Paper Citation Record · LEDGER

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements

As of 9 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 2 inbound Pith citation observations for arXiv:2502.04353.

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

pith.paper-citation-record.v1
2502.04353 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:51:34.791112Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:17:53.604403Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

38 of 38 outbound references displayed

verified exact1
verified fuzzy33
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation d7e72b83-1e3f-44fc-b530-6f2313475972 · outbound

This paper cites Unveiling the evolution of generative ai (gai): a comprehensive and investiga- tive analysis toward llm models (2021–2024) and beyond.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Unveiling the evolution of generative ai (gai): a comprehensive and investiga- tive analysis toward llm models (2021–2024) and beyond

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.214226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f8f8e487-b88d-48ee-98b4-e865f89f7f71 · outbound

This paper cites Latent dirichlet allocation.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Latent dirichlet allocation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.183546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d15f1c23-6a75-4edf-b68f-e7f41db6d66c · outbound

This paper cites A deep learning approach to clustering visual arts.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements A deep learning approach to clustering visual arts

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.154277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fe82269f-729d-4147-aff5-6816a9d3f125 · outbound

This paper cites Lever- aging knowledge graphs and deep learning for automatic art analysis.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Lever- aging knowledge graphs and deep learning for automatic art analysis

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.144270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d0cc2eb8-2826-42dd-b288-4d4ba2411b65 · outbound

This paper cites Under- standing and creating art with ai: Review and outlook.ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 18(2):1–22,.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Under- standing and creating art with ai: Review and outlook.ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 18(2):1–22,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.133676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6d4e119b-41d5-4f0a-ad08-edc702b2d054 · outbound

This paper cites A deep learning perspective on beauty, sentiment, and remembrance of art.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements A deep learning perspective on beauty, sentiment, and remembrance of art

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.122315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 285f58c2-822b-4e46-823e-9b561ef4340a · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Imagenet: A large-scale hierarchical image database

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.102337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6856a12e-086c-471b-b1bf-65561ead8ee7 · outbound

This paper cites A Neural Algorithm of Artistic Style.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements A Neural Algorithm of Artistic Style

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T11:51:34.712317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c753eb4f-4546-44d1-9464-a74e112ba613 · outbound

This paper cites Elements of Art: Ten Ways to Decode the Masterpieces.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Elements of Art: Ten Ways to Decode the Masterpieces

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.060899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 639dd25a-408d-4d25-97a4-8e6bf711d356 · outbound

This paper cites Artistic style recognition: Combining deep and shallow neural networks for painting classification.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Artistic style recognition: Combining deep and shallow neural networks for painting classification

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.049826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation dd5aec93-629e-409e-ab6d-f35c6910360c · outbound

This paper cites Neural style transfer: A review.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Neural style transfer: A review

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.038903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 676744de-5076-4646-aa52-b167112d7604 · outbound

This paper cites Photo aesthetics ranking network with attributes and content adaptation.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Photo aesthetics ranking network with attributes and content adaptation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.029187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c295bae2-da06-4b86-9005-7964a327effd · outbound

This paper cites NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T11:51:34.735946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2515f105-5dc7-44f0-acb9-c7be48d6f4df · outbound

This paper cites Visual instruction tuning.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Visual instruction tuning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.009547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d0b22d3c-2c91-4e0e-b66f-4e2ce17353d2 · outbound

This paper cites The rijksmuseum challenge: Museum- centered visual recognition.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements The rijksmuseum challenge: Museum- centered visual recognition

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.999842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 57034824-b9ca-4993-bfdb-ccc159cbe706 · outbound

This paper cites Ava: A large-scale database for aesthetic visual analysis.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Ava: A large-scale database for aesthetic visual analysis

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.979183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b8d53d57-e745-4375-a927-a6a09a7348a7 · outbound

This paper cites Learning transferable visual models from natural lan- guage supervision.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Learning transferable visual models from natural lan- guage supervision

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.968519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e8ee79f5-92bc-4775-a797-227e7fa80244 · outbound

This paper cites Sentence-bert: Sentence embeddings using siamese bert-networks.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Sentence-bert: Sentence embeddings using siamese bert-networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.947460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c1a6b904-9b9b-429f-a4e0-d0fa58a8da76 · outbound

This paper cites Graphclip: Image-graph contrastive learning for multimodal artwork classification.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Graphclip: Image-graph contrastive learning for multimodal artwork classification

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.936767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2edc190d-570f-4b26-8d1d-de6feaeed23b · outbound

This paper cites Omniart: a large-scale artistic benchmark.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Omniart: a large-scale artistic benchmark

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.914683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f19ee316-93b5-48f7-9214-197348afb611 · outbound

