Historical Dynamics of Lexical System as Random Walk Process
Victor Kromer
提出将词义历时变化看作是带有反射屏和吞噬屏的连续随机游动。定义了词生存周期的基本特征。用不同年龄段的俄语词汇分布数据对模型进行了验证。
It is offered to consider word meanings changes in diachrony as semicontinuous random walk with reflecting and swallowing screens. The basic characteristics of word life cycle are defined. Verification of the model has been realized on the data of Russian words distribution on various age periods.
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We present RuSemShift, a large-scale manually annotated test set for the task of semantic change modeling in Russian for two long-term time period pairs: from the pre-Soviet through the Soviet times and from the Soviet through the post-Soviet times. Target words were annotated by multiple crowd-source workers. The annotation process was organized following the DURel framework and was based on sentence contexts extracted from the Russian National Corpus. Additionally, we report the performance of several distributional approaches on RuSemShift, achieving promising results, which at the same tim…
The National Library of Finland has digitized the historical newspapers published in Finland between 1771 and 1910. This collection contains approximately 1.95 million pages in Finnish and Swedish. Finnish part of the collection consists of about 2.40 billion words. The National Library's Digital Collections are offered via the digi.kansalliskirjasto.fi web service, also known as Digi. Part of the newspaper material (from 1771 to 1874) is also available freely downloadable in The Language Bank of Finland provided by the FINCLARIN consortium. The collection can also be accessed through the Korp…
Talking the Talk Does Not Entail Walking the Walk: On the Limits of Large Language Models in Lexical Entailment Recognition
本研究评估八种大型语言模型在词汇蕴含识别中的表现，发现其性能中等且少样本提示可提升效果，但完美解决仍具挑战，凸显进一步研究需求。
Contextualized word embeddings have demonstrated state-of-the-art performance in various natural language processing tasks including those that concern historical semantic change. However, language models such as BERT was trained primarily on contemporary corpus data. To investigate whether training on historical corpus data improves diachronic semantic analysis, we present a pre-trained BERT-based language model, HistBERT, trained on the balanced Corpus of Historical American English. We examine the effectiveness of our approach by comparing the performance of the original BERT and that of Hi…
Neural Recovery of Historical Lexical Structure in Bantu Languages from Modern Data
研究神经模型是否能从现代形态数据中恢复跨语言词汇结构，发现13个 productive classes 在班图语言中保持高相似性，验证了与Proto-Bantu的关联。
Who Warmed the Archives? LLMs Overestimate Historical Warmth
本研究评估 LLM 从历史档案提取气候指数时的跨世纪偏差，发现六个 LLM 均存在随年份增长的温暖偏差，仅凭相关性不足以验证其可靠性。
We adopt an evolutionary view on language change in which cognitive factors (in addition to social ones) affect the fitness of words and their success in the linguistic ecosystem. Specifically, we propose a variety of psycholinguistic factors -- semantic, distributional, and phonological -- that we hypothesize are predictive of lexical decline, in which words greatly decrease in frequency over time. Using historical data across three languages (English, French, and German), we find that most of our proposed factors show a significant difference in the expected direction between each curated se…
A Multidimensional Framework for Evaluating Lexical Semantic Change with Social Science Applications
本文提出一个整合情感、广度与强度的三维计算框架，用于系统评估词汇语义变化，并通过对心理健康相关语料的示例分析，揭示病理化、污名化和概念蠕变等社会议题中的语义演变模式。
Our languages are in constant flux driven by external factors such as cultural, societal and technological changes, as well as by only partially understood internal motivations. Words acquire new meanings and lose old senses, new words are coined or borrowed from other languages and obsolete words slide into obscurity. Understanding the characteristics of shifts in the meaning and in the use of words is useful for those who work with the content of historical texts, the interested general public, but also in and of itself. The findings from automatic lexical semantic change detection, and the …
