60f33ad579ca1482b

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:f71a35092be85a7b9fd7446bff69f811b2790cca1a558fa5e19a5e0af6051b03