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Paper Citation Record · LEDGER

Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2406.07546.

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

pith.paper-citation-record.v1
2406.07546 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:21:03.809359Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:09:50.423322Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 54752231-047b-4069-be2e-242b0b1df1de · inbound

Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation cites this paper.

Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-18T14:40:00.094694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-18T14:39:59.870039Z digest=sha256:84becdfb1bab7cb256d1b9002ac313b143da480fc4a00f6fe8001d7f8cc91d6d

Observation afdcc556-0802-4452-b94d-39fe4267e5f9 · 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 Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-23T08:02:43.281911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-23T08:00:12.781392Z digest=sha256:4f5b29b8c74014ea10713bd19cd794a8ebe9d4b3814d4043a30d56b6e77a2d5f

Observation 03ca60db-6b29-4640-8767-d6f46c6a8f6e · inbound

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

EvalGIM: A Library for Evaluating Generative Image Models Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T15:50:16.662639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:50:16.662639Z digest=sha256:1244e02de382074842b1e5393c5e5be32782023b67dffbe3b04db1b4d7a09f15

Observation adf6ea4b-8d45-4b8b-85df-de20ad9611e0 · 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 Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-15T16:24:27.579185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-15T16:24:27.407376Z digest=sha256:f0a675ebce94e318059397c4768e1edb2fec5f1caed7af4416dbabd844249a55

Observation c8b11c57-6ead-4fab-aef7-2da2874d5f5c · inbound

WorldGenBench: A World-Knowledge-Integrated Benchmark for Reasoning-Driven Text-to-Image Generation cites this paper.

WorldGenBench: A World-Knowledge-Integrated Benchmark for Reasoning-Driven Text-to-Image Generation Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:03.809359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:21:03.809359Z digest=sha256:814403f12d8fda42e02f23d2f72474a7960a9601cc47271717b73fd6bd5a6b5a

Observation 0fdaa2c4-798b-47ef-989e-0baa7be44b3c · 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 Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-16T01:02:21.651121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T01:02:21.651121Z digest=sha256:1ca3f3b91c2bc13c7fc7a5b65d5cc2b17d7526693259ec463ec7d6fe56f78bf8

Observation cc46d3a9-9e75-4f0f-83e2-6b198eacd0d1 · 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 Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 8

Resolution
unresolved
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 9b784e3f-2441-487a-a237-cf01ea15bdca · 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 Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:32.854514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:32.854514Z digest=sha256:f8cb468949c552c0c362ca01c16f0ed3f280234b06a77c2f93d5a6fefae015a0

Observation 2a1e1bb1-ba1a-4820-90c6-e681d26cbd59 · inbound

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

R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T12:48:50.711956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:48:50.711956Z digest=sha256:5675458dea4a9b847f205cf94fdf4bbfa911a2e50b398c0a5aa40b5fd96c1521

Observation 5042c595-d8b2-4957-8d6e-e989a06c2c7b · inbound

GenSpace: Benchmarking Spatially-Aware Image Generation cites this paper.

GenSpace: Benchmarking Spatially-Aware Image Generation Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:21.501770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:21.501770Z digest=sha256:8911a50a0ede315e89e15465993ac56c2cb0380dd09a6d3bac405034408a0bd2

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

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

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

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T05:25:44.095229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:25:44.095229Z digest=sha256:2d977b95fa097bad9acf0848a75cfc88c794d614794a7e347d65a7d636ce41c7

Observation ba2461e4-cd1c-4b4a-9292-c133b1004b66 · inbound

AIGI-Holmes: Towards Explainable and Generalizable AI-Generated Image Detection via Multimodal Large Language Models cites this paper.

AIGI-Holmes: Towards Explainable and Generalizable AI-Generated Image Detection via Multimodal Large Language Models Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T20:32:59.658017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:32:59.658017Z digest=sha256:9739950e90a011b0bddda928dbe36d4d3a1fbe175d2bc7bb74ed73b90620891a

Observation 66c32426-e674-488e-8e1d-aaad6cc0f225 · 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 Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-04T18:48:03.655845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:48:03.655845Z digest=sha256:58821cbddd1606869bfd7cff0f38c40ae32e75b64ea53c9f14bb24ee41a8d7d7

Observation eb48bd77-e076-41ca-a7fe-926222af3742 · inbound

Do Image Editing Models Understand Lighting? cites this paper.

Do Image Editing Models Understand Lighting? Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:09:50.425449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-26T05:29:42.024146Z digest=sha256:1c24d4ade79caaeb0c61ffbf2583a2f6908778ac398969d6ff434655eab8437d

Observation 9bee8750-2446-469c-90c2-3cc1218ad00e · inbound

Do Image Editing Models Understand Lighting? cites this paper.

Do Image Editing Models Understand Lighting? Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-02T10:10:09.175457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T10:10:09.175457Z digest=sha256:a53e4033e8cfb7ff885b59678e8c456d77e91a8f0a4de68ae8497f84d0281a58

Observation 611ce9ff-7846-466d-a374-78755633f1e1 · inbound

Intermediate Text Representation Guided Text-to-Image Generation for Enhancing One-and-Only Alignment cites this paper.

Intermediate Text Representation Guided Text-to-Image Generation for Enhancing One-and-Only Alignment Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:24:27.106668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-30T06:04:54.816368Z digest=sha256:3f1500337f612752df90b7fd461880eae78a9315d65279048b18f2310e15fb39

Observation 64f394f1-01c4-4210-9b78-a5196d16eef7 · inbound

OmniPhys: Knowledge-Graph-Driven Benchmarking and Collective Optimization for Physical Commonsense in Text-to-Image Generation cites this paper.

OmniPhys: Knowledge-Graph-Driven Benchmarking and Collective Optimization for Physical Commonsense in Text-to-Image Generation Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-01T01:54:37.826437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T01:54:37.826437Z digest=sha256:17d1467f4126c79fa55a122aae477c1caa05b03095dc81f5de0c2e4138f88bfc

Observation b8e6eff9-412a-43a9-9940-376db9b11c24 · inbound

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

ToolArtist: Tool-Using Unified Multimodal Models for Agentic Image Generation Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T00:15:38.364743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:15:38.364743Z digest=sha256:872555a88e0b176becd20e52cce983c5648f8d4a8decd432f0aa2d0f50cf4844