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Paper Citation Record · LEDGER

GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 59 inbound Pith citation observations for arXiv:2406.13743.

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

pith.paper-citation-record.v1
2406.13743 v3

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measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 59 of 59 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 59 of 59 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:35:43.571101Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-07T13:23:47.427719Z

Reference resolution

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Outbound references

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Pith citing papers

Observation fffa1bfe-1607-440d-97e7-b7bc8f092de5 · inbound

Detecting Human Artifacts from Text-to-Image Models cites this paper.

Detecting Human Artifacts from Text-to-Image Models GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 22

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Observation c00f906e-fc29-4576-8777-748cefb19812 · inbound

High-Resolution Image Synthesis via Next-Token Prediction cites this paper.

High-Resolution Image Synthesis via Next-Token Prediction GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 63

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Observation 376e513f-6908-436a-b939-e06b0f8971c1 · inbound

Appearance Matching Adapter for Exemplar-based Semantic Image Synthesis in-the-Wild cites this paper.

Appearance Matching Adapter for Exemplar-based Semantic Image Synthesis in-the-Wild GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 15

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Observation 009c486e-e436-413d-a1e7-b38533cac5f6 · inbound

T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts cites this paper.

T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 24

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Observation a6f06a76-e92b-4222-bda5-9dcebc36ae81 · inbound

EvalGIM: A Library for Evaluating Generative Image Models cites this paper.

EvalGIM: A Library for Evaluating Generative Image Models GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 34

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Observation cb6b0374-f776-4503-8711-0803822a4cb4 · inbound

EvalMuse-40K: A Reliable and Fine-Grained Benchmark with Comprehensive Human Annotations for Text-to-Image Generation Model Evaluation cites this paper.

EvalMuse-40K: A Reliable and Fine-Grained Benchmark with Comprehensive Human Annotations for Text-to-Image Generation Model Evaluation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 20

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Observation d5891fbb-79d0-44d8-be45-48376fc8b49d · inbound

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

WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 22

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Observation 9b2c457f-ebf4-44f0-8d14-8898f957bb99 · inbound

Token-Shuffle: Towards High-Resolution Image Generation with Autoregressive Models cites this paper.

Token-Shuffle: Towards High-Resolution Image Generation with Autoregressive Models GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 13

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Observation 031f252d-3a54-4090-9bf8-ff7c55b0c9b9 · inbound

Multi-Modal Language Models as Text-to-Image Model Evaluators cites this paper.

Multi-Modal Language Models as Text-to-Image Model Evaluators GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 32

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Observation fa7aeb7f-a96e-4b26-ba40-5ed73e0c247c · inbound

Improving Physical Object State Representation in Text-to-Image Generative Systems cites this paper.

Improving Physical Object State Representation in Text-to-Image Generative Systems GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 12

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Observation 81838fe5-29bc-4b25-8eb6-c8fbb5e161c5 · inbound

PiCo: Enhancing Text-Image Alignment with Improved Noise Selection and Precise Mask Control in Diffusion Models cites this paper.

PiCo: Enhancing Text-Image Alignment with Improved Noise Selection and Precise Mask Control in Diffusion Models GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 25

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Observation 712bbeb4-4630-4507-975e-d301c26d874b · inbound

Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models cites this paper.

Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 233

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Observation a8ab0b5e-2c44-4626-a456-6b8df16829bd · inbound

NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment cites this paper.

NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 25

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

Align Beyond Prompts: Evaluating World Knowledge Alignment in Text-to-Image Generation cites this paper.

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 a6d82efc-93f1-4e0a-9be3-468e66cde8ea · inbound

MMIG-Bench: Towards Comprehensive and Explainable Evaluation of Multi-Modal Image Generation Models cites this paper.

MMIG-Bench: Towards Comprehensive and Explainable Evaluation of Multi-Modal Image Generation Models GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 28

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Observation 836d8399-db45-4cb3-84f0-0bbc4b029464 · inbound

R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation cites this paper.

R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 22

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

OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation cites this paper.

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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Observation 4093adbf-4e7f-4333-9802-e5abbf15e686 · inbound

A Comprehensive Study of Decoder-Only LLMs for Text-to-Image Generation cites this paper.

A Comprehensive Study of Decoder-Only LLMs for Text-to-Image Generation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 30

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Observation c609c333-7627-4635-9bbd-fa9e148f5191 · inbound

FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model Evaluation cites this paper.

FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model Evaluation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 29

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Observation a7b6832e-462a-4b40-b691-402e80d01c12 · inbound

FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space cites this paper.

FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 28

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AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation cites this paper.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 28

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Observation 00571947-fd5a-4889-aa9f-1a4e481338b5 · inbound

4KAgent: Agentic Any Image to 4K Super-Resolution cites this paper.

