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Paper Citation Record · LEDGER

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

As of 22 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 21 inbound Pith citation observations for arXiv:2506.07977.

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

pith.paper-citation-record.v1
2506.07977 v3

Coverage vector

measured 79 of 79 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:25:44.520732Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:59:46.927837Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:39:51.249678Z

Reference resolution

79 of 79 outbound references displayed

  • verified exact0
  • verified fuzzy21
  • unresolved58
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0224aeab-852f-406a-89d3-108203ddf297 · outbound

This paper cites Vqa: Visual question answering.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Vqa: Visual question answering

Reference 1

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source=pdf_text observed=2026-08-07T05:25:43.986102Z digest=sha256:56c77170592e98456a98ceb5c4ee8bc981c6e516100318855b3035e05c322174

Observation 7e1ba31c-aae5-4556-b7b4-c9aabfa73a0d · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2

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source=pdf_text observed=2026-08-07T05:25:43.991862Z digest=sha256:98d16e9a78d07dc65e955f3b55ec7c08ce12fbbc60acbf74a42e55b2216a5307

Observation a46aea39-57c0-4e85-bce0-3fd07e1b15ce · outbound

This paper cites Qwen2.5-VL Technical Report.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Qwen2.5-VL Technical Report

Reference 4

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source=pdf_text observed=2026-08-07T05:25:44.003618Z digest=sha256:3fc47b5bd3491f7ae2d085db294c51fe61dc73e35cc8edd28a1e2beb4572a3fc

Observation 63ed52be-1d1e-4d98-9d6a-e6bdc28dfd8f · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Hrs-bench: Holistic, reliable and scalable benchmark for text-to-image models

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.009084Z digest=sha256:60c6ed8e0f4b61c6d42086857911ab31a5023694804976e15d4bfd1d4c52af0b

Observation bd62b77d-ddf4-4c43-a4ee-adfa7808a266 · outbound

This paper cites The official api of flux-1.dev.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation The official api of flux-1.dev

Reference 6

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.014278Z digest=sha256:c5a9511b2d9ecbe178480f341a21c791010f5153e3c2f94a5cfc714d1fb498c5

Observation 67ba8ebf-cff5-4887-bf2d-d277df26f5af · outbound

This paper cites Attend-and-excite: Attention- based semantic guidance for text-to-image diffusion models.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Attend-and-excite: Attention- based semantic guidance for text-to-image diffusion models

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.019581Z digest=sha256:93bfe215ad5e591dac0d8dc9faad10dbd052bc8b29675b8d471d6038903a3fcb

Observation 75a3d805-a6d0-4caa-9a43-22a23b0c37a1 · outbound

This paper cites BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset

Reference 8

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source=pdf_text observed=2026-08-07T05:25:44.024265Z digest=sha256:f76b80b253da0d3c0587dc4b25908ffe178a164da4458ef03f9fdb7672d9c2d9

Observation 3debd87b-aef4-4233-b21b-43f9fdf8d9bf · outbound

This paper cites Pixart-sigma: Weak-to-strong training of diffusion transformer for 4k text-to-image generation.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Pixart-sigma: Weak-to-strong training of diffusion transformer for 4k text-to-image generation

Reference 9

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.029143Z digest=sha256:29181efaa871fb503dc280d467f1d9e86f42d07ab78656cc9668d57a39c6a67c

Observation b09b4e0d-f642-4469-8b74-b38645309a4c · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 10

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source=pdf_text observed=2026-08-07T05:25:44.033958Z digest=sha256:0e0b34520399be0c6564d340b66deee93d2dcdcf770dca90d541e2947fde5894

Observation 28c36f47-fe3c-40e4-ad65-3c1f65b77c9a · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 11

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source=pdf_text observed=2026-08-07T05:25:44.040123Z digest=sha256:22a614792aad524b5fd53416cde4001ea708a3b15e4f5288f2ee9539c592d2f8

Observation a21fb488-8122-4e43-a190-1cae4cb794f3 · outbound

This paper cites Generative pretraining from pixels.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Generative pretraining from pixels

Reference 12

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source=pdf_text observed=2026-08-07T05:25:44.045275Z digest=sha256:2c39058d71d0a2c06152fe386af979e98a00035587ebc199d3633bd200043fa4

Observation dc1bd828-3e8e-4271-a2fa-ab5d84a8dd93 · outbound

This paper cites Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling

Reference 13

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source=pdf_text observed=2026-08-07T05:25:44.050469Z digest=sha256:bc5431e7d2d03c2f094fa1bedc6ea5d9bd9aa596820b20b0d0000d71d36b8a2e

Observation deced6d7-3dd1-4d2c-b650-b344aa5d0619 · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 14

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source=pdf_text observed=2026-08-07T05:25:44.055680Z digest=sha256:8a4518d081e86ef0816130ec556d061a216f0c5da7e59b2e38a3c4ead721fb81

