Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research

T Zhong, Z Yang, Z Liu, R Zhang, Y Liu, H Sun… - arxiv preprint arxiv …, 2024 - arxiv.org
Low-resource languages serve as invaluable repositories of human history, embodying
cultural evolution and intellectual diversity. Despite their significance, these languages face …

Explainability and transparency in the realm of digital humanities: toward a historian XAI

H El-Hajj, O Eberle, A Merklein, A Siebold… - International Journal of …, 2023 - Springer
The recent advancements in the field of Artificial Intelligence (AI) translated to an increased
adoption of AI technology in the humanities, which is often challenged by the limited amount …

LLMCO4MR: LLMs-Aided Neural Combinatorial Optimization for Ancient Manuscript Restoration from Fragments with Case Studies on Dunhuang

Y Zhang, H Li, S Zhang, R Wang, B He, H Dou… - … on Computer Vision, 2024 - Springer
Restoring ancient manuscripts fragments, such as those from Dunhuang, is crucial for
preserving human historical culture. However, their worldwide dispersal and the shifts in …

Reproducing the Past: A Dataset for Benchmarking Inscription Restoration

S Zhu, H Xue, N Nie, C Zhu, H Liu, P Fang - Proceedings of the 32nd …, 2024 - dl.acm.org
Inscriptions on ancient steles, as carriers of culture, encapsulate the humanistic thoughts
and aesthetic values of our ancestors. However, these relics often deteriorate due to …

A Systematic Review of Computational Approaches to Deciphering Bronze Age Aegean and Cypriot Scripts

M Braović, D Krstinić, M Štula, A Ivanda - Computational linguistics, 2024 - direct.mit.edu
This paper provides a detailed insight into computational approaches for deciphering
Bronze Age Aegean and Cypriot scripts, namely the Archanes script and the Archanes …

A novel masking model for Buddhist literature understanding by using Generative Adversarial Networks

C Yan, Y Wang, L Chang, Q Zhang, T He - Expert Systems with Applications, 2024 - Elsevier
This paper is focused on ancient Chinese Buddhist literature understanding. Buddhist
literature incorporates a plethora of dialects and slang, which makes it challenging to extract …

Deep Aramaic: Towards a synthetic data paradigm enabling machine learning in epigraphy

AC Aioanei, RR Hunziker-Rodewald, KM Klein… - Plos one, 2024 - journals.plos.org
Epigraphy is witnessing a growing integration of artificial intelligence, notably through its
subfield of machine learning (ML), especially in tasks like extracting insights from ancient …

The Artificial Papyrologist at Work

N Reggiani - Decoding Cultural Heritage: A Critical Dissection and …, 2024 - Springer
The chapter focuses on the recent advancements in Artificial Intelligence (AI) and Machine
Learning (ML) applications within papyrological research. These technologies have a …

Lacuna Language Learning: Leveraging RNNs for Ranked Text Completion in Digitized Coptic Manuscripts

L Levine, CT Li, L Bremer-McCollum, N Wagner… - arxiv preprint arxiv …, 2024 - arxiv.org
Ancient manuscripts are frequently damaged, containing gaps in the text known as lacunae.
In this paper, we present a bidirectional RNN model for character prediction of Coptic …

Multi-Modal Multi-Granularity Tokenizer for Chu Bamboo Slips

Y Chen, C Hu, C Feng, C Song, S Yu… - Proceedings of the …, 2025 - aclanthology.org
This study presents a multi-modal multi-granularity tokenizer specifically designed for
analyzing ancient Chinese scripts, focusing on the Chu bamboo slip (CBS) script used …