Dynamic embedded topic models and change-point detection for exploring literary-historical hypotheses
本文结合动态嵌入式主题模型与变点检测，分析古典及早期基督教拉丁语中词汇语义情态的历时变化，并提出可迁移至更嘈杂语料的无监督研究路径。
Semantic Field Theory: Historical Origin, Higher-Order Interaction, and Stabilized Semantic Inference
本文围绕语义场理论展开，重构其演变并赋予清晰数学核心。核心方法是通过词汇表征等建模语言组织层次，贡献五个形式元素。主要贡献是为计算语言学等提供了可评估的模型及相关理论元素，虽非完整理论，但有重要意义。
While a great deal of work has been done on NLP approaches to lexical semantic change detection, other aspects of language change have received less attention from the NLP community. In this paper, we address the detection of sound change through historical spelling. We propose that a sound change can be captured by comparing the relative distance through time between their distributions using PPMI character embeddings. We verify this hypothesis in synthetic data and then test the method's ability to trace the well-known historical change of lenition of plosives in Danish historical sources. W…
Words are fundamental linguistic units that connect thoughts and things through meaning. However, words do not appear independently in a text sequence. The existence of syntactic rules induces correlations among neighboring words. Using an ordinal pattern approach, we present an analysis of lexical statistical connections for 11 major languages. We find that the diverse manners that languages utilize to express word relations give rise to unique pattern structural distributions. Furthermore, fluctuations of these pattern distributions for a given language can allow us to determine both the his…
This paper presents a number of experiments to model changes in a historical Portuguese corpus composed of literary texts for the purpose of temporal text classification. Algorithms were trained to classify texts with respect to their publication date taking into account lexical variation represented as word n-grams, and morphosyntactic variation represented by part-of-speech (POS) distribution. We report results of 99.8% accuracy using word unigram features with a Support Vector Machines classifier to predict the publication date of documents in time intervals of both one century and half a c…
Between Century and Poet: Graph-Based Lexical Semantic Change in Persian Poetry
本文通过词向量空间与图分析研究波斯诗歌中词汇语义的变迁，揭示词汇在历史与文学传统中的持续性与语义网络重构的动态过程。
Change and its precondition, variation, are inherent in languages. Over time, new words enter the lexicon, others become obsolete, and existing words acquire new senses. Associating a word's correct meaning in its historical context is a central challenge in diachronic research. Historical corpora of classical languages, such as Ancient Greek and Latin, typically come with rich metadata, and existing models are limited by their inability to exploit contextual information beyond the document timestamp. While embedding-based methods feature among the current state of the art systems, they are la…
A Tale of Two Laws of Semantic Change: Predicting Synonym Changes with Distributional Semantic Models
本文首次构建完整评估框架，利用分布语义模型检测同义词演变中分化定律与平行变化定律何者占主导，实验表明分化定律更具优势，最佳方法平衡准确率超过0.6。
Knowledge in the human mind exhibits a dualistic vector/network nature. Modelling words as vectors is key to natural language processing, whereas networks of word associations can map the nature of semantic memory. We reconcile these paradigms - fragmented across linguistics, psychology and computer science - by introducing FEature-Rich MUltiplex LEXical (FERMULEX) networks. This novel framework merges structural similarities in networks and vector features of words, which can be combined or explored independently. Similarities model heterogenous word associations across semantic/syntactic/pho…
LSC-Eval: A General Framework to Evaluate Methods for Assessing Dimensions of Lexical Semantic Change Using LLM-Generated Synthetic Data
