Paper Citation Record · LEDGER

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts?

As of 19 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 1 inbound Pith citation observation for arXiv:2505.16915.

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

pith.paper-citation-record.v1
2505.16915 v3

Coverage vector

measured 72 of 72 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:55:32.127569Z

measured 73 of 73 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T04:22:19.645747Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T12:01:03.744330Z

Reference resolution

72 of 72 outbound references displayed

verified exact1
verified fuzzy25
unresolved45
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b8deb0b7-dfd9-464d-9da3-a7b1cbd601d2 · outbound

This paper cites write newline.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:25.236529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4498b290-d28e-4c13-8b66-d28935da35c7 · outbound

This paper cites GPT-4 Technical Report.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? GPT-4 Technical Report

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:25.342327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0842ee5-ed83-4c63-b60e-84833b0e07c8 · outbound

This paper cites DeepFloyd IF : a novel state-of-the-art open-source text-to-image model with a high degree of photorealism and language understanding.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? DeepFloyd IF : a novel state-of-the-art open-source text-to-image model with a high degree of photorealism and language understanding

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:38.220244Z

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 a4557e7d-0c77-40f5-bf90-7a8f4f35506c · outbound

This paper cites Hrs-bench: Holistic, reliable and scalable benchmark for text-to-image models.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Hrs-bench: Holistic, reliable and scalable benchmark for text-to-image models

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:38.055478Z

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 651e8506-075d-4375-88e3-58bc10c3913d · outbound

This paper cites Improving image generation with better captions.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Improving image generation with better captions

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:25.597506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2fa7e38-cfa9-4415-b6cf-853663cb796a · outbound

This paper cites A survey of ai-generated content (aigc).

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? A survey of ai-generated content (aigc)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:37.868801Z

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 a83e2d2d-7547-4196-af5c-909f41291762 · outbound

This paper cites Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:25.758652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4519c43-82da-4928-9b58-f0d06a162b60 · outbound

This paper cites Data-juicer 2.0: Cloud-scale adaptive data processing for and with foundation models.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Data-juicer 2.0: Cloud-scale adaptive data processing for and with foundation models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:37.690180Z

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 fd7d9d22-bb62-4c69-9316-d6aa7ee9793e · outbound

This paper cites Data-juicer sandbox: A feedback-driven suite for multimodal data-model co-development.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Data-juicer sandbox: A feedback-driven suite for multimodal data-model co-development

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:37.517849Z

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 13a8bef6-d4c6-4bb7-9e4f-450488504528 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:25.989364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70c08de5-668e-4f95-856b-e23380c9e598 · outbound

This paper cites Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:26.052578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85f93c2a-e2e8-4692-8afb-1728d3548073 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:26.176849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94de4e54-9fd9-4681-82ff-b7f38d7b989b · outbound

This paper cites Diffsynth: Latent in-iteration deflickering for realistic video synthesis.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Diffsynth: Latent in-iteration deflickering for realistic video synthesis

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:37.291485Z

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 fc602498-e7b0-4e83-a5d0-f65b21eebc1c · outbound

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

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Scaling rectified flow transformers for high-resolution image synthesis

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:26.243518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18f1ba49-3f16-4ae5-af57-72a4be1e6706 · outbound

This paper cites nsfw-image-detection.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? nsfw-image-detection

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:37.134203Z

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 36d99a75-cc11-4bfa-9750-bf4d522af339 · outbound

This paper cites LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:26.445655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcc1c580-9363-4814-a25a-deff32e7e82f · outbound

This paper cites Generative adversarial nets.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Generative adversarial nets

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:26.527836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9663f881-1aad-40f0-98b6-da6612525720 · outbound

This paper cites Gemini 2.0 flash image generation.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Gemini 2.0 flash image generation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:36.963214Z

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 5ddb6e81-0817-4e4c-b02d-47951ebf0898 · outbound

This paper cites CLIPScore: A Reference-free Evaluation Metric for Image Captioning.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:26.882061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e33d1df4-9838-4c80-8e85-90391aebdd27 · outbound

This paper cites Denoising diffusion probabilistic models.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Denoising diffusion probabilistic models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:27.012502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d601b964-d16a-4078-8aef-6441b89316ad · outbound

This paper cites ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:27.234325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 376db6c2-17d9-4866-97e1-94d7b530cce0 · outbound