Observation 10f86999-c4bc-44b4-bc1c-5005dc1bc195 · outbound

This paper cites Mask2Former for Video Instance Segmentation.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Mask2Former for Video Instance Segmentation

Reference 15

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source=pdf_text observed=2026-08-07T05:25:44.060493Z digest=sha256:e8c4845892941a27c889a60e7211ea96e93784803a17d1f91b115e3749e67949

Observation 45f95dfa-7c79-490a-8eb0-3d73ba18dab3 · outbound

This paper cites Davidsonian scene graph: Improving reliability in fine-grained evaluation for text-to-image generation.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Davidsonian scene graph: Improving reliability in fine-grained evaluation for text-to-image generation

Reference 16

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.065918Z digest=sha256:24d0abc4675e3eb9c1106f83752fa0957ce72b851211f2217af0f17bf9a99eab

Observation ff38fb48-5b64-448b-99fa-9dc7ca5a8b31 · outbound

This paper cites an unresolved cited work.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Unresolved cited work

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.070702Z digest=sha256:48e3c1431300bfd2ccaa52035d7b7e8e46133dcdf3a27d6cc4a832a83b12b354

Observation 1c16c095-5132-41f6-9044-b4f46a23346a · outbound

This paper cites Emerging Properties in Unified Multimodal Pretraining.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Emerging Properties in Unified Multimodal Pretraining

Reference 18

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source=pdf_text observed=2026-08-07T05:25:44.076301Z digest=sha256:1babbef714a62d85e93846e50e26e3056894f978cc80ef37008e66a084abc5e0

Observation 3a8a880e-3c23-47b6-8cc8-8dae56163a41 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Scaling rectified flow transformers for high-resolution image synthesis

Reference 19

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.081486Z digest=sha256:1cbdd3b77820085d9389674ab369bdd04138825752545de2c99f34d2d9589a2c

Observation ec9d9ce4-a2f7-453e-9788-e540916e9461 · outbound

This paper cites Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis

Reference 20

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source=pdf_text observed=2026-08-07T05:25:44.086087Z digest=sha256:afc71bdb06a2d4f440540683fe7f34a95a020d36cd637d2a6da15b47aac3d8e3

Observation 0ceee4f6-5acf-4756-b317-1156f2595266 · outbound

This paper cites Dreamsim: Learning new dimensions of human visual similarity using synthetic data, 2023.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Dreamsim: Learning new dimensions of human visual similarity using synthetic data, 2023

Reference 21

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source=pdf_text observed=2026-08-07T05:25:44.090847Z digest=sha256:2d44c5b5da2e150419c8db91614638a841a795bcbbfa423ffb35b1e6ed6a09d1

Observation 16ad961e-f0ce-402b-b9f1-d84bc5b2ff81 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 22

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source=pdf_text observed=2026-08-07T05:25:44.095229Z digest=sha256:1748f406db12bcbd53afc6e49ce75866354a46ee0d4c7b005614930d935c9df0

Observation 1c5ff251-2783-4b48-93f1-ccda884f8dfa · outbound

This paper cites Distilling diversity and control in diffusion models.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Distilling diversity and control in diffusion models

Reference 23

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source=pdf_text observed=2026-08-07T05:25:44.100097Z digest=sha256:7034732a5f2df593622fa9ccaa5d6978b37d1660f2da497e1b915b453e863787

Observation 6520c209-2447-4565-9cc8-3748ff9e87cb · outbound

This paper cites Seedream 3.0 Technical Report.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Seedream 3.0 Technical Report

Reference 24

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source=pdf_text observed=2026-08-07T05:25:44.105493Z digest=sha256:73e898069564aedfcf8ddb8c6ae4d76cb09b99bb7936dba908142ad9a924cb9e

Observation a6949646-a872-48bc-bbf7-356dfb6921e2 · outbound

This paper cites Geneval: An object-focused framework for evaluating text-to-image alignment.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Geneval: An object-focused framework for evaluating text-to-image alignment

Reference 25

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source=pdf_text observed=2026-08-07T05:25:44.110467Z digest=sha256:3c0261cb9c0f02bddf5c1860a27c4ac2dcaea122edc5b074d50d3245ce18620e

Observation 44db4c0d-9c4d-4f6d-a8d8-b228283e5424 · outbound

This paper cites Generative adversarial networks.Communications of the ACM, 63(11):139– 144, 2020.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Generative adversarial networks.Communications of the ACM, 63(11):139– 144, 2020

Reference 26

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source=pdf_text observed=2026-08-07T05:25:44.116471Z digest=sha256:b244e9677f055160579c65e0bda089e4a08d18fce740c2eddcd780ed3240afed