4KAgent: Agentic Any Image to 4K Super-Resolution GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 101

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Observation dc4ce276-d8bb-4f72-b948-675d50d021df · inbound

Towards Effective Human-in-the-Loop Assistive AI Agents cites this paper.

Towards Effective Human-in-the-Loop Assistive AI Agents GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 10

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Trade-offs in Image Generation: How Do Different Dimensions Interact? cites this paper.

Trade-offs in Image Generation: How Do Different Dimensions Interact? GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 35

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Observation d33fa69b-7a28-4909-9114-fbebdc2da3be · inbound

Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generation cites this paper.

Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 37

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Observation 1b15b544-8055-4470-8502-c0d2b6fc4c0a · inbound

Reusing Computation in Text-to-Image Diffusion for Efficient Generation of Image Sets cites this paper.

Reusing Computation in Text-to-Image Diffusion for Efficient Generation of Image Sets GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 15

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Observation 817fe4d2-c078-4b26-b7d9-ae1f0aec9d92 · inbound

FLUX-Reason-6M & PRISM-Bench: A Million-Scale Text-to-Image Reasoning Dataset and Comprehensive Benchmark cites this paper.

FLUX-Reason-6M & PRISM-Bench: A Million-Scale Text-to-Image Reasoning Dataset and Comprehensive Benchmark GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 37

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Observation 9e2288a9-e8a4-4b19-85a0-1741d6505915 · inbound

Early Estimation of Language to Latent Alignment in Diffusion Models cites this paper.

Early Estimation of Language to Latent Alignment in Diffusion Models GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 24

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Observation c3bcdb40-25d5-437a-b8f1-11cddfe3a4ac · inbound

Efficient Adversarial Attacks on High-dimensional Offline Bandits cites this paper.

Efficient Adversarial Attacks on High-dimensional Offline Bandits GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 2015

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Observation c3ab40fd-af2a-469c-ae65-5e2b8f8c5654 · inbound

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation cites this paper.

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 60

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Observation 69cea2fc-8951-494a-8d96-e5548f0ecd28 · inbound

Exploring the AI Obedience: Why is Generating a Pure Color Image Harder than CyberPunk? cites this paper.

Exploring the AI Obedience: Why is Generating a Pure Color Image Harder than CyberPunk? GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 9

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arxiv_id, observed 2026-05-15T19:16:31.468959Z

Source-reported events for the cited work

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Observation 13c95945-8010-4ad6-914c-d1fcba15056e · inbound

On Semiotic-Grounded Interpretive Evaluation of Generative Art cites this paper.

On Semiotic-Grounded Interpretive Evaluation of Generative Art GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 53

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Observation 6a32781a-b527-43d7-82f3-65dbd40bec98 · inbound

HumanScore: Benchmarking Human Motions in Generated Videos cites this paper.

HumanScore: Benchmarking Human Motions in Generated Videos GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 28

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arxiv_id, observed 2026-05-11T13:41:04.347648Z

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Observation 32463b92-e760-475d-8085-4653538e6cd4 · inbound

Image Generators are Generalist Vision Learners cites this paper.

Image Generators are Generalist Vision Learners GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 15

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arxiv_id, observed 2026-05-11T13:41:06.134499Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 283e7cd2-6d6d-429e-8925-a71eca6cf748 · inbound

Image Generators are Generalist Vision Learners cites this paper.

Image Generators are Generalist Vision Learners GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:45:14.691380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-15T07:40:46.090808Z digest=sha256:da794742019e2f0fd2b76ba7ab479cb74471c25fcb5397a48c4299d1763724ba

Observation 83bbd6d8-da19-4878-aff4-eb58cfb26284 · inbound

DynT2I-Eval: A Dynamic Evaluation Framework for Text-to-Image Models cites this paper.

DynT2I-Eval: A Dynamic Evaluation Framework for Text-to-Image Models GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:46:10.544499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T13:54:00.141439Z digest=sha256:97668b0b5f3913317cc9595365136e20e9028f861c085d730ccb54b3af317711

Observation 90f61cbc-c0ed-42e3-8c56-36e56bd61672 · inbound

Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling cites this paper.

Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-14T20:22:54.501735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-14T20:22:20.464966Z digest=sha256:9cefd199f7bb8398698dcee28cdd7b28b94cf23768362a5c534e83d6e7373034

Observation 5db012ac-f001-4fc2-9543-e58e5fff7793 · inbound

Few Channels Draw The Whole Picture: Revealing Massive Activations in Diffusion Transformers cites this paper.

Few Channels Draw The Whole Picture: Revealing Massive Activations in Diffusion Transformers GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-15T05:59:48.815652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-15T05:58:55.640862Z digest=sha256:3ae5f335e6465eb36ecd487f58e20e79c7762b465bf82eb9444fe208c2422f7b

Observation f4129ff1-c1a0-43b1-9001-6706b1fb21a9 · inbound

Few Channels Draw The Whole Picture: Revealing Massive Activations in Diffusion Transformers cites this paper.

