Paper Citation Record · LEDGER

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation

As of 10 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:2505.18730.

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

pith.paper-citation-record.v1
2505.18730 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:29:21.502877Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:15:37.003251Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T00:15:41.320900Z

Reference resolution

53 of 53 outbound references displayed

verified exact3
verified fuzzy15
unresolved35
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bb155788-5860-4057-8397-0021a4ce904e · outbound

This paper cites Tallyqa: Answering complex counting questions.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Tallyqa: Answering complex counting questions

Reference 1

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Source-reported events for the cited work

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Observation b9288481-74b3-4e63-8eb6-e7786d218de3 · outbound

This paper cites Improving image generation with better captions.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Improving image generation with better captions

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:29:27.077673Z

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Observation b22070d4-e572-4756-8565-068c657e214f · outbound

This paper cites Measuring Progress in Fine-grained Vision-and-Language Understanding.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Measuring Progress in Fine-grained Vision-and-Language Understanding

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:29:22.567556Z

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Observation 26f778c1-79de-4b56-be96-4f45fd88478d · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation

Reference 4

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Observation 983e1a34-ec16-4d73-985d-19c899a95292 · outbound

This paper cites Diffusion bridges vector quantized variational autoencoders.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Diffusion bridges vector quantized variational autoencoders

Reference 5

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Observation 5ee96bd6-5812-4111-9840-580c0171524a · outbound

This paper cites Cogview: Mastering text-to-image generation via transformers.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Cogview: Mastering text-to-image generation via transformers

Reference 6

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Observation dedadfc0-9772-4ce7-a207-fa949c6364cb · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Scaling rectified flow transformers for high-resolution image synthesis

Reference 7

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Observation cc46d3a9-9e75-4f0f-83e2-6b198eacd0d1 · outbound

This paper cites Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 8

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Observation c9468441-2afa-4be0-b5c9-cf182aa22214 · outbound

This paper cites Benchmarking Spatial Relationships in Text-to-Image Generation.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Benchmarking Spatial Relationships in Text-to-Image Generation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:14.923026Z

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Observation 59ccdda0-f430-4c38-9009-11a1a97e28b7 · outbound

This paper cites Generative adversarial networks.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Generative adversarial networks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:29:26.796147Z

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Observation 147352c5-6109-4beb-b5ee-c404ccb4391a · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 11

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Observation 43fa08c3-38d4-4b2b-9a3c-32c0d08ae7e0 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in neural information processing systems, 30, 2017.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in neural information processing systems, 30, 2017

Reference 12

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Observation 09441fd1-98fd-44c3-bd7b-73ffe3d9233b · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Tifa: Accurate and interpretable text-to-image faithfulness evaluation with question answering

Reference 13

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Observation 931fe707-d246-42bf-9148-193bf9ab403e · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation

Reference 14

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Observation 44eaefcc-fe82-4fde-9909-4827c573cea9 · outbound

This paper cites Evaluating numerical reasoning in text-to-image models.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Evaluating numerical reasoning in text-to-image models

Reference 15

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Observation 1988dbe4-d4fd-455a-bd7e-c2f5b4bcc060 · outbound

This paper cites Diffusionclip: Text-guided diffusion models for robust image manipulation.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Diffusionclip: Text-guided diffusion models for robust image manipulation

Reference 16

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Observation f8548f64-4ed7-47d4-8d13-c88d1a28bc68 · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Pick-a- pic: An open dataset of user preferences for text-to-image generation

Reference 17

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Observation 1e5abc39-9021-49d6-8b63-15ce95ed4fee · outbound

This paper cites VIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluation.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation VIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluation

Reference 18

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Observation fd29f28e-7ba9-4377-881e-7345fd63229c · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Multi-concept customization of text-to-image diffusion

Reference 19

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Observation 49365c10-8081-4ec1-b56c-12845b9c04e1 · outbound

This paper cites Holistic evaluation of text-to-image models.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Holistic evaluation of text-to-image models

Reference 20

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Observation 1bd714eb-f125-4c00-9927-2646a537b6fc · outbound

This paper cites GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 21

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Observation b4ba232f-7829-4ec7-94a6-3846824810e9 · outbound

This paper cites Evaluating and improving compositional text-to-visual generation.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Evaluating and improving compositional text-to-visual generation

Reference 22

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Observation 6dc4ac3c-753d-4ec2-ae99-68fa65054518 · outbound

This paper cites Blip-diffusion: Pre-trained subject representation for controllable text-to-image generation and editing.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Blip-diffusion: Pre-trained subject representation for controllable text-to-image generation and editing

Reference 23

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Observation 798f96f2-cacf-46a2-943a-da52e98e7db8 · outbound

