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Paper Citation Record · LEDGER

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

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 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 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:29:14.789184Z

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

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-18T14:39:59.870039Z digest=sha256:bab0b96026f925a124b752a6d641d779b1154fcdc689b40b3b920e8a84d8da72

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-23T08:00:12.781392Z digest=sha256:f4a24f980527d0f526ad27f1e188fb958a6fd02ec29a6be177af42b77f1b3d20

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T16:24:27.407376Z digest=sha256:22a45f44867873960f23e2639ece5d69700472aa61935e969fe3f276dc38c015

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=sha256:22be70bdf30377e02c9a3929ac5e378e2d2ed801772b5efd83e5f3885dbb5c0f

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:ecf2e75aaebcde31d18efba87c262f064355e3472c9a336eb65e0196675dc19d

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=sha256:0d58a2c40f55eeb6c712c342234e1a03b0cf2754b9617fa8b3adce3e955ca8ad

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=sha256:381281e232512833e16bfb04556aa6d7d5f3209115f46c157c3187327afaafe3

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=sha256:26078d6270f6420aa8bb65edcc36cf5b48cc1661ff357e3f0c40c7a72e52b51c

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=sha256:965136c49ebf5015a1234b66585b7f041844f9b037567f54eaefcad532d9d5c9

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=sha256:3f54511d47ba161ae4274a8a8cdb3ad9e98e92df82404dd29e526aa4dcdabd2f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T05:29:42.024146Z digest=sha256:809a88474b24b787ba87d74e1d22d99fae94e722f0530b782747d631bcb1d63c

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=sha256:90d56b25e9b2a83c600ea4e4eb45a4789ffc7f931339db3d017396b7c7546bac

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T06:04:54.816368Z digest=sha256:1dd0badc347d0c3f633e0ee35d3fb543f2f61ee98e75cf9a091012c121bc7663

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:f0a3d173d6e328df3d89c8660b4ad5e263951a06de8f245b2ffa309620b16591

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=sha256:1933b2ced09ce6be641f3d96fd631171cb876f5ec71280eacb4983fa52d37da7