Few Channels Draw The Whole Picture: Revealing Massive Activations in Diffusion Transformers GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 21

Resolution
unresolved
no resolver link, observed 2026-07-12T16:52:22.264276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T16:52:22.264276Z digest=sha256:f5eefda8333367ae34b7eb9fbca15eb33ed4907032474ee3efaff4150acd7d65

Observation 526d8ec4-e8c5-4d8e-ac59-387d73ae046d · inbound

AutoRubric-T2I: Robust Rule-Based Reward Model for Text-to-Image Alignment cites this paper.

AutoRubric-T2I: Robust Rule-Based Reward Model for Text-to-Image Alignment GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-20T12:13:16.139717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T12:11:23.775843Z digest=sha256:beed09d02de79250edf306ab22eea38610a9093c9b54e08b8a57529cc6873d4a

Observation ab9d56a3-38b7-4d84-8e9d-cb1af0d9c4db · inbound

AutoRubric-T2I: Robust Rule-Based Reward Model for Text-to-Image Alignment cites this paper.

AutoRubric-T2I: Robust Rule-Based Reward Model for Text-to-Image Alignment GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-22T09:21:21.381629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T09:19:39.848194Z digest=sha256:c70ea2441b1b9f852369a1679630b3a9bb800f5b6cd98b1a3ad322e4887e944e

Observation 1bf4a8e9-f5d5-495c-b01a-abb200617bf5 · inbound

Improved Baselines with Representation Autoencoders cites this paper.

Improved Baselines with Representation Autoencoders GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:43:15.287042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T11:40:14.358108Z digest=sha256:ec9f1424d33599a0fda134c86acfa5bd6253810693223468531538293e42f88d

Observation 6847c576-9c14-42e9-b9f4-4a121e927b81 · inbound

FAGER: Factually Grounded Evaluation and Refinement of Text-to-Image Models cites this paper.

FAGER: Factually Grounded Evaluation and Refinement of Text-to-Image Models GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-20T10:43:12.583779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T10:40:37.777253Z digest=sha256:1d1fc86bd14aebafe26e8336171e6c297a312381b7973bc4d5e2e756cd90d619

Observation eae3f1c9-55fd-4969-bed2-cc8b7662be54 · inbound

Qwen-Image-Bench: From Generation to Creation in Text-to-Image Evaluation cites this paper.

Qwen-Image-Bench: From Generation to Creation in Text-to-Image Evaluation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T14:13:30.367898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-29T14:05:25.988619Z digest=sha256:d42eaa06487b52762d9a05beba844cd48e130230c6a5458c512ec8712e3103a6

Observation 75bb3396-436e-428e-a6d6-399bf5c2bf4e · inbound

Balancing Performance and Diversity in GRPO Autoregressive Text-to-Image Post-Training cites this paper.

Balancing Performance and Diversity in GRPO Autoregressive Text-to-Image Post-Training GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-04T06:49:37.323604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-26T14:14:45.547957Z digest=sha256:a3d7dc142e45c976cac9ae4703f3bb81e5944d1db1ecf51c2b7c1f03b52881d6

Observation 35627ccb-01a3-4d97-8f7c-af6743445c11 · inbound

DiffusionBench: On Holistic Evaluation of Diffusion Transformers cites this paper.

DiffusionBench: On Holistic Evaluation of Diffusion Transformers GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 163

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T16:59:58.175350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-26T00:06:11.951205Z digest=sha256:068792ffdc497cf57e63aba2a951d52f901d02b848df0345e7a1dff8d17a2aa8

Observation 04b7e5aa-3c6e-4917-ac17-8378278fc930 · inbound

Do Image Editing Models Understand Lighting? cites this paper.

Do Image Editing Models Understand Lighting? GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:09:50.457779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-26T05:29:42.024146Z digest=sha256:46412e001e00f796e6f4f1b79056a1573c7682adbb87c986fd9002c19b031b3d

Observation b743acc6-2c6b-4af4-b431-f86c2087cd54 · inbound

Do Image Editing Models Understand Lighting? cites this paper.

Do Image Editing Models Understand Lighting? GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-02T10:10:09.220449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T10:10:09.220449Z digest=sha256:e62bc745c5a1387f827884c56e4c615ff8271331ac739a842da0e96701a94540

Observation bf99cfa5-c3d5-4670-a33c-09f9076753aa · inbound

KathaTrace: Diagnosing Semantic Trajectory Collapse in Generated Visual Narratives cites this paper.