Observation 03c0aa6c-bbed-40ca-b3ef-e4919b535d6f · outbound

This paper cites Evalmuse-40k: A reliable and fine-grained benchmark with comprehensive human annotations for text-to-image generation model evaluation, 2024.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Evalmuse-40k: A reliable and fine-grained benchmark with comprehensive human annotations for text-to-image generation model evaluation, 2024

Reference 27

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.123351Z digest=sha256:7824b15681578162f8e1ac2fe299b6b2b5509c5eaf1994b61ba5d5a6eb140c0a

Observation 2ba7f8f4-54af-43f7-91aa-f3bca75f2a50 · 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.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for 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 28

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source=pdf_text observed=2026-08-07T05:25:44.128309Z digest=sha256:fc126e02ff127d4643b340b56b5a9905173c4869c5ef2bc3e64b65a6f8ba6c93

Observation b315326f-0cf2-4edc-b4eb-601c0cc26228 · outbound

This paper cites Hidream-i1.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Hidream-i1

Reference 29

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.132974Z digest=sha256:7a1235566681a38e6bdbf65f0ff3cff3b17089d836db0643a8c6b66c30ca04af

Observation 6ed22e4c-05e0-4a7c-bc7b-0d01489df1d4 · outbound

This paper cites Denoising diffusion probabilistic models.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Denoising diffusion probabilistic models

Reference 30

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source=pdf_text observed=2026-08-07T05:25:44.137448Z digest=sha256:9940a0e17ede252387401ded9ebf7e70db1f90b9fcfe42bd492ddd65c567e2e7

Observation 4f3f05dd-3ad5-4fee-89e4-bd8d256c09ae · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment

Reference 31

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source=pdf_text observed=2026-08-07T05:25:44.141991Z digest=sha256:11ca6b1b2ba0fb4bade668a335b6b2279d05081a7ec4af3f13cac8fbaec5a3a0

Observation b67fc08d-238f-4761-b46a-ccc65e0ad39f · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Tifa: Accurate and interpretable text-to-image faithfulness evaluation with question answering

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.146947Z digest=sha256:af494b8b50e1e9587e5d48676b2cb8125f1a157bf67e0abf470ddd1e0afb2849

Observation f5732f7a-a022-4639-9bc7-71935afc4ef1 · outbound

This paper cites T2i-compbench++: An enhanced and comprehensive benchmark for compositional text-to-image generation.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation T2i-compbench++: An enhanced and comprehensive benchmark for compositional text-to-image generation

Reference 33

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raw_fallback, observed 2026-08-07T05:25:45.540308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.151303Z digest=sha256:b0c01fe9a2509f5a24ba69b17966e3ef4f4611e45440c9b08f399c05a7ddba76

Observation 03576435-53b7-4798-811a-2fcc531e2899 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation

Reference 34

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source=pdf_text observed=2026-08-07T05:25:44.156341Z digest=sha256:0f52829f484241728fffcd712e8b03881409d349754a8e6cf40f0c9d988968c4

Observation 0695f3ae-478a-4700-a002-8ef519ae4d8a · outbound

This paper cites Llm2clip: Powerful language model unlock richer visual representation.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Llm2clip: Powerful language model unlock richer visual representation

Reference 35

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source=pdf_text observed=2026-08-07T05:25:44.161137Z digest=sha256:cd26b365bbb418480de83d9c076c01c739be44068182ca2e5add87a999746ad3

Observation 3a60a612-5238-4cb7-b067-5a1c93532628 · outbound

This paper cites Imagen 3, 2024.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Imagen 3, 2024

Reference 36

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raw_fallback, observed 2026-08-07T05:25:45.511400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.165584Z digest=sha256:5d66bd6fbcc716747ffba041e8c44cbab98eb0a6dc0b1d541b324369380d4ed0

Observation acd379d9-af82-4da0-adee-6decab8d9562 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Pick-a- pic: An open dataset of user preferences for text-to-image generation

Reference 37

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source=pdf_text observed=2026-08-07T05:25:44.170115Z digest=sha256:cf4507d99ef4c8e1011734b8b0a2dcf103d5875258f1609ebb3eb5ed3e284c83

Observation 0e2bb515-390b-44e1-89c3-c43d159f40e7 · outbound

This paper cites an unresolved cited work.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Unresolved cited work

Reference 38

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source=pdf_text observed=2026-08-07T05:25:44.174864Z digest=sha256:de19c01fd75beda85a341876241772fc55924d999dd731cc6e1f970de1f7d3bb

Observation 57a1ef34-babb-4bcd-8a90-6077c31f9dce · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 39

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source=pdf_text observed=2026-08-07T05:25:44.179662Z digest=sha256:77c43c9856f640408c92d7248ce412f5afc309ab07670d69d79ab77aa0738ab5

Observation af7f3d7c-83b6-460d-8f3b-eb2989350fb5 · outbound

This paper cites Playground v2.5: Three insights towards enhancing aesthetic quality in text-to-image generation, 2024.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Playground v2.5: Three insights towards enhancing aesthetic quality in text-to-image generation, 2024

