Paper Citation Record · LEDGER

Distribution-Conditional Generation: From Class Distribution to Creative Generation

As of 19 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 2 inbound Pith citation observations for arXiv:2505.03667.

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

pith.paper-citation-record.v1
2505.03667 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:51:41.274853Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T12:23:30.122689Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T19:53:42.566031Z

Reference resolution

48 of 48 outbound references displayed

verified exact3
verified fuzzy38
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e0d21cf5-056c-4130-930a-13b1b38fb9f7 · outbound

This paper cites GPT-4 Technical Report.

Distribution-Conditional Generation: From Class Distribution to Creative Generation GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T23:51:41.068249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fdc34de-c08c-48cc-9f21-e17934d5cdcc · outbound

This paper cites Prompting for discovery: Flexible sense-making for ai art-making with dreamsheets.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Prompting for discovery: Flexible sense-making for ai art-making with dreamsheets

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.992424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c05826f2-4ace-4d33-a29f-578a7a487b20 · outbound

This paper cites Flux: Diffusion models for layered image generation.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Flux: Diffusion models for layered image generation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.978033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e718ed7c-b36e-458c-a81e-cb7a673c4e73 · outbound

This paper cites Artadapter: Text-to-image style transfer using multi-level style encoder and explicit adaptation.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Artadapter: Text-to-image style transfer using multi-level style encoder and explicit adaptation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.963858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 055f471d-0b6f-44e0-9331-ca3e16df1238 · outbound

This paper cites Tailored visions: Enhancing text-to-image generation with personalized prompt rewriting.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Tailored visions: Enhancing text-to-image generation with personalized prompt rewriting

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.949721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d6a3cbca-4bcd-4bf0-b7a2-c17c54bd566b · outbound

This paper cites IP-Composer: Semantic Composition of Visual Concepts.

Distribution-Conditional Generation: From Class Distribution to Creative Generation IP-Composer: Semantic Composition of Visual Concepts

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-15T23:51:41.440955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2bed09c7-ce40-4a01-97fa-f270c5fb14ff · outbound

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

Distribution-Conditional Generation: From Class Distribution to Creative Generation Scaling rectified flow trans- formers for high-resolution image synthesis

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.934717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1866b2f9-bd7f-435e-9c8c-5b644bf2b19b · outbound

This paper cites Genes in Intelligent Agents.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Genes in Intelligent Agents

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T23:51:41.100634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22721dde-4d86-43f1-908e-9db7552f5a87 · outbound

This paper cites Redefining <creative> in dictionary: Towards an enhanced semantic understanding of creative generation.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Redefining <creative> in dictionary: Towards an enhanced semantic understanding of creative generation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.920662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b80df57e-7d7d-4b7c-be3a-806242696b76 · outbound

This paper cites An image is worth one word: Personalizing text-to-image generation using textual inversion.

Distribution-Conditional Generation: From Class Distribution to Creative Generation An image is worth one word: Personalizing text-to-image generation using textual inversion

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.906728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 005c66e7-bdef-46c9-9eb0-1d52c09d5b4d · outbound

This paper cites Enhancing creative generation on stable diffusion-based models.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Enhancing creative generation on stable diffusion-based models

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.893542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2cc65eb6-967c-43fa-91ea-363052201d3d · outbound

This paper cites Svdiff: Compact parameter space for diffusion fine-tuning.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Svdiff: Compact parameter space for diffusion fine-tuning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.880263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 54e0d812-120e-4332-9dea-1899101683f5 · outbound

This paper cites One more step: A versatile plug-and-play module for rectifying diffusion schedule flaws and enhancing low-frequency controls.

Distribution-Conditional Generation: From Class Distribution to Creative Generation One more step: A versatile plug-and-play module for rectifying diffusion schedule flaws and enhancing low-frequency controls

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.866343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 59b22f2c-143d-4077-9ec1-4a9680588ae7 · outbound

This paper cites Pick-a-pic: An open dataset of user preferences for text-to-image generation.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Pick-a-pic: An open dataset of user preferences for text-to-image generation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.852602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ba60ca84-4b65-4804-a7e5-b9619f470468 · outbound

This paper cites Multi- concept customization of text-to-image diffusion.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Multi- concept customization of text-to-image diffusion

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.838908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5cbe45fa-5d10-4b31-9441-6836f82e2616 · outbound

This paper cites A path towards autonomous machine intelligence.