KathaTrace: Diagnosing Semantic Trajectory Collapse in Generated Visual Narratives GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-03T21:18:58.049200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-03T21:14:13.641041Z digest=sha256:d27c9db07d8d96788c2fd5531840f85a0149cb7060af2ac59ebba27013a5cb0f

Observation 0baa27bf-ac84-4a85-af00-b16d21e2ff83 · inbound

Flash-BoN: Instant Drafts for Inference-Time Scaling in Diffusion Models cites this paper.

Flash-BoN: Instant Drafts for Inference-Time Scaling in Diffusion Models GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-07-11T18:59:01.561509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T18:59:01.561509Z digest=sha256:176c21240f3bd1ffc4843c11bfaf69ce9745367600efab400180f2bc1742b58d

Observation 59690c0c-82df-4b81-b191-5f0036796de7 · inbound

Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation cites this paper.

Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-07-07T13:23:47.429438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-07T13:18:50.793715Z digest=sha256:1eb335034dd6a42333f4ec72686cdc699d8145502b18b703cd68f0dc184236de

Observation e0e78e7b-7a1f-4c7a-9805-803dd4e3f3dd · inbound

Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation cites this paper.

Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 32

Resolution
unresolved
no resolver link, observed 2026-07-11T07:09:39.972776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T07:09:39.972776Z digest=sha256:873fb68db195577ef1f22a58bdecd1da12475b18c87b0bfa581296c6ecedb8ae

Observation 978a0430-c666-4568-b00c-89b57bb9aab0 · inbound

VGIF-Score: Interpretable and Diagnostic Evaluation of Spatio-Temporal Instruction Following in Video Generation cites this paper.

VGIF-Score: Interpretable and Diagnostic Evaluation of Spatio-Temporal Instruction Following in Video Generation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-02T04:57:34.799559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T04:57:34.799559Z digest=sha256:d39975d3d048a4c1e94665a81ff3231d67ab7d36405874e59a3ef42b6067c4a5

Observation 61260bf7-9534-4614-98bc-bd70f4d3562e · inbound

Show, Don't Tell: Evaluating Spatial Cognition in Generative Pixels Rather Than LLM Text cites this paper.

Show, Don't Tell: Evaluating Spatial Cognition in Generative Pixels Rather Than LLM Text GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-01T08:39:38.560857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T08:39:38.560857Z digest=sha256:3ea3c85a156db5154e12773512ddba0bd6e79f070bad03567f30b45c3e951b83

Observation 2754443a-4a4a-4a44-964a-a8ae94568356 · inbound

HALLELUAI: A Hallucination-Aware AI System for Ultra-Realistic Image-to-Video Generation at Scale cites this paper.

HALLELUAI: A Hallucination-Aware AI System for Ultra-Realistic Image-to-Video Generation at Scale GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-01T04:06:00.179125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T04:06:00.179125Z digest=sha256:8c2d947ae227079626b4d86fd0557fdccd337fe9214439f80fb0967bfa08f68e

Observation 12c620fe-5572-4908-bec4-40a4bd5cc03a · inbound

Latent Reward Registers for Diffusion Preference Alignment cites this paper.

Latent Reward Registers for Diffusion Preference Alignment GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T05:39:05.547200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:39:05.547200Z digest=sha256:5e1cdf2dfc6671b087a0039363332abe56e5fd1d4873b3d6b5abdb139d6dd2bb

Observation a90f5d99-d73b-4f90-bc75-21e879e8384e · inbound

Latent Reward Registers for Diffusion Preference Alignment cites this paper.

Latent Reward Registers for Diffusion Preference Alignment GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-08T00:41:15.241468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:41:15.241468Z digest=sha256:bfa54503d2c580ba11da9a0bcea72e1195ab03a1ffe07cbf13fc17e206e2268a

Observation 646c45fc-7f83-48dc-8b61-75e135b1c6d2 · inbound

Sci-VBench: Evaluating Knowledge- and Reasoning-Intensive Video Generation in Science Domains cites this paper.

Sci-VBench: Evaluating Knowledge- and Reasoning-Intensive Video Generation in Science Domains GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T05:13:22.316438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:13:22.316438Z digest=sha256:c645ceb7c274687464235b52826acdf7e67ee5f7e21ef4f676689b976bd48118

Observation c022f01b-7d78-42ed-9a41-f369b05b03fe · inbound

TangPoetryBench: A Multi-Dimensional Benchmark and Rubric-Conditioned Evaluator for Poetry-to-Image Generation cites this paper.

TangPoetryBench: A Multi-Dimensional Benchmark and Rubric-Conditioned Evaluator for Poetry-to-Image Generation GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-15T14:17:50.700719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:17:50.700719Z digest=sha256:6b2cc393eb790aaa1ce7eab9924898e2e43d0c9a2982f8930be139f4a9893616