Reference 40

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source=pdf_text observed=2026-08-07T05:25:44.184414Z digest=sha256:cebbd0824a4a731ad6b20b0d39729a7ccf1785ab5a0d634d162e0b64c22445ac

Observation 93446f06-d01f-42b5-addf-57f1fd37a952 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 41

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source=pdf_text observed=2026-08-07T05:25:44.188963Z digest=sha256:1b1dedf18d8f46c56cbb9bec574453df372e98e5252ab90ccdfe193672abacb7

Observation b1d644db-517c-43f0-82e0-07ae67a7ccf6 · outbound

This paper cites Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers

Reference 42

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.324766Z digest=sha256:93f04b8566794cdf05ff5e49ac9954f76d75623cbb5e040175acd4f5de5f8927

Observation c19071cf-049e-4ce7-b263-d227424ead75 · outbound

This paper cites WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation

Reference 43

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source=pdf_text observed=2026-08-07T05:25:44.329662Z digest=sha256:3e4ae28d97887599013a72a787bfb37a0edd07a03981e80fd86e4b9da04e556c

Observation 207e4c3a-93a8-4f0c-940d-efe9d6d35553 · outbound

This paper cites Gpt-4o system card.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Gpt-4o system card

Reference 44

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source=pdf_text observed=2026-08-07T05:25:44.334614Z digest=sha256:9e896f3c054265b54e77d3e2def56ad05576b4040704cf047b31c37954d8e6a8

Observation 1524515d-0ee5-492d-9439-a6f628046347 · outbound

This paper cites Introducing 4o image generation.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Introducing 4o image generation

Reference 45

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.339063Z digest=sha256:47a392914d798e8aab72639b9cb2826bbc46cb049ec0ee25738ce5669535e6bb

Observation 220f40d5-9c80-4ceb-8cc6-64d61211148c · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 46

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source=pdf_text observed=2026-08-07T05:25:44.344113Z digest=sha256:e1c98ca09d9f313da4b4136e3b9368dff7e22e4f6a35c40aa3ab215d869d807d

Observation e7405897-fa72-4c77-9977-948a928a367e · outbound

This paper cites Lumina-image 2.0: A unified and efficient image generative framework, 2025.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Lumina-image 2.0: A unified and efficient image generative framework, 2025

Reference 47

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source=pdf_text observed=2026-08-07T05:25:44.348906Z digest=sha256:3efb354e9694dfd5a2c1f5d6014aec131cf46bd24394ace10e7d8445be1850e5

Observation ef9be859-608e-4677-a58a-2d2f2b39bf22 · outbound

This paper cites PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models

Reference 48

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source=pdf_text observed=2026-08-07T05:25:44.353897Z digest=sha256:b6ccfc4b1116bcb2a2191b7f64ed8c73e8de2c9e1fe67941b5a15057947cc6e6

Observation 42a7b0b3-c958-493a-9286-6edac2e725a4 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Learning transferable visual models from natural language supervision

Reference 50

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source=pdf_text observed=2026-08-07T05:25:44.364376Z digest=sha256:c9f6c5d02c79305736062c9f49144303fb74e1aea334c3d3214120b7ecc2d3ed

Observation 9e90daba-94ee-4897-9e8c-ce0b37685468 · outbound

This paper cites Language models are unsupervised multitask learners.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Language models are unsupervised multitask learners

Reference 51

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source=pdf_text observed=2026-08-07T05:25:44.368924Z digest=sha256:13ab6009700ab4a7da69985d2eeccf273363afdcae6056f7337fb8083098f1e6

Observation e62e35a5-d6ab-4e8b-aff7-21cf83a24ce2 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 52

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source=pdf_text observed=2026-08-07T05:25:44.374272Z digest=sha256:999ff68f43f65bc106d6e480ab2c44a1803fea134bc2e6477c0070cf2adab458

Observation 5dd96539-18fb-4c72-a978-da805d2c4f69 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 53

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source=pdf_text observed=2026-08-07T05:25:44.378716Z digest=sha256:4c66b4fd962558e7f9943269df0e6135ee6af99d966b105aa0c5883a4805b0b0

Observation 6e033c79-ef6c-44eb-9dc0-8bff93d04ee8 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Zero-shot text-to-image generation

Reference 54

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source=pdf_text observed=2026-08-07T05:25:44.383658Z digest=sha256:da54110f28da2ff6253302df1326fb2a634af607b8055fd7bf659c693b7e161d

Observation 783e479a-eb5f-4b52-869c-2383b41277e5 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation High-resolution image synthesis with latent diffusion models

Reference 55

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source=pdf_text observed=2026-08-07T05:25:44.388060Z digest=sha256:8406f3d1a9914033d36de8ca93344d64e1ceaff58ca706e55897e38d8d5ee79e