Distribution-Conditional Generation: From Class Distribution to Creative Generation A path towards autonomous machine intelligence

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.825165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ad2268a7-c297-4edc-9c0d-13614f3792e2 · outbound

This paper cites Tp2o: Creative text pair-to-object generation using balance swap-sampling.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Tp2o: Creative text pair-to-object generation using balance swap-sampling

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.811686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 729ae71f-bc5e-4254-ba8c-e78d6ed0be38 · outbound

This paper cites MagicMix: Semantic Mixing with Diffusion Models.

Distribution-Conditional Generation: From Class Distribution to Creative Generation MagicMix: Semantic Mixing with Diffusion Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T23:51:41.142748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd490341-fb14-46c8-89b6-7a2f867e09ed · outbound

This paper cites Evaluating text-to-visual generation with image-to-text generation.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Evaluating text-to-visual generation with image-to-text generation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.797500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0e9b4d5b-eff7-464f-b608-3fc8eaa6d475 · outbound

This paper cites Procreate, don’t reproduce! propulsive energy diffusion for creative generation.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Procreate, don’t reproduce! propulsive energy diffusion for creative generation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.781926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 63443cfd-3ed4-4e6f-a913-b33477e7b498 · outbound

This paper cites Towards machine learning as an enabler of computational creativity.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Towards machine learning as an enabler of computational creativity

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.766854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 63d4973b-e45d-4f9e-bcd4-f2554ed4439b · outbound

This paper cites Art, creativity, and the potential of artificial intelligence.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Art, creativity, and the potential of artificial intelligence

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.751723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4abf15ea-956d-4fe6-80a0-f90e44c7b342 · outbound

This paper cites Midjourney.com.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Midjourney.com

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.736953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2dce0f8d-8fa0-48f4-94ff-a0913f93bc82 · outbound

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

Distribution-Conditional Generation: From Class Distribution to Creative Generation T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.723463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a59f1c13-b4f9-47c6-af50-03547e157d95 · outbound

This paper cites Chirpy3D: Part-Aware Multi-View Diffusion for Creative Fine-Grained Object Generation.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Chirpy3D: Part-Aware Multi-View Diffusion for Creative Fine-Grained Object Generation

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-15T23:51:41.393570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 25701549-5072-4935-88fa-daf4461f292f · outbound

This paper cites Partcraft: Crafting creative objects by parts.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Partcraft: Crafting creative objects by parts

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.709133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9363868f-597d-4fbe-8e61-9be05af046aa · outbound

This paper cites Gpt-4: Openai language model.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Gpt-4: Openai language model

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.695541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1ac6b422-33f0-430b-bc44-2e4dbbe4b50b · outbound

This paper cites Prompting ai art: An investiga- tion into the creative skill of prompt engineering.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Prompting ai art: An investiga- tion into the creative skill of prompt engineering

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.681652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 84b1b782-f3aa-4ea4-884d-0be504269d56 · outbound

This paper cites Portraitbooth: A versatile portrait model for fast identity-preserved personalization.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Portraitbooth: A versatile portrait model for fast identity-preserved personalization

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.667968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 37e12223-5c36-49dc-be7e-c7d3fc21a92b · outbound

This paper cites Learning transferable visual models from natural language supervision.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Learning transferable visual models from natural language supervision

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.654151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7c392bb2-0725-4233-ba9a-031db24e6d70 · outbound

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

Distribution-Conditional Generation: From Class Distribution to Creative Generation Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T23:51:41.201804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64bb7cb8-e117-4e5d-bfe1-ee4006dd7f42 · outbound

This paper cites Kandinsky: An improved text-to-image synthesis with image prior and latent diffusion.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Kandinsky: An improved text-to-image synthesis with image prior and latent diffusion

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.640526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e69bbced-4484-4ef8-8dd8-0aab8ba95c36 · outbound

This paper cites Conceptlab: Creative concept generation using vlm-guided diffusion prior constraints.ACM Transactions on Graphics, 43(3):1–14, 2024.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Conceptlab: Creative concept generation using vlm-guided diffusion prior constraints.ACM Transactions on Graphics, 43(3):1–14, 2024

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.626623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5de82470-da64-4edc-a575-47d3eab7b66f · outbound

