Paper Citation Record · LEDGER

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework

As of 18 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2507.05621.

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

pith.paper-citation-record.v1
2507.05621 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:27:08.461822Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

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

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

verified exact0
verified fuzzy25
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 57d1d765-bdc5-4412-9b6c-6a0cf2e93902 · outbound

This paper cites Multimodal datasets: misogyny, pornography, and malignant stereotypes.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Multimodal datasets: misogyny, pornography, and malignant stereotypes

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:09.101175Z

Source-reported events for the cited work

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

Observation e376bb5e-e641-444e-9775-ecf3aa47b5ea · outbound

This paper cites Ap-adapter: Improving generalization of automatic prompts on unseen text-to-image diffusion models.Advances in Neural Information Processing Systems, 37:98320–98346, 2024.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Ap-adapter: Improving generalization of automatic prompts on unseen text-to-image diffusion models.Advances in Neural Information Processing Systems, 37:98320–98346, 2024

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:09.084952Z

Source-reported events for the cited work

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

Observation 8db37590-c350-4499-ab50-de1b5dae96cb · outbound

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

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework High-resolution image synthesis with latent diffusion models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:08.289993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d06f7407-2ce3-4b8b-9492-33d4e104819f · outbound

This paper cites Zero-shot text-to-image generation.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Zero-shot text-to-image generation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:08.294960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8f38470-e525-43a2-8416-77fa60029a4f · outbound

This paper cites DoRA: Weight-decomposed low-rank adaptation.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework DoRA: Weight-decomposed low-rank adaptation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:09.043411Z

Source-reported events for the cited work

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

Observation 683d6fb9-7811-45cb-b70f-fda13e3a153b · outbound

This paper cites AdaLoRA: Adaptive budget allocation for parameter-efficient fine-tuning.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework AdaLoRA: Adaptive budget allocation for parameter-efficient fine-tuning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:09.027805Z

Source-reported events for the cited work

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

Observation 1179471d-f53c-44c9-8c2a-43fd70993ef5 · outbound

This paper cites QLoRA: Efficient finetuning of quantized LLMs.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework QLoRA: Efficient finetuning of quantized LLMs

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:08.311360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da81887a-d22e-4a2b-83c8-db00b5236544 · outbound

This paper cites Design guidelines for prompt engineering text-to-image generative models.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Design guidelines for prompt engineering text-to-image generative models

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:09.002959Z

Source-reported events for the cited work

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

Observation dae836e5-5ebe-4c16-9f21-8adc4d25348f · outbound

This paper cites Prompt engineering for text-to-image generative models.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Prompt engineering for text-to-image generative models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.988394Z

Source-reported events for the cited work

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

Observation 76b078ec-2d90-405c-93bb-52c2fb298cec · outbound

This paper cites DiffusionDB: A large-scale prompt gallery dataset for text-to-image generative models.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework DiffusionDB: A large-scale prompt gallery dataset for text-to-image generative models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.971872Z

Source-reported events for the cited work

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

Observation 983c5c51-3ecb-46ff-bdd7-e9f69f82025b · outbound

This paper cites Easily accessible text-to-image generation amplifies demographic stereotypes at large scale.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Easily accessible text-to-image generation amplifies demographic stereotypes at large scale

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.954009Z

Source-reported events for the cited work

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

Observation 742c095a-52a8-4eb6-98cc-29424bc253a4 · outbound

This paper cites Prompt-free diffusion: Taking" text" out of text-to-image diffusion models.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Prompt-free diffusion: Taking" text" out of text-to-image diffusion models

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.937861Z

Source-reported events for the cited work

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

Observation 97900c40-93f2-4053-b4b1-9e4f598bf604 · outbound

This paper cites Best prompts for text-to-image models and how to find them.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Best prompts for text-to-image models and how to find them

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.919532Z

Source-reported events for the cited work

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

Observation fd03b35f-6d2e-4cb9-9140-d7ed642aad46 · outbound

This paper cites LoRA: Low-rank adaptation of large language models.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework LoRA: Low-rank adaptation of large language models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.903254Z

Source-reported events for the cited work

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

Observation c93e9468-c505-4dd5-b94c-0b52c71ec6b6 · outbound

This paper cites VeRA: Vector-based random matrix adaptation.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework VeRA: Vector-based random matrix adaptation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.887143Z

Source-reported events for the cited work

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

Observation fd5dbea4-0c11-431c-920d-c21a14efedee · outbound

This paper cites Optimizing prompts for text-to-image generation.Advances in Neural Information Processing Systems, 36:66923–66939, 2023.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Optimizing prompts for text-to-image generation.Advances in Neural Information Processing Systems, 36:66923–66939, 2023