Observation c5000dc2-bdef-4a2a-8c4a-742e1dde46f6 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Photorealistic text-to- image diffusion models with deep language understanding

Reference 56

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source=pdf_text observed=2026-08-07T05:25:44.394044Z digest=sha256:b2f0f4e4ab0791186bf146ea958c33d4dce94a88e926c68261922777c44117ab

Observation 373711cc-d37d-488d-b2b6-cde41f1e96d0 · outbound

This paper cites Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis

Reference 57

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.399509Z digest=sha256:9171d2051dd873e179b81473e4b6b6b9a204cf0fd60c7e897e70601e53678a9d

Observation a4cec638-0a26-49a3-8f32-3db73838c31b · outbound

This paper cites Measuring Style Similarity in Diffusion Models.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Measuring Style Similarity in Diffusion Models

Reference 58

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source=pdf_text observed=2026-08-07T05:25:44.404354Z digest=sha256:2a58fa42eac4da6988513d6588f734a3d7492a13d27d5b725d2eba3d461c5d8d

Observation 52fe9ff2-7635-435d-b8ab-18940e5915b3 · outbound

This paper cites Denoising Diffusion Implicit Models.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Denoising Diffusion Implicit Models

Reference 59

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source=pdf_text observed=2026-08-07T05:25:44.409667Z digest=sha256:47443a3a338de77ce7f09bb3a40db4644275de501e9805b0cfbbc8ed319741ea

Observation d0bc6807-5c52-4eb1-90c8-ab840810a3b6 · outbound

This paper cites stable-diffusion-3.5-large.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation stable-diffusion-3.5-large

Reference 60

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raw_fallback, observed 2026-08-07T05:25:45.330279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.415559Z digest=sha256:c7464143823661f4081ec62f143701403a71def3ba8d1bd096d16ec9794d80b5

Observation 8ea5534e-b4bb-429d-a619-65ec5d00e7de · outbound

This paper cites Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 61

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source=pdf_text observed=2026-08-07T05:25:44.420597Z digest=sha256:97988d8c75f3153703cb34710fca789d553470f125b93c778819fd83659a1192

Observation f73d692f-6367-479b-b28d-b770f2fcec2d · outbound

This paper cites Evalalign: Evaluating text-to-image models through precision alignment of multimodal large models with supervised fine-tuning to human annotations.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Evalalign: Evaluating text-to-image models through precision alignment of multimodal large models with supervised fine-tuning to human annotations

Reference 62

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.425146Z digest=sha256:e4ac06a943c1c6ad526776b42a3d4b9d4d772d56c0197509255da0eba5547d6f

Observation 181de5af-0728-47ca-8398-898db9ce1af6 · outbound

This paper cites Chameleon: Mixed-Modal Early-Fusion Foundation Models.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 63

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source=pdf_text observed=2026-08-07T05:25:44.429923Z digest=sha256:edd44aaf08101f893f80a4787353bbf923fa6d67351ccadb0066d207e3da2ea3

Observation 05a32a37-fbc0-45c4-a9b6-85cd2b48eb85 · outbound

This paper cites Kolors2.0.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Kolors2.0

Reference 64

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source=pdf_text observed=2026-08-07T05:25:44.434498Z digest=sha256:3941991a472243b6c71460ea794f97b22fa316942b5f566a24febd5673b39623

Observation 448a2f39-c47c-42f5-b174-deb4fb53bd21 · outbound

This paper cites How to create sota image generation with text recrafts ml team insights.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation How to create sota image generation with text recrafts ml team insights

Reference 65

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.438808Z digest=sha256:7dd28b6203f4b1852bdda6158758009cd8bb25e760cd0ad57b757cbe04d8b608

Observation c2ae66e5-18e1-4242-9ba0-a7b9ba6c4eea · outbound

This paper cites Recraft v3.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Recraft v3

Reference 66

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.443618Z digest=sha256:4ec21d57c66ba3d8d8fe24700f536280c3817b236575b32c576df2eb7e8d58e0

Observation 13106869-5090-48b4-bf5b-7f15e51e5d4e · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 67

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source=pdf_text observed=2026-08-07T05:25:44.448457Z digest=sha256:5627f01de30f9036e4767364e1ddbabd8687770bc5bccd9386b8649a3d05e092

Observation 8c9e52a7-9376-499a-9888-4cc69efb9600 · outbound

This paper cites Emu3: Next-Token Prediction is All You Need.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Emu3: Next-Token Prediction is All You Need

Reference 68

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source=pdf_text observed=2026-08-07T05:25:44.453240Z digest=sha256:b528453197d47350766b3a9af614b380af5b917406c9b2663539de3039e99aaa

Observation 2eeba09a-a1c8-43b2-8348-8fa434d0148a · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Image quality assessment: from error visibility to structural similarity