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

Distribution-Conditional Generation: From Class Distribution to Creative Generation Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.612973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b8f4a088-9da6-437a-b34d-62c14a48e23e · outbound

This paper cites Hyperdreambooth: Hypernetworks for fast personaliza- tion of text-to-image models.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Hyperdreambooth: Hypernetworks for fast personaliza- tion of text-to-image models

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.599568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 024161af-d3c3-4bc9-8048-f8b7795984e1 · outbound

This paper cites Stable diffusion 3.5.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Stable diffusion 3.5

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.585335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b0cdaad4-f70f-495c-b5f1-0536ac69c929 · outbound

This paper cites Multimodal large language models make text-to-image generative models align better.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Multimodal large language models make text-to-image generative models align better

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.571199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9d5c4187-380c-45ca-9cd7-d2117b9a4569 · outbound

This paper cites Novel Object Synthesis via Adaptive Text-Image Harmony.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Novel Object Synthesis via Adaptive Text-Image Harmony

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-15T23:51:41.360154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation aec47730-e747-4c73-844d-cad9b97e3e56 · outbound

This paper cites Imagereward: Learning and evaluating human preferences for text-to-image generation.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Imagereward: Learning and evaluating human preferences for text-to-image generation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.556482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8b4f3ecc-d3ff-424a-ad20-9d590df43cc0 · outbound

This paper cites IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models.

Distribution-Conditional Generation: From Class Distribution to Creative Generation IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T23:51:41.239026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c588d2b-ef5d-4296-9384-6ae1817fb8b2 · outbound

This paper cites Few-shot learner parameterization by diffusion time-steps.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Few-shot learner parameterization by diffusion time-steps

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.541366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 54f5d36e-64b2-4985-a554-68d9cef58abe · outbound

This paper cites Diffmorpher: Unleashing the capability of diffusion models for image morphing.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Diffmorpher: Unleashing the capability of diffusion models for image morphing

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.526406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 38e621ad-d5cc-44e9-a38b-3faf97137ca1 · outbound

This paper cites Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T23:51:41.252141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b554452-5eaf-4420-b348-5ac66849495c · outbound

This paper cites Multi-LoRA Composition for Image Generation.

Distribution-Conditional Generation: From Class Distribution to Creative Generation Multi-LoRA Composition for Image Generation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T23:51:41.256703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4e9fe79-6c4f-462a-a5fe-0d474dff3e6c · outbound

This paper cites A high score signifies that the elements are intricately merged, creating a new, unified entity.

Distribution-Conditional Generation: From Class Distribution to Creative Generation A high score signifies that the elements are intricately merged, creating a new, unified entity

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.512571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f47cc152-ce8b-4117-8e70-b5b67d12344f · outbound

This paper cites The image should refrain from including irrelevant elements that detract from the primary concepts.

Distribution-Conditional Generation: From Class Distribution to Creative Generation The image should refrain from including irrelevant elements that detract from the primary concepts

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.498665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7d549199-6933-431d-9c7b-4955b0d8f0ff · outbound

This paper cites The depicted concept should not mimic existing animals, plants, or widely recognized mythical creatures unless specifically mentioned in the prompt.

Distribution-Conditional Generation: From Class Distribution to Creative Generation The depicted concept should not mimic existing animals, plants, or widely recognized mythical creatures unless specifically mentioned in the prompt

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.483952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 81f47eef-529a-4b24-b96b-7b27aed84ce7 · outbound

This paper cites A high score is awarded when the image is not only conceptually robust but also visually engaging.

Distribution-Conditional Generation: From Class Distribution to Creative Generation A high score is awarded when the image is not only conceptually robust but also visually engaging

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:51:41.470031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 73f6d013-da17-44b3-b606-ebca06e4f2d6 · inbound

Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training cites this paper.

Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training Distribution-Conditional Generation: From Class Distribution to Creative Generation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T12:23:30.122689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb189708-b6fc-47b9-b4dd-e0d4be2cc420 · inbound

Seeking the Unfamiliar but Memorable: Conceptual Creativity as Meta-Learning cites this paper.

Seeking the Unfamiliar but Memorable: Conceptual Creativity as Meta-Learning Distribution-Conditional Generation: From Class Distribution to Creative Generation

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:53:42.570449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.