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Paper Citation Record · LEDGER

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

As of 19 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 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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

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
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:13.694400Z digest=sha256:855270f2cca23b6eece11d5a7e8e81cf19c6737394b9b9b463411803d5e5c042

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

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raw_fallback, observed 2026-08-07T14:29:27.077673Z

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.

source=pdf_text observed=2026-08-07T14:29:13.847917Z digest=sha256:e451ce4a4a3893cadbcd65a25d64230fb96e40f8869ac8540afebbec975b852f

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

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local_arxiv, observed 2026-08-07T14:29:22.567556Z

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.

source=pdf_text observed=2026-08-07T14:29:13.981587Z digest=sha256:e94cef0d7bf1a7f8150ffeb585edc19ed25c28d5bae5e88d82e7a9a99753826d

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:14.112716Z digest=sha256:5e86ae2dc2156541e197ac3e8f06814ef9ee9b685502543deafd56a626bb5053

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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verified exact
raw_fallback, observed 2026-08-07T14:29:22.316111Z

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.

source=pdf_text observed=2026-08-07T14:29:14.286282Z digest=sha256:12189bebde0e1d20b2532c133d49de9f1912b7e6fd13c0a3fc0d425b255262cf

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:14.417588Z digest=sha256:10f2185480be194dd43eee52b0e2d5e559bec9c9bc6d241dfdd21fcbb313c6a6

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:14.601166Z digest=sha256:4dc6bd187318e13d085f789bd186b6b4f02787bf089fba9616d6ca72af54f3fe

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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no resolver link, observed 2026-08-07T14:29:14.789184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:14.789184Z digest=sha256:b427d1ca16fc684ced59e1176c57805feb7714f82667a6ed6f7a7fcf7f126418

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:14.923026Z digest=sha256:90e11378baf38fb23ff9e88efd0c1d1b9aea9259b2fe44637651434adfd8ec2f

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

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

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.

source=pdf_text observed=2026-08-07T14:29:15.109768Z digest=sha256:9c2efe7f0a5b5444baf615ebb5b4071b1ab4f5ddb035c2a31ff32a80c418a3d4

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:15.301188Z digest=sha256:7954aad1bc0c54a515767b75075b64fc004742a5092611b33901cac9cf1208e9

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:15.489580Z digest=sha256:fa53c5dc6d66a2985ff6509461e71ebd473a6ffe518395a74d00ac60618061b3

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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no resolver link, observed 2026-08-07T14:29:15.681993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:15.681993Z digest=sha256:5810953db4339e36b8e9d6af48007ac37fc8aabeec7a56973784419ddab87ee2

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:15.867570Z digest=sha256:f3ed14f8227666b5730805edbf67a3dff8ade236dfca8bf613516dd5c7432b79

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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raw_fallback, observed 2026-08-07T14:29:26.572628Z

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.

source=pdf_text observed=2026-08-07T14:29:15.998258Z digest=sha256:690129af2341e32ce179012d5b530979504cfd6ff09b3aa97bd20481eb2021c0

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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raw_fallback, observed 2026-08-07T14:29:22.049661Z

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.

source=pdf_text observed=2026-08-07T14:29:16.164128Z digest=sha256:7eae498217d4c63155a0e07f92d427dfab6dcfeaf87127b03a9187ba7c0f7dd0

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:16.279484Z digest=sha256:cccfd99cc683a4fed8a296743f8948446bf7c1e2cd0505d61dfef63ac39992ae

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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source=pdf_text observed=2026-08-07T14:29:16.408545Z digest=sha256:39dd13a4d8271ac3f398d3df1e4d88550e4378a1ba7ac1dab9a45a6a12f1d871

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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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:29:16.572717Z digest=sha256:89a243c1a3fbcd282f5d753cc5d9ebb9d91de3658a1b9fd9d1db6267dfc84f1d

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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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.

source=pdf_text observed=2026-08-07T14:29:16.687718Z digest=sha256:b243e28f9bc33e3f43483a4fcc804b370ba67932d61177a2a78065a9ffe788e4