Reference 69

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source=pdf_text observed=2026-08-07T05:25:44.458981Z digest=sha256:e7a2fbe6ccd9c64badcd2daf3e19eb3b094561ca41c138eb24391e88b475ebe4

Observation ac1cb8d5-3e7a-40dc-a870-2c8bc2c35341 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Ratings

Reference 70

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source=pdf_text observed=2026-08-07T05:25:44.463994Z digest=sha256:ded93c678e672b756a50a7f13c11953ab0af28040c94fc4c364e0c25df693012

Observation c67b9732-02e1-478b-8c54-be1a6568717f · outbound

This paper cites OmniGen2: Towards Instruction-Aligned Multimodal Generation.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation OmniGen2: Towards Instruction-Aligned Multimodal Generation

Reference 71

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source=pdf_text observed=2026-08-07T05:25:44.468825Z digest=sha256:8a088ae4bf7b6c057a44ec506b83ad70215176883fde1e7a1a404fcff4ebfb4a

Observation 170abaf6-347f-4310-9c00-3d5f7aa819f9 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 72

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source=pdf_text observed=2026-08-07T05:25:44.474579Z digest=sha256:c551348a0b5613e33ae9e82f9cfb529726f4a50e9a68750bf37dbccd2228b96f

Observation 8f301db4-0be5-4268-8054-69fe550fc666 · outbound

This paper cites Sana 1.5: Efficient scaling of training-time and inference-time compute in linear diffusion transformer, 2025.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Sana 1.5: Efficient scaling of training-time and inference-time compute in linear diffusion transformer, 2025

Reference 73

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source=pdf_text observed=2026-08-07T05:25:44.479994Z digest=sha256:8dbc019ff4592c1daa23d35e4c941b5d9098f85805a0680ba6c690dcefab5bc2

Observation 614d90cd-6d56-4b5d-9109-217b96512529 · outbound

This paper cites Show-o: One Single Transformer to Unify Multimodal Understanding and Generation.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Reference 74

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source=pdf_text observed=2026-08-07T05:25:44.485018Z digest=sha256:efb48785ec5977550f5f69eb68236e25981d086c92e3d9e5b20f87f70360f3b7

Observation b659cb1e-ddd8-4f3f-9172-17de88b0f0ab · outbound

This paper cites Show-o2: Improved Native Unified Multimodal Models.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Show-o2: Improved Native Unified Multimodal Models

Reference 75

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source=pdf_text observed=2026-08-07T05:25:44.490660Z digest=sha256:4b51f9f595cfe212c333678cd571fb9f9344f21023a597fcfce119c50ed38846

Observation 739d742f-a702-4a60-95fa-849647ae7b45 · outbound

This paper cites CSGO: Content-Style Composition in Text-to-Image Generation.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation CSGO: Content-Style Composition in Text-to-Image Generation

Reference 76

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source=pdf_text observed=2026-08-07T05:25:44.495435Z digest=sha256:9c8fbb77c04372e04b818be9fef042ed31decd490f80a6a29179a09579ded6c0

Observation 25a8ef6f-7c96-4537-acab-f6ba0e316079 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Reference 77

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source=pdf_text observed=2026-08-07T05:25:44.500274Z digest=sha256:3b80bb4efd6af93840dbb80947cef03004b99db14efe012af2ec254aaf73183a

Observation 01b65e69-e555-45a6-b796-a459c967543b · outbound

This paper cites Cogview4.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Cogview4

Reference 78

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raw_fallback, observed 2026-08-07T05:25:45.235804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.505964Z digest=sha256:b2b8094958efa2dc16238e1e743c3a45a74b242a9825b3db728dc657805dc588

Observation 5119290e-d55a-449d-b210-6d98d9551256 · outbound

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Sigmoid loss for language image pre-training

Reference 79

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source=pdf_text observed=2026-08-07T05:25:44.510477Z digest=sha256:bd64c608800781834254afa08f299b35f1e9597bb35d5cbf047776375a9021b7

Observation cd798b1e-c5ac-4aa6-9482-7b19ef2ffb2f · outbound

This paper cites Worldgenbench: A world-knowledge-integrated benchmark for reasoning-driven text-to-image generation, 2025.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation Worldgenbench: A world-knowledge-integrated benchmark for reasoning-driven text-to-image generation, 2025

Reference 80

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raw_fallback, observed 2026-08-07T05:25:45.209610Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.515840Z digest=sha256:4e7a86c3f577ca8a7d540af9e885a643baaaabd324573d108027a4e1dbcdcbe3

Observation eac599bc-6709-4c91-a204-1626b965f6c9 · outbound

This paper cites K & R" is the abbreviation for.