This paper cites What does a visual formal analysis of the world’s 500 most famous paintings tell us about multimodal llms? In The Second Tiny Papers Track at ICLR 2024,.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements What does a visual formal analysis of the world’s 500 most famous paintings tell us about multimodal llms? In The Second Tiny Papers Track at ICLR 2024,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.903311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 39f2e09b-dfbf-406b-96a1-dca181d40f8b · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Gemini: A Family of Highly Capable Multimodal Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-09T11:51:34.780489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58a26fe5-17bf-43cf-9dbd-0f515729e226 · outbound

This paper cites an unresolved cited work.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:51:34.880696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 54f725c3-ee10-4e02-a258-b460c9e2f43e · outbound

This paper cites Due to the interactive nature of the data visualizations, these figures are also available online at https://cognartive.github.io/.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Due to the interactive nature of the data visualizations, these figures are also available online at https://cognartive.github.io/

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.869359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ddb4b199-8e67-4627-8923-f98ecee30767 · outbound

This paper cites Language models are few-shot learners.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Language models are few-shot learners

Reference 2003

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.173736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f79751fa-557f-4995-813b-34314b6d4ea0 · outbound

This paper cites The shape of art history in the eyes of the machine.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements The shape of art history in the eyes of the machine

Reference 2009

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.092098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a7f9756a-ab46-4580-a516-23fc83b780ac · outbound

This paper cites Towards Cross-Lingual Explanation of Artwork in Large-scale Vision Language Models.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Towards Cross-Lingual Explanation of Artwork in Large-scale Vision Language Models

Reference 2012

Resolution: verified exact; local_arxiv, observed 2026-08-09T11:51:34.838146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7fd5fe4d-56d8-4409-a7d9-e99eddd4616b · outbound

This paper cites M3-embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements M3-embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation

Reference 2014

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.989780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c7685c40-7c39-479c-ad72-0aa4649d5ad7 · outbound

This paper cites Towards artwork explanation in large-scale vision language models.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Towards artwork explanation in large-scale vision language models

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.071755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2d7ce978-4f7c-4f73-b129-1c40b60c712c · outbound

This paper cites Large language models (llms): survey, technical frameworks, and future challenges.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Large language models (llms): survey, technical frameworks, and future challenges

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.019444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4db0944f-e9ae-4d0c-aad4-e7754d9b627b · outbound

This paper cites How to read paintings: semantic art understanding with multi-modal retrieval.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements How to read paintings: semantic art understanding with multi-modal retrieval

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.082163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1d16b133-438e-48e5-b6a5-27cbf0c3ff31 · outbound

This paper cites Culturai: Exploring mixed reality art exhibitions with large language models for personalized immersive experiences.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Culturai: Exploring mixed reality art exhibitions with large language models for personalized immersive experiences

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.112531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e31a5daf-b4e8-459d-9903-042534d0812d · outbound

This paper cites Optimizing style recognition algorithm for digital art images using large language models (llms).

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Optimizing style recognition algorithm for digital art images using large language models (llms)

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.164002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0d365048-bf7f-4096-a8f4-8812f89b9f38 · outbound

This paper cites Dall-e: Creating images from text.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Dall-e: Creating images from text

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.958014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d70217e8-0220-4076-a0d6-37ca1e906cac · outbound

This paper cites Gallerygpt: Analyzing paintings with large multi- modal models.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Gallerygpt: Analyzing paintings with large multi- modal models

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.193551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 196efe97-6610-47df-964a-cfb320818707 · outbound

This paper cites Augmented SBERT: Data augmentation method for improving bi- encoders for pairwise sentence scoring tasks.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Augmented SBERT: Data augmentation method for improving bi- encoders for pairwise sentence scoring tasks

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.892190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 82dcacd3-7c80-4b41-a22a-896cd9318b84 · outbound

This paper cites Flamingo: a visual language model for few- shot learning.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Flamingo: a visual language model for few- shot learning

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:35.203511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ddeef9c9-3bfa-4dc5-be6b-215d9894cf83 · outbound

This paper cites Artpedia: A new visual-semantic dataset with visual and contextual sentences in the artistic domain.

CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements Artpedia: A new visual-semantic dataset with visual and contextual sentences in the artistic domain

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:51:34.926179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation fc2adfa3-f4e2-475a-8615-7ecb90e8cd3a · inbound

Speaking images. A novel framework for the automated self-description of artworks cites this paper.

Speaking images. A novel framework for the automated self-description of artworks CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T13:17:53.604403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9427a9c-cb33-47a1-82e5-1beeff38cc41 · inbound

MIRAGE: A Micro-Interaction Relational Architecture for Grounded Exploration in Multi-Figure Artworks cites this paper.

MIRAGE: A Micro-Interaction Relational Architecture for Grounded Exploration in Multi-Figure Artworks CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-08T23:14:22.740954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.