Ancient history relies on disciplines such as epigraphy, the study of ancient inscribed texts, for evidence of the recorded past. However, these texts, "inscriptions", are often damaged over the centuries, and illegible parts of the text must be restored by specialists, known as epigraphists. This work presents Pythia, the first ancient text restoration model that recovers missing characters from a damaged text input using deep neural networks. Its architecture is carefully designed to handle long-term context information, and deal efficiently with missing or corrupted character and word representations. To train it, we wrote a non-trivial pipeline to convert PHI, the largest digital corpus of ancient Greek inscriptions, to machine actionable text, which we call PHI-ML. On PHI-ML, Pythia's predictions achieve a 30.1% character error rate, compared to the 57.3% of human epigraphists. Moreover, in 73.5% of cases the ground-truth sequence was among the Top-20 hypotheses of Pythia, which effectively demonstrates the impact of this assistive method on the field of digital epigraphy, and sets the state-of-the-art in ancient text restoration.
Ancient Greek to Modern Greek Machine Translation: A Novel Benchmark and Fine-Tuning Experiments on LLMs and NMT Models
National and Kapodistrian University of Athens, Department of Informatics and Telecommunications（雅典国家和卡普迪斯特里亚大学信息与电信系）；Institute for Language and Speech Processing, Athena RC（语言与语音处理研究所，雅典RC）
VaseVQA: Multimodal Agent and Benchmark for Ancient Greek Pottery
University of Adelaide（阿德莱德大学）；University of Liverpool（利物浦大学）；University of Technology Sydney（悉尼技术大学）；The Australian National University（澳大利亚国立大学）；La Trobe University（拉特罗布大学）
Lexical semantic change for Ancient Greek and Latin
Amazon（亚马逊）；University of Gothenburg（哥德堡大学）；University of Oxford（牛津大学）；University of Warwick（华威大学）；The Alan Turing Institute（艾伦·图灵研究所）；University of Cambridge（剑桥大学）
GASC: Genre-Aware Semantic Change for Ancient Greek
Amazon（亚马逊）；University of Warwick（华威大学）；University of Helsinki（赫尔辛基大学）；University of Oxford（牛津大学）；The Alan Turing Institute（艾伦·图灵研究所）；University of Cambridge（剑桥大学）
Learning Diachronic Representations of Ancient Greek Letterforms
Athens University of Economics and Business（雅典经济与商业大学）；Archimedes, Athena Research Center（阿基米德，雅典娜研究中心）；Department of Computer and Systems Sciences, Stockholm University（斯德哥尔摩大学计算机与系统科学系）；Università degli Studi di Torino（都灵大学）；University of Basel（巴塞尔大学）；Democritus University of Thrace（德谟克利特大学）；Computer Vision Center (CVC) - Barcelona（巴塞罗那计算机视觉中心）；Julius-Maximilians-Universität Würzburg（维尔茨堡大学）
Evaluating LLM-Based Translation of a Low-Resource Technical Language: The Medical and Philosophical Greek of Galen
Department of Classical and Mediterranean Studies, Vanderbilt University（维斯尼尔大学古典与地中海研究系）；Center for Hellenic Studies, Harvard University（哈佛大学希腊研究中心）；Department of Philosophy, Vanderbilt University（维斯尼尔大学哲学系）；Machine Intelligence and Normative Theory (MINT) Lab, Australian National University（澳大利亚国立大学机器智能与规范理论实验室）；Department of the Classics, Harvard University（哈佛大学古典学系）