This paper cites Tifa: Accurate and interpretable text-to-image faithfulness evaluation with question answering.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Tifa: Accurate and interpretable text-to-image faithfulness evaluation with question answering

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:36.778465Z

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 5745046d-35de-419c-8175-f543fb3fc1a3 · outbound

This paper cites T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:27.465217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 340e6967-515d-4845-a9c9-69ae3e845280 · outbound

This paper cites Visual storytelling.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Visual storytelling

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:36.569719Z

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 fe3c505b-b2cd-46c9-9c04-aa50bc229374 · outbound

This paper cites From Training-Free to Adaptive: Empirical Insights into MLLMs' Understanding of Detection Information.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? From Training-Free to Adaptive: Empirical Insights into MLLMs' Understanding of Detection Information

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:27.700565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3377342-8b73-4474-bc1e-cf5316b19167 · outbound

This paper cites Img-diff: Contrastive data synthesis for multimodal large language models.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Img-diff: Contrastive data synthesis for multimodal large language models

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:36.402490Z

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 026e90cb-ef80-4780-a940-84c965a49dff · outbound

This paper cites an unresolved cited work.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:55:36.167255Z

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 ace5e3e7-a0bc-432e-99c1-7798f52fe182 · outbound

This paper cites Natural language understanding and inference with mllm in visual question answering: A survey.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Natural language understanding and inference with mllm in visual question answering: A survey

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:35.935257Z

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 a5646d32-438b-4632-8c88-535bea381d69 · outbound

This paper cites an unresolved cited work.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:27.977541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e98ab4f8-0e88-4dbe-a523-fdcadaff2faf · outbound

This paper cites Genai-bench: A holistic benchmark for compositional text-to-visual generation.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Genai-bench: A holistic benchmark for compositional text-to-visual generation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:35.735158Z

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 d8d60920-01de-4428-9bb3-3fe32c6d7d0c · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? LLaVA-OneVision: Easy Visual Task Transfer

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:28.147348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4722c6c-9f1a-44ad-9e7b-9df5dcc26f57 · outbound

This paper cites mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:28.217225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6258123-ccaa-4d7e-a9ff-7ac5b1aaea0b · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:35.562786Z

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 c07fe08f-5bdd-4f1d-af29-d3907d40fbec · outbound

This paper cites Rich human feedback for text-to-image generation.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Rich human feedback for text-to-image generation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:35.321901Z

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 54a39d1b-4b6e-4480-892a-abc9840a58df · outbound

This paper cites Microsoft coco: Common objects in context.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Microsoft coco: Common objects in context

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:28.521024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31d7a765-4198-4192-84a3-d8865643cad4 · outbound

This paper cites Flow Matching for Generative Modeling.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Flow Matching for Generative Modeling

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:28.590688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a42b0a63-8dd3-4338-9b2b-71c18bb2a129 · outbound

This paper cites Improving Long-Text Alignment for Text-to-Image Diffusion Models.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Improving Long-Text Alignment for Text-to-Image Diffusion Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:28.663859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec8865cc-1e92-4e2e-b08d-73f4ef025517 · outbound

This paper cites Llm4gen: Leveraging semantic representation of llms for text-to-image generation.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Llm4gen: Leveraging semantic representation of llms for text-to-image generation

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:35.084854Z

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 a3c041d6-74d3-4ca9-b9be-cd9eaf8daabc · outbound

This paper cites Browsing like human: A multimodal web agent with experiential fast-and-slow thinking.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Browsing like human: A multimodal web agent with experiential fast-and-slow thinking

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:34.922193Z

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 ebea15ab-0fab-4db2-959a-4de94a0538e8 · outbound

This paper cites Automated flower classification over a large number of classes.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Automated flower classification over a large number of classes

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:28.916410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7836a0a7-e510-4929-a79a-eeac3e22b4dd · outbound

This paper cites Docci: Descriptions of connected and contrasting images.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Docci: Descriptions of connected and contrasting images

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:34.685316Z

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 799a5789-e1a5-4527-9d4b-59f31b1c951c · outbound

This paper cites Gpt image-1.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Gpt image-1

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:34.472643Z

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 847789b4-1643-4243-a9a9-46d16b3f80f6 · outbound

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

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:29.176831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdd8fa48-2e44-4616-a173-271eac2279ed · outbound

This paper cites Connecting vision and language with localized narratives.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Connecting vision and language with localized narratives