This paper cites Science-t2i: Addressing scientific illusions in image synthesis.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Science-t2i: Addressing scientific illusions in image synthesis

Reference 24

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Observation 9f06d282-874c-4a0d-b22c-04d94b4a4482 · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Rich human feedback for text-to-image generation

Reference 25

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Observation bfdddb92-6456-4b80-84e6-9c188efbb1ea · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Evaluating text-to-visual generation with image-to-text generation

Reference 26

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Observation 481a1896-9b42-41f6-a953-80a733cd2052 · outbound

This paper cites Llmscore: Unveiling the power of large language models in text-to-image synthesis evaluation.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Llmscore: Unveiling the power of large language models in text-to-image synthesis evaluation

Reference 27

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Observation 68867e7c-2fb7-40e9-a590-99e9727bb743 · outbound

This paper cites Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps

Reference 28

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Observation d461ebed-ec12-46be-b344-a95a16f4f7af · outbound

This paper cites PhyBench: A Physical Commonsense Benchmark for Evaluating Text-to-Image Models.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation PhyBench: A Physical Commonsense Benchmark for Evaluating Text-to-Image Models

Reference 29

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Observation 3964ce9f-9f17-4662-ace8-aa6ea3b9e62b · outbound

This paper cites Midjourney version 6, 2024.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Midjourney version 6, 2024

Reference 30

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Observation eae11b18-8e14-493c-8ac3-d3666dbe26ce · outbound

This paper cites Addendum to gpt-4o system card: Native image generation, 2025.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Addendum to gpt-4o system card: Native image generation, 2025

Reference 31

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This paper cites Toward verifiable and reproducible human evaluation for text-to-image generation.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Toward verifiable and reproducible human evaluation for text-to-image generation

Reference 32

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Observation 37a47874-8eea-404d-a9a3-198a3b995e48 · outbound

This paper cites Teaching clip to count to ten.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Teaching clip to count to ten

Reference 33

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Observation c9382c27-0787-40e4-a11d-9b9e6779c11c · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 34

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Zero-shot text-to-image generation

Reference 35

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Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation High-resolution image synthesis with latent diffusion models

Reference 36

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Dream- booth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 37

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Observation 95d758fe-e73d-41a6-861f-0b67054236a1 · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Photorealistic text-to- image diffusion models with deep language understanding

Reference 38

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Observation 97a2557f-3e34-439b-b6c5-11430e8c3237 · outbound

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Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Improved techniques for training gans

Reference 39

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Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Enhancing image generation by fusing auto encoder & transformative generation approach

Reference 40

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Observation ab8faaa4-7d4b-4eca-b572-142f7c2330a8 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 41

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Observation e47f5798-5c80-4869-97a2-f217263df9e6 · outbound

This paper cites Conceptnet 5.5: An open multilingual graph of general knowledge.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Conceptnet 5.5: An open multilingual graph of general knowledge

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:29:23.159746Z

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Observation d68228e6-44a5-494f-af9d-d2e7fcc388e7 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Gemini: A Family of Highly Capable Multimodal Models

Reference 43

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Ratings

Reference 44

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This paper cites Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation

Reference 45

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Observation 9113fd68-0001-425a-adfe-b640bd8c608d · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 46

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This paper cites ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty

Reference 47

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Observation 50fd0ce5-2fc9-4961-bc78-26bd14e21a66 · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Imagereward: Learning and evaluating human preferences for text-to-image generation

Reference 48

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This paper cites What you see is what you read? improving text-image alignment evaluation.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation What you see is what you read? improving text-image alignment evaluation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:29:22.890638Z

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Observation ac01512f-127b-4625-9706-5d0f8abe1555 · outbound

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Reference 50

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Observation 6c99276e-8e7d-462f-b1c3-637c0ae3a42c · outbound

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Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation Sigmoid loss for language image pre-training

Reference 51

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Observation 8dfe7e35-1325-4ff5-8fce-280fbc210314 · outbound

This paper cites GPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation GPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks

Reference 52

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53f5a135-43f9-47b5-b72e-db4660a2314f · outbound

This paper cites A Contrastive Compositional Benchmark for Text-to-Image Synthesis: A Study with Unified Text-to-Image Fidelity Metrics.

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation A Contrastive Compositional Benchmark for Text-to-Image Synthesis: A Study with Unified Text-to-Image Fidelity Metrics

Reference 53

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Pith citing papers

Observation f4cced5a-a747-4f11-ab60-922e101f0195 · inbound

ToolArtist: Tool-Using Unified Multimodal Models for Agentic Image Generation cites this paper.

ToolArtist: Tool-Using Unified Multimodal Models for Agentic Image Generation Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation

Reference 1

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