本文提出LSC-Eval通用评估框架，利用LLM生成合成数据模拟词汇语义变化，验证了合成基准的有效性并揭示现有模型在情感维度检测上的不足。
Measures of lexical distance between languages
测量语言之间距离的想法似乎起源于法国探险家Dumont D 'Urville \cite{Urv}的工作。他在1826年至1829年的星盘航行中收集了各种语言的比较词汇表，在他关于太平洋地理划分的著作中，他提出了一种衡量语言之间关系程度的方法。现代声门年代学所使用的方法是由莫里斯·斯瓦迪什（Morris Swadesh）在20世纪50年代开发的，它测量了与共享同源词的百分比的距离，这些同源词是具有共同历史起源的词。最近，我们提出了一种新的自动化方法，该方法使用具有相同含义的单词之间的归一化Levenshtein距离和列表中包含的单词的平均值。最近，另一组学者\cite{Bak, Hol}提出了一个完善的定义，包括第二个规范化。在本文中，我们比较我们的定义与改进版本的信息内容，以决定两者中的哪一个可以更成功地解决语言之间的关系。
Pretraining Language Models for Diachronic Linguistic Change Discovery
本文提出通过预训练语言模型发现历时语言变化，通过高效预训练技术处理大规模语料，发现预训练模型在训练速度和历史划分尊重方面优于微调基线，展示了在历时语言学中检测词汇变化等现象的能力。
Matching Meaning at Scale: Evaluating Semantic Search for 18th-Century Intellectual History through the Case of Locke
本文通过洛克作品的接受情况，评估语义搜索在18世纪思想史中的应用，发现其能更有效地检索隐含意义，但受限于词汇重叠。
Community based question answering platforms have attracted substantial users to share knowledge and learn from each other. As the rapid enlargement of CQA platforms, quantities of overlapped questions emerge, which makes users confounded to select a proper reference. It is urgent for us to take effective automated algorithms to reuse historical questions with corresponding answers. In this paper we focus on the problem with question retrieval, which aims to match historical questions that are relevant or semantically equivalent to resolve one s query directly. The challenges in this task are …
Several language applications often require word semantics as a core part of their processing pipeline, either as precise meaning inference or semantic similarity. Multi-sense embeddings (M-SE) can be exploited for this important requirement. M-SE seeks to represent each word by their distinct senses in order to resolve the conflation of meanings of words as used in different contexts. Previous works usually approach this task by training a model on a large corpus and often ignore the effect and usefulness of the semantic relations offered by lexical resources. However, even with large trainin…
Interpretable Word Sense Representations via Definition Generation: The Case of Semantic Change Analysis
本研究提出用专门的Flan-T5模型生成语境化词汇用法的自然语言定义作为可解释词义表示，选取簇内原型定义为义项标签，提升了语义变化分析的可解释性，且在语境词语义相似度任务上优于传统嵌入，为NLP提供了新型词汇表示方案。
Automated words stability and languages phylogeny
测量语言之间距离的想法似乎起源于法国探险家Dumont D'Urville的工作（D'Urville 1832）。他在1826年至1829年的星盘航行中收集了各种语言的比较词汇表，在他关于太平洋地理划分的著作中，他提出了一种衡量语言之间联系程度的方法。现代声门年代学所使用的方法，由Morris Swadesh在20世纪50年代发展（Swadesh 1952），测量与共享同源词的百分比的距离，这些同源词是具有共同历史起源的词。最近，我们提出了一种新的自动化方法，该方法使用具有相同含义的单词之间的归一化Levenshtein距离和列表中包含的单词的平均值。声门年代学的另一个经典问题是研究对应不同意义的词的稳定性。事实上，由于词汇的变化、借用和替换，词汇的发展速度并不相同。词汇演变的速度对于不同的含义是不同的，这可能与相关词的使用频率有关（Pagel et al. 2007）。这个问题是解决这里的自动化方法，只基于归一化Levenshtein距离。
The availability of large diachronic corpora has provided the impetus for a growing body of quantitative research on language evolution and meaning change. The central quantities in this research are token frequencies of linguistic elements in texts, with changes in frequency taken to reflect the popularity or selective fitness of an element. However, corpus frequencies may change for a wide variety of reasons, including purely random sampling effects, or because corpora are composed of contemporary media and fiction texts within which the underlying topics ebb and flow with cultural and socio…
Diachronic word embeddings -- vector representations of words over time -- offer remarkable insights into the evolution of language and provide a tool for quantifying sociocultural change from text documents. Prior work has used such embeddings to identify shifts in the meaning of individual words. However, simply knowing that a word has changed in meaning is insufficient to identify the instances of word usage that convey the historical or the newer meaning. In this paper, we link diachronic word embeddings to documents, by situating those documents as leaders or laggards with respect to ongo…
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