Word meanings change over time, and word senses evolve, emerge or die out in the process. For ancient languages, where the corpora are often small and sparse, modelling such changes accurately proves challenging, and quantifying uncertainty in sense-change estimates consequently becomes important. GASC (Genre-Aware Semantic Change) and DiSC (Diachronic Sense Change) are existing generative models that have been used to analyse sense change for target words from an ancient Greek text corpus, using unsupervised learning without the help of any pre-training. These models represent the senses of a given target word such as "kosmos" (meaning decoration, order or world) as distributions over context words, and sense prevalence as a distribution over senses. The models are fitted using Markov Chain Monte Carlo (MCMC) methods to measure temporal changes in these representations. This paper introduces EDiSC, an Embedded DiSC model, which combines word embeddings with DiSC to provide superior model performance. It is shown empirically that EDiSC offers improved predictive accuracy, ground-truth recovery and uncertainty quantification, as well as better sampling efficiency and scalability properties with MCMC methods. The challenges of fitting these models are also discussed.
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）
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）
