Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T17:49:20.995464Z
Paper Citation Record · LEDGER
GeoLoom: High-quality Geometric Diagram Generation from Textual Input
As of 23 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2512.08180.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
27 of 27 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved27
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- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a2e13e56-0cad-4e2a-a589-7fd8f96c6487 · outbound
This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:09.868067Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 35468e35-5317-4f8f-ba4a-ab817f069fcb · outbound
This paper cites Deepsvg: A hierarchical generative network for vector graphics animation.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Deepsvg: A hierarchical generative network for vector graphics animation
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:10.308214Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 69e8546b-c599-48ec-9629-ebabbc24399e · outbound
This paper cites Geoqa: A geometric question answering benchmark towards multimodal numerical reason- ing.In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021,.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Geoqa: A geometric question answering benchmark towards multimodal numerical reason- ing.In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021,
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:10.584811Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5aa13fcd-a41a-45fa-af6e-cec0b0a87587 · outbound
This paper cites Seedream 3.0 Technical Report.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Seedream 3.0 Technical Report
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:11.095467Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc4ab651-e369-4c61-9d21-848fae57eabd · outbound
This paper cites The Llama 3 Herd of Models.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input The Llama 3 Herd of Models
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:11.281001Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8cbaf14d-58a5-4971-b0b9-a58207b66585 · outbound
This paper cites Scaling Autoregressive Models for Content-Rich Text-to-Image Generation.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Scaling Autoregressive Models for Content-Rich Text-to-Image Generation
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:11.421158Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 47e5f77b-e9f9-4248-9ca5-a15754513eca · outbound
This paper cites Scaling up gans for text-to-image synthesis.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Scaling up gans for text-to-image synthesis
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:11.604832Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 82693605-52dd-49eb-9436-2e8bfd40d697 · outbound
This paper cites Evaluating Text-to-Visual Generation with Image-to-Text Generation.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Evaluating Text-to-Visual Generation with Image-to-Text Generation
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:11.784837Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 550bdf8d-f718-45fd-8ef4-44b567099809 · outbound
This paper cites DeepSeek-V3 Technical Report.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input DeepSeek-V3 Technical Report
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:12.485684Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f755aef4-ef96-4965-8292-d4184b77e06d · outbound
This paper cites Generative Language Modeling for Automated Theorem Proving.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Generative Language Modeling for Automated Theorem Proving
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:19.404541Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 298e0411-b773-4635-8aab-77f0dfff2853 · outbound
This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Hierarchical Text-Conditional Image Generation with CLIP Latents
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:19.739807Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 81956c17-2130-4b34-869b-4c65d5c1a577 · outbound
This paper cites High resolution image synthesis with latent diffusion models.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input High resolution image synthesis with latent diffusion models
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:19.925525Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9b7e734b-91e0-4eb6-87e4-46f32e07eea3 · outbound
This paper cites Photorealistic text-to- image diffusion models with deep language understanding.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Photorealistic text-to- image diffusion models with deep language understanding
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:20.107000Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 447710af-044e-4e9b-9a19-5c59f66430c4 · outbound
This paper cites MagicGeo: Training-Free Text-Guided Geometric Diagram Generation.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input MagicGeo: Training-Free Text-Guided Geometric Diagram Generation
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:20.185462Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 92d8e054-3f1b-4d71-a4ff-3210a750b5e3 · outbound
This paper cites IconShop: Text-Guided Vector Icon Synthesis with Autoregressive Transformers.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input IconShop: Text-Guided Vector Icon Synthesis with Autoregressive Transformers
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:20.372299Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 381a9cad-219f-45b7-be22-ebc93576a275 · outbound
This paper cites Chat2SVG: Vector graphics generation with large language models and image diffusion models.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Chat2SVG: Vector graphics generation with large language models and image diffusion models
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:20.524330Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 177e5c00-b3ed-4b4f-b27b-ad74cd544fec · outbound
This paper cites SVGFusion: A VAE-Diffusion Transformer for Vector Graphic Generation.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input SVGFusion: A VAE-Diffusion Transformer for Vector Graphic Generation
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:20.658277Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fcc9972e-0b0e-4256-8831-234fe4d202cd · outbound
This paper cites Text-to-image Diffusion Models in Generative AI: A Survey.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Text-to-image Diffusion Models in Generative AI: A Survey
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:20.995464Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bc46f177-bac4-4791-982d-c93db6e3ab39 · outbound
This paper cites NeuralSVG: An Implicit Representation for Text-to-Vector Generation.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input NeuralSVG: An Implicit Representation for Text-to-Vector Generation
Reference 1949
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:19.145857Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d2dca44c-80cf-4cdd-8f17-0a6ab71f16ba · outbound
This paper cites Freeman, Michael Rubinstein, Yuanzhen Li, and Dilip Krishnan.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Freeman, Michael Rubinstein, Yuanzhen Li, and Dilip Krishnan
Reference 2001
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:10.514818Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7568c42-b2ed-4bd3-86f3-db580d22774f · outbound
This paper cites DiagrammerGPT: Generating Open-Domain, Open-Platform Diagrams via LLM Planning.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input DiagrammerGPT: Generating Open-Domain, Open-Platform Diagrams via LLM Planning
Reference 2015
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:20.831567Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4de6c1e3-f4d9-4497-97cd-edaa9fc4f648 · outbound
This paper cites Learning Transferable Visual Models From Natural Language Supervision.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Learning Transferable Visual Models From Natural Language Supervision
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:19.540209Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 17cb7e8e-5e10-4d2e-bb91-fe4315d584aa · outbound
This paper cites Unigeo: Unifying geometry logical reasoning via reformulating mathematical expression.In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pp.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Unigeo: Unifying geometry logical reasoning via reformulating mathematical expression.In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pp
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:10.667664Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49891995-2fa3-4d21-8d27-b10d43d0e54b · outbound
This paper cites Trinh, Miroslav Olˇs´ak, Xiao-Meng Yang, Hoang Nguyen, Marcelo Mene- gali, Junehyuk Jung, Vikas Verma, Quoc V.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Trinh, Miroslav Olˇs´ak, Xiao-Meng Yang, Hoang Nguyen, Marcelo Mene- gali, Junehyuk Jung, Vikas Verma, Quoc V
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:10.757231Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d02d6e5b-06b6-4d43-b5a3-984043931d6c · outbound
This paper cites AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:09.969284Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5d25640f-9558-48d8-9a42-aa4b5b289a6c · outbound
This paper cites Leveraging Large Language Models for Scalable Vector Graphics-Driven Image Understanding.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Leveraging Large Language Models for Scalable Vector Graphics-Driven Image Understanding
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:10.172206Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0793b62d-bb74-4a26-9b03-6a76902c0d76 · outbound
This paper cites Cogview: Mastering text-to-image generation via transformers.
GeoLoom: High-quality Geometric Diagram Generation from Textual Input Cogview: Mastering text-to-image generation via transformers
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:49:10.924471Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.