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:08.357791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef8d0e07-4314-47b5-8b21-8f1aa3c241a4 · outbound

This paper cites Datadream: Few-shot guided dataset generation.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Datadream: Few-shot guided dataset generation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.849331Z

Source-reported events for the cited work

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

Observation 8d9fbbbf-3fd9-48ae-b327-98f22d159321 · outbound

This paper cites BeautifulPrompt: Towards automatic prompt engineering for text-to-image synthesis.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework BeautifulPrompt: Towards automatic prompt engineering for text-to-image synthesis

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.831824Z

Source-reported events for the cited work

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

Observation ee79e655-2430-4798-8a11-15769b470571 · outbound

This paper cites Neuroprompts: An adaptive framework to optimize prompts for text-to-image generation.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Neuroprompts: An adaptive framework to optimize prompts for text-to-image generation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:08.374822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6464004-b459-4c84-b20e-8a98d1e4a940 · outbound

This paper cites PromptCharm: Text-to-image generation through multi-modal prompting and refinement.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework PromptCharm: Text-to-image generation through multi-modal prompting and refinement

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.798527Z

Source-reported events for the cited work

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

Observation dfd2a81d-80a3-4336-9303-00fa27db5df5 · outbound

This paper cites Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:08.389265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d60caeea-5b2f-43f1-a980-e424a198e28d · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:08.394104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79457adc-56cc-4dfd-a75d-5678d12afc96 · outbound

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

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Learning transferable visual models from natural language supervision

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:08.398703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b21bf8b0-9e85-4943-8051-40dfa1be9c17 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:08.402886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b250581-6d9b-48ff-92c2-d4595e2dcba3 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.2009 IEEE Conference on Computer Vision and Pattern Recognition, pages 248–255, 2009.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Imagenet: A large-scale hierarchical image database.2009 IEEE Conference on Computer Vision and Pattern Recognition, pages 248–255, 2009

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.714919Z

Source-reported events for the cited work

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

Observation da414137-0f42-4401-b41d-384c905f9d28 · outbound

This paper cites Sun database: Large-scale scene recognition from abbey to zoo.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Sun database: Large-scale scene recognition from abbey to zoo

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.696512Z

Source-reported events for the cited work

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

Observation c80cc811-2274-404c-848d-961ad873990b · outbound

This paper cites Food-101–mining discriminative components with random forests.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Food-101–mining discriminative components with random forests

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.679110Z

Source-reported events for the cited work

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

Observation 93c92ae9-18a3-451e-9e71-89b219ea34a2 · outbound

This paper cites Geetharamani and J.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Geetharamani and J

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.662527Z

Source-reported events for the cited work

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

Observation 9928950a-2134-4393-be35-37475479b310 · outbound

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

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework High-resolution image synthesis with latent diffusion models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.644672Z

Source-reported events for the cited work

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

Observation dcb39d6d-c560-4b9a-bac1-3c51b5a49953 · outbound

This paper cites Zero-shot text-to-image generation.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Zero-shot text-to-image generation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:08.435213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4cff03f-8614-46b3-8980-de4ba2b08f8b · outbound

This paper cites Parameter-efficient transfer learning for NLP.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Parameter-efficient transfer learning for NLP

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.611717Z

Source-reported events for the cited work

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

Observation ee60c1d2-6a7b-4e36-84ab-dbfbdee810d0 · outbound

This paper cites Towards a unified view of parameter- efficient transfer learning.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Towards a unified view of parameter- efficient transfer learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.592672Z

Source-reported events for the cited work

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

Observation 7b57de47-c526-4783-8121-5b5408545234 · outbound

This paper cites Prefix-tuning: Optimizing continuous prompts for generation.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework Prefix-tuning: Optimizing continuous prompts for generation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.566715Z

Source-reported events for the cited work

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

Observation 84be72e8-80e3-47a6-9e63-e8ea67b843a3 · outbound

This paper cites The power of scale for parameter-efficient prompt tuning.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework The power of scale for parameter-efficient prompt tuning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.546157Z

Source-reported events for the cited work

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

Observation f10df397-a263-47a3-8797-bdd61fad09e1 · outbound

This paper cites BitFit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.

AdaptaGen: Domain-Specific Image Generation through Hierarchical Semantic Optimization Framework BitFit: Simple parameter-efficient fine-tuning for transformer-based masked language-models

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:27:08.526465Z

Source-reported events for the cited work

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

Pith citing papers

No inbound Pith citation observations are available.