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:16.838722Z digest=sha256:0b10dccb8c89754cb01f6f0ab64bfdb1c917adfb41b95057a0c5b5de0a5e70d2

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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raw_fallback, observed 2026-08-07T14:29:26.109268Z

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.

source=pdf_text observed=2026-08-07T14:29:16.980088Z digest=sha256:103f050f3edc244b6e6f7327670333254e8b47e05848dd0006f08699947304cd

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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source=pdf_text observed=2026-08-07T14:29:17.166743Z digest=sha256:1b4b2bf491a7bf2dbdcf2e915df8e7bc58a7ac68117c0a554bda77d2e33c7f4d

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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source=pdf_text observed=2026-08-07T14:29:17.284669Z digest=sha256:a75ce0c7125d3520386f0c5880fa0ffa386ce4ef11215e3d7eaa054f75a5f147

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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raw_fallback, observed 2026-08-07T14:29:25.806499Z

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.

source=pdf_text observed=2026-08-07T14:29:17.436476Z digest=sha256:7de29f86a16e47e2175370560609e5c9b64c03a28d15cd20c39e3531aa471c98

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:17.595148Z digest=sha256:b94ff45dc7836a6cbace409fe406d533a30b53cb97764c16523dc64ac0f2c468

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:25.552190Z

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.

source=pdf_text observed=2026-08-07T14:29:17.729078Z digest=sha256:ef6579128fb464dbfc4cf5e96c110e72e659c63ab762bfe2ac590ef4b09d0211

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:17.887379Z digest=sha256:eeb9de6f22397e0ea9d2819b93b30853197df1ca9a98506d96d85c514796639b

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:18.079146Z digest=sha256:ae60727d3477d6b25465fde45fa68a1ea7386657c56c695bfc0defa73c20bdbf

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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raw_fallback, observed 2026-08-07T14:29:25.220668Z

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.

source=pdf_text observed=2026-08-07T14:29:18.238625Z digest=sha256:62993465b9d2b6a6dca984c8253c5b9af09923f41750ed36467e5ec2b1b5d6ea

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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raw_fallback, observed 2026-08-07T14:29:24.828748Z

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.

source=pdf_text observed=2026-08-07T14:29:18.374045Z digest=sha256:858d6406538aaa3a822416cf10fa0708c98e8d7c95ed8d55726eed7d133072fc

Observation b1fa7751-f450-4eb1-9bf9-585305419fb4 · outbound

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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raw_fallback, observed 2026-08-07T14:29:24.454859Z

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.

source=pdf_text observed=2026-08-07T14:29:18.523882Z digest=sha256:5b91337823a19a80274aa1ad716c00adb5425f9b8c7ec546ba07248010238cf2

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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raw_fallback, observed 2026-08-07T14:29:24.122426Z

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.

source=pdf_text observed=2026-08-07T14:29:18.652281Z digest=sha256:8ea64e04ceccd4080adeead0d840f4827829860d973fcecd08039842af6f5dae

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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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:29:18.821920Z digest=sha256:3ae8df9f0b260303909e0448cb30b722884869ad90c4fe2b8fb90977d12306c2

Observation 7fb2f27d-6d47-4896-9d19-36e92326f8d1 · outbound

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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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:29:18.979999Z digest=sha256:60018a93699be95dc663e4d25b0b0a404bc580d4ba5890e65ce6eb7fa2933b8b

Observation d76aa6c1-2180-4ba8-a0ad-e45426ed8678 · outbound

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

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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source=pdf_text observed=2026-08-07T14:29:19.152449Z digest=sha256:c5631e955e4dd052ccf8141f5a5de2d06e0156f94c423ddb8c72e17a8bc17e9a

Observation f54582fd-e8b0-48f6-9018-350a703b5364 · outbound

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

source=pdf_text observed=2026-08-07T14:29:19.316019Z digest=sha256:27f31a1545e1b121dfe19fcb8c272989128dc24a8b7bc92b1301662089c6f5ae

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

This paper cites Improved techniques for training gans.

