Skip to content
Log in
Sponsored Artificial Intelligence: A Modern Approach, Global Edition Artificial Intelligence: A Modern Approach, Global Edition
#artificial intelligence Dataset Open access

ATTRIBUTION AND ATTRIBUTIVE ANALYSIS OF ARTWORKS: A PRACTICAL, THEORETICAL, AND LEGAL GUIDE FOR MUSEUM RESEARCH STAFF

D. Nusratullaeva Worldly Knowledge Publishing Centre
Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

This article develops a practical, theoretical, methodological, and legal framework for the attribution and attributive analysis of artworks in museum collections. It preserves the core professional focus of museum attribution while reorganizing it into an IMRAD research structure and strengthening the relationship between connoisseurship, provenance research, technical examination, digital humanities, and museum documentation. The study is intended primarily for new and practicing research staff in museum art departments. Classical approaches associated with Giovanni Morelli, Heinrich Wölfflin, and Erwin Panofsky are considered alongside infrared and ultraviolet imaging, radiography, microscopy, spectroscopy, X-ray fluorescence, digital image analysis, and carefully bounded applications of artificial intelligence. Particular attention is given to provenance, evidentiary hierarchy, legal due diligence, and the scientific passport of a museum object. The legal context is discussed with reference to the Law of the Republic of Uzbekistan “On Museums,” the ICOM Code of Ethics for Museums, and the UNESCO 1970 Convention. As a principal result, a five-stage integrated attribution protocol is proposed: preliminary documentation and provenance screening; visual-stylistic and iconographic analysis; technical and material examination; digital/computational assistance; and collegial synthesis with formal documentation. An illustrative training case based on a Fergana Valley painting is used to demonstrate how a museum researcher should distinguish hypotheses from verified evidence.

DOI
View source

Similar papers

#artificial intelligence Open access May 2023

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations of such models.

Xiaotian Zhang, Chun-yan Li, Yi Zong et al. · 216 citations · ⚡17
#artificial intelligence Open access Jul 2024

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.

Kyra Wilson, Aylin Caliskan · 131 citations · ⚡8
#artificial intelligence Feb 2025

PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection

Empirically, PRISM reduces the end-to-end time for data selection and model tuning to just 30% of conventional pipelines, and achieves this efficiency while simultaneously enhancing performance, surpassing models fine-tuned on the full dataset across eight multimodal and three language understanding benchmarks.

Jinhe Bi, Yifan Wang, Danqi Yan et al. · 73 citations · ⚡4
#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6
#artificial intelligence May 2023

Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets

This paper designs Markov decision processes (MDPs) for different combinatorial problems and proposes to train conditional GFlowNets to sample from the solution space and demonstrates that GFlowNet policies can efficiently find high-quality solutions.

Dinghuai Zhang, H. Dai, Esmeralda S. Whitammer et al. · 59 citations · ⚡8
#artificial intelligence Review Mar 2025

A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives

A comprehensive survey of the leading simulation environments and platforms used for multi-agent cooperative decision-making and an in-depth analysis for these simulation environments from various perspectives, including task formats, reward allocation, and the underlying technologies employed.

Weiqiang Jin, Hong-Yang Du, Biao Zhao et al. · 57 citations · ⚡6

Related blog posts

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.