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation K & R" is the abbreviation for

Reference 81

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raw_fallback, observed 2026-08-07T05:25:45.192133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T05:25:44.520732Z digest=sha256:f2c270883dc8aba96ee83e829590be50910063514f81c1dbabcffcc35a05f9dc

Pith citing papers

Observation b1f74876-055f-44f3-90c4-18203316a66c · inbound

Show-o2: Improved Native Unified Multimodal Models cites this paper.

Show-o2: Improved Native Unified Multimodal Models OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 13

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arxiv_id, observed 2026-05-12T18:51:16.085575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-12T18:51:15.428692Z digest=sha256:70b563accca69df4e73221ab8126bac20864efa5365ef0e9478d5963845b0d2f

Observation fba26abe-b8c3-4469-9e75-f0cae9f0748d · inbound

X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again cites this paper.

X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 81

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source=pdf_text observed=2026-08-06T12:10:08.475625Z digest=sha256:8b655fa2905411bd39229d34cf69b8391c9134381934ece8a9c275c7451c2225

Observation 22f6b097-4e7f-41ab-9e57-d280bed86530 · inbound

Qwen-Image Technical Report cites this paper.

Qwen-Image Technical Report OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 5

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arxiv_id, observed 2026-05-10T14:29:06.936121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T14:29:06.883874Z digest=sha256:725275846e293c8f60dbf846387c756e2f0b17268626c24a08d358e580ee0d90

Observation c1c9beee-3b0d-41a7-af2f-2b5562734f09 · inbound

Interleaving Reasoning for Better Text-to-Image Generation cites this paper.

Interleaving Reasoning for Better Text-to-Image Generation OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 2025

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no resolver link, observed 2026-08-04T22:55:44.864389Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:55:44.864389Z digest=sha256:9edd57395b9f0b85c6cb14a79231e70ea14f9d519dd0b8033c5d6560034a7a6d

Observation 7074b797-ab45-45af-9c31-e98a5a625764 · inbound

Emu3.5: Native Multimodal Models are World Learners cites this paper.

Emu3.5: Native Multimodal Models are World Learners OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 12

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arxiv_id, observed 2026-05-18T01:12:13.675245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-18T01:12:13.426640Z digest=sha256:a1605329da1b034d6aafe55161119a5dcda6af752fbd5ef29695178c8cf012b0

Observation 6a23d3a8-3df1-4f94-b84b-6199dfdfac30 · inbound

Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer cites this paper.

Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 9

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arxiv_id, observed 2026-05-11T14:08:37.325689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-11T14:08:36.801359Z digest=sha256:dc06429d9bec9d49d1f83e2a65cf9f766e644aea5a8ec45b02a514579ff1258d

Observation 245f5d62-2469-4ceb-8d6f-5b2ee348c88f · inbound

Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer cites this paper.

Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 9

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no resolver link, observed 2026-08-03T19:47:30.934626Z

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source=pdf_text observed=2026-08-03T19:47:30.934626Z digest=sha256:0a0ad21de56c9aa5a8cfa36712e1f1851e09a2896056ee59403156a71fed7cdd

Observation 568bf610-c062-4a32-9e82-cbf03f3e8202 · inbound

Nucleus-Image: Sparse MoE for Image Generation cites this paper.

Nucleus-Image: Sparse MoE for Image Generation OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 43

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verified exact
arxiv_id, observed 2026-05-11T10:26:00.452725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T15:30:46.994872Z digest=sha256:e0b99b932e6cb96b675e5b14d7aebb4f957e955fc138b59ff9e348d9e34e79b7

Observation 804c0179-ebd8-4a8c-a3e3-ba96c5e1152f · inbound

Knowledge Visualization: A Benchmark and Method for Knowledge-Intensive Text-to-Image Generation cites this paper.

Knowledge Visualization: A Benchmark and Method for Knowledge-Intensive Text-to-Image Generation OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 6

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arxiv_id, observed 2026-05-11T19:06:12.389791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-08T12:31:52.893480Z digest=sha256:f8aa50be0af5fcebd1044aa640ace3519724612e3c77018650fb3583d0fed412

Observation 71d5c1ad-1931-4f39-988a-69d7aa632b8f · inbound

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture cites this paper.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 12

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arxiv_id, observed 2026-05-13T05:17:18.581960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-13T05:12:37.339084Z digest=sha256:c6c145fc6a8700954640a302d978f90a34133c36db58f6d42232ad0556bdc1d6

Observation 9f0355ce-c8f9-46f5-bd35-77f9a17a7aba · inbound

When Preference Labels Fall Short: Aligning Diffusion Models from Real Data cites this paper.

When Preference Labels Fall Short: Aligning Diffusion Models from Real Data OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 2

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arxiv_id, observed 2026-05-20T06:13:05.219203Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-20T06:13:01.821585Z digest=sha256:31c129aec1393b0199dbb7121457df85008711fbadddf79c51fe98a5cf71759f

Observation 5b6d85ca-6a43-4c61-b1b2-4ede8d1828a1 · inbound

When Preference Labels Fall Short: Aligning Diffusion Models from Real Data cites this paper.