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:55:34.272214Z

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 88b6dadb-6586-4801-9d4f-6adab5c7c8d8 · outbound

This paper cites The synergy between data and multi-modal large language models: A survey from co-development perspective.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? The synergy between data and multi-modal large language models: A survey from co-development perspective

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:29.375398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0a9b799-f4f9-4374-9ce0-686c4e6f1026 · outbound

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

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Learning transferable visual models from natural language supervision

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:29.453485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e87bdd9-aa69-4edd-b4ac-a88a34bff960 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:29.545971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a18da4a-a3bd-4b14-8136-bef38c15809d · outbound

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

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Zero-shot text-to-image generation

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:29.616410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f33bc5ee-1b2f-4aa3-9137-ff085641cb8d · outbound

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

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:29.680330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 832c8e8c-ba0c-4335-9ec4-f8c2fa9bd9b6 · outbound

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

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? High-resolution image synthesis with latent diffusion models

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:29.766420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c90e7de4-d2c4-40c4-a356-8e9eee85db9d · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Photorealistic text-to-image diffusion models with deep language understanding

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:29.865585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24284bcc-236a-49c8-ba13-ad16aab445ac · outbound

This paper cites Qwen2.5: A party of foundation models, September 2024.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Qwen2.5: A party of foundation models, September 2024

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:29.955998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20e604a6-2e47-42a5-b3d4-d55e3474f228 · outbound

This paper cites Qwen2.5-vl, January 2025.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Qwen2.5-vl, January 2025

Reference 54

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Source-reported events for the cited work

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This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 55

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This paper cites The caltech-ucsd birds-200-2011 dataset.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? The caltech-ucsd birds-200-2011 dataset

Reference 56

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This paper cites Yoloe: Real-time seeing anything.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Yoloe: Real-time seeing anything

Reference 57

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This paper cites Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Ratings.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Ratings

Reference 58

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This paper cites Integrating aigc with design: dependence, application, and evolution-a systematic literature review.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Integrating aigc with design: dependence, application, and evolution-a systematic literature review

Reference 59

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This paper cites Paragraph-to-Image Generation with Information-Enriched Diffusion Model.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Paragraph-to-Image Generation with Information-Enriched Diffusion Model

Reference 60

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This paper cites Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 62

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This paper cites Ai-generated content for academic visualization and communication in maker education.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Ai-generated content for academic visualization and communication in maker education

Reference 63

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

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Imagereward: Learning and evaluating human preferences for text-to-image generation

Reference 64

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This paper cites Mindgym: What matters in question synthesis for thinking-centric fine-tuning? In NeurIPS, 2025.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Mindgym: What matters in question synthesis for thinking-centric fine-tuning? In NeurIPS, 2025

Reference 65

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Observation ec8c97eb-28ee-49ab-aea7-b5128f283d87 · outbound

This paper cites From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions

Reference 66

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This paper cites Scaling Autoregressive Models for Content-Rich Text-to-Image Generation.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Reference 67

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This paper cites Learning multi-dimensional human preference for text-to-image generation.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Learning multi-dimensional human preference for text-to-image generation

Reference 68

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Observation 75def250-758c-4cb5-8ddf-c262e8bf8340 · outbound

This paper cites HumanVBench: Probing Human-Centric Video Understanding in MLLMs with Automatically Synthesized Benchmarks.

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? HumanVBench: Probing Human-Centric Video Understanding in MLLMs with Automatically Synthesized Benchmarks

Reference 69

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Source-reported events for the cited work

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Observation e0be45fa-a2ce-4835-a6c3-ca0b0df87e13 · outbound

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DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 70

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Observation 9886c18f-904d-4ce6-b7fa-422291e00bf2 · outbound

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DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 71

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DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? @esa (Ref

Reference 72

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DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Unresolved cited work

Reference 73

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Observation bcf72c9f-a956-4dad-9e6d-346bb6bc02d4 · outbound

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DetailMaster: Can Your Text-to-Image Model Handle Long Prompts? Unresolved cited work

Reference 74

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Pith citing papers

Observation 195a35c4-a2a8-4831-9f81-b7e23fe20712 · inbound

Long-Text-to-Image Generation via Compositional Prompt Decomposition cites this paper.

Long-Text-to-Image Generation via Compositional Prompt Decomposition DetailMaster: Can Your Text-to-Image Model Handle Long Prompts?

Reference 47

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