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

Reference 39

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Observation fe780c4f-4ce7-4489-93e9-279dcbd7eb5a · outbound

This paper cites Enhancing image generation by fusing auto encoder & transformative generation approach.

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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raw_fallback, observed 2026-08-07T14:29:23.446628Z

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.

source=pdf_text observed=2026-08-07T14:29:19.806945Z digest=sha256:cb41774d92658c716154a5d34c0d0c9c55da8c0bfd66aa27f965a2430a91673f

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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source=pdf_text observed=2026-08-07T14:29:19.937516Z digest=sha256:08456fa72ce527f9bb1dd97d862d1337f144bd97f39b14cdd1d76acd2c3af70f

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

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raw_fallback, observed 2026-08-07T14:29:23.159746Z

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.

source=pdf_text observed=2026-08-07T14:29:20.089494Z digest=sha256:f29aa307405ff0131b2fae04133da6bd0c6edc55bd84e62ea8fa76d63609390b

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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source=pdf_text observed=2026-08-07T14:29:20.226654Z digest=sha256:d3fa72743243096312efcedfb21a1cf62b37a018309107cba73999abec1e1a39

Observation 8e87ac9c-38de-46f8-a40f-655a398cedf0 · outbound

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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source=pdf_text observed=2026-08-07T14:29:20.385035Z digest=sha256:367acafb31a1a8bbe8b1584689dd20cb7e9a95491e19710eb221827d88f6ec69

Observation b020c638-43fa-41e1-b516-a4ebdaa05ea0 · outbound

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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source=pdf_text observed=2026-08-07T14:29:20.529173Z digest=sha256:1736ad53e69b075924e9457ebfd9614cfaf1d90701feb7ebbb6816257d40a0c4

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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source=pdf_text observed=2026-08-07T14:29:20.704757Z digest=sha256:529985a412032c532792f7aec347b19011048da0197bd8a388333a486ebd1f80

Observation fef0d297-ac87-43a2-930d-ca4374b4f151 · outbound

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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source=pdf_text observed=2026-08-07T14:29:20.813586Z digest=sha256:db3f90417fa768b35ab3f828a62123f275c7226c0480fe753985ce7a0376506e

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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source=pdf_text observed=2026-08-07T14:29:20.939357Z digest=sha256:f2d58d573f71cf2657ff0092e436f51498251fc69e0477dddaa9a973f2e8fed4

Observation 622168f4-d83d-4245-b848-2eba141ad681 · outbound

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

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raw_fallback, observed 2026-08-07T14:29:22.890638Z

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.

source=pdf_text observed=2026-08-07T14:29:21.069686Z digest=sha256:2e40e1008f6a7306db467e2d29b92ae5e7052dab09df1289c42331feefa8c304

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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source=pdf_text observed=2026-08-07T14:29:21.180996Z digest=sha256:1e88dfc216f84a6ece5ee664d9c110bad9e0ef3389900ce608708dd1fdd20ae2

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

This paper cites Sigmoid loss for language image pre-training.

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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source=pdf_text observed=2026-08-07T14:29:21.304097Z digest=sha256:00b5822e8938ed0f5db8965d40c577dd06726d2ab3e56f62c5301c5c6ff9d4ce

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=pdf_text observed=2026-08-07T14:29:21.420118Z digest=sha256:b907f1c51a47f9ae8d76fd8f3b561ac1314e6704d036e252964838610a1183ff

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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source=pdf_text observed=2026-08-07T14:29:21.502877Z digest=sha256:b1696c6517d03e0e12824abd97859df71a68b44265e7736a9ae5b6a5b810e938

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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local_arxiv, observed 2026-08-07T00:15:41.386031Z

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

source=pdf_text observed=2026-08-07T00:15:37.003251Z digest=sha256:480b754af2efef4569f5513338f4accf4a9c81be0fe3ca9d2cf27b459d59f8cd