When Preference Labels Fall Short: Aligning Diffusion Models from Real Data OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 2

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arxiv_id, observed 2026-06-30T18:14:59.858980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T18:12:11.972394Z digest=sha256:8e48c2053c2617ec705fa9749a9281812edf79675f18586d64abe08cf107dba4

Observation cb589d4d-a51a-483f-837b-433042cf561f · inbound

High-Fidelity Two-Step Image Generation via Teacher-Aligned End-to-End Distillation cites this paper.

High-Fidelity Two-Step Image Generation via Teacher-Aligned End-to-End Distillation OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 1

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arxiv_id, observed 2026-07-03T10:37:56.949559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T09:54:36.000245Z digest=sha256:b29de3452051920b2499c7fae5f64952f84bef943afd74833f41e19240608782

Observation 80b153a3-d307-46a6-a802-f7767d3dddfc · inbound

HYDRA-X: Native Unified Multimodal Models with Holistic Visual Tokenizers cites this paper.

HYDRA-X: Native Unified Multimodal Models with Holistic Visual Tokenizers OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 212

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arxiv_id, observed 2026-07-03T14:28:29.699718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-27T07:01:07.362430Z digest=sha256:7fe667234619ee51e9264a7fbecc43c8a09f2f174f0b086645b5d04147755b6f

Observation d73c5fff-b468-4059-aea2-1df7d5fd5d0f · inbound

WeGenBench: A Multidimensional Diagnostic Benchmark towards Text-to-Image Model Optimization cites this paper.

WeGenBench: A Multidimensional Diagnostic Benchmark towards Text-to-Image Model Optimization OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 23

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arxiv_id, observed 2026-07-04T03:39:29.338045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T17:54:09.656061Z digest=sha256:97733b95cdaa5f2535af50f70633d8606118552f6ea3d917db82ab6495604ae3

Observation 37bfc01f-92ce-4066-bd89-395025e787b6 · inbound

TMP: Tree-structured Mixed-policy Pruning for Large-scale Image Generation and Editing cites this paper.

TMP: Tree-structured Mixed-policy Pruning for Large-scale Image Generation and Editing OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 4

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arxiv_id, observed 2026-07-04T13:39:51.252294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T04:59:12.294502Z digest=sha256:d6d930d79b936afddcbab69131f3d9edfc310d61cb9df23485e5b4d44c42268a

Observation 3700a9bf-6ff2-4cf6-8ab3-46ed487984da · inbound

COMFYCLAW: Self-Evolving Skill Harnesses for Image Generation Workflows cites this paper.

COMFYCLAW: Self-Evolving Skill Harnesses for Image Generation Workflows OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 56

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arxiv_id, observed 2026-07-03T14:28:31.278327Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-07-03T14:22:25.280140Z digest=sha256:9b0570d82d2b3c2b02178363320888db8702416fcc583e31ffd8ff4b307c0947

Observation 3bf47c79-a902-40c7-92ea-b1dd3384aabc · inbound

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget cites this paper.

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 21

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no resolver link, observed 2026-08-02T06:13:51.220875Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T06:13:51.220875Z digest=sha256:96fe2e68f44846e4cc23db9ed19fa122953b984a5e84a737bd13a0ac46caf6be

Observation 5f638d58-3ce3-4a7f-9114-9e0ae05d6ef8 · inbound

Parallel Decoding Distillation for Fast Image and Video Generation cites this paper.

Parallel Decoding Distillation for Fast Image and Video Generation OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 8

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source=pdf_text observed=2026-08-01T00:57:36.484539Z digest=sha256:09e45d1ebed79e4359bc21b1a983a7191e5fc3b045565e7cae7387e0d94d2b13

Observation e2f263a4-bb43-4cb8-86d2-22a1fde6549b · inbound

Can Text-to-Image Models Draw from the Right Frame of Reference? cites this paper.

Can Text-to-Image Models Draw from the Right Frame of Reference? OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 28

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no resolver link, observed 2026-08-15T14:59:46.927837Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:59:46.927837Z digest=sha256:1f2cd57c7a2063863772f503cc1d5eb1fa1aa817686cca17cbc171d7118c13b7

Observation 5cf963ea-b8d0-4ac6-86bd-d6810d7a49e3 · inbound

UniSpace: Unified Visual Representation and Scalable Multimodal Modeling cites this paper.

UniSpace: Unified Visual Representation and Scalable Multimodal Modeling OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 2021

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no resolver link, observed 2026-08-14T04:34:59.981913Z

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source=pdf_text observed=2026-08-14T04:34:59.981913Z digest=sha256:fc8f9668b4c45bc80fa28e295c11ec8baeebfbd43a4291b7dffbea055905c53a