CHRONOBERG：捕捉基础模型中的语言演变与时间感知
CHRONOBERG: Capturing Language Evolution and Temporal Awareness in Foundation Models
AI总结：
针对现有语料库缺乏时间结构的问题，提出CHRONOBERG，一个跨越250年的英语书籍时间语料库，用于量化词汇语义变化并构建历史情感词典，证明现代LLM需时间感知训练以捕捉历时意义变化。
摘要：
大型语言模型（LLMs）通过利用社交媒体和从网络抓取的各种数据，在规模化运行方面表现出色。尽管现有语料库多种多样，但它们常常缺乏长期的时间结构，这可能限制了LLM将语言语义和规范的演变进行情境化处理以及捕捉历时变化的能力。为了支持后者的分析和训练，我们引入了CHRONOBERG，这是一个时间结构化的英语书籍文本语料库，跨越250年，选自Project Gutenberg，并丰富了各种时间注释。首先，书籍的编辑性质使我们能够通过时间敏感的效价-唤醒-支配（VAD）分析来量化词汇语义变化，并构建历史校准的情感词典，以支持基于时间的解释。有了这些词典，我们证明了现代基于LLM的工具需要更好地定位其对歧视性语言的检测和跨不同时期情感的情境化。事实上，我们展示了在CHRONOBERG上顺序训练的语言模型难以编码意义的历时变化，强调了需要时间感知的训练和评估流程，并将CHRONOBERG定位为研究语言变化和时间泛化的可扩展资源。免责声明：本文包含可能冒犯读者的语言和样本展示。开放获取：Chronoberg可在HuggingFace上公开获取（此https URL）。代码可在（此https URL）获取。
英文摘要：
Large language models (LLMs) excel at operating at scale by leveraging social media and various data crawled from the web. Whereas existing corpora are diverse, their frequent lack of long-term temporal structure may however limit an LLM's ability to contextualize semantic and normative evolution of language and to capture diachronic variation. To support analysis and training for the latter, we introduce CHRONOBERG, a temporally structured corpus of English book texts spanning 250 years, curated from Project Gutenberg and enriched with a variety of temporal annotations. First, the edited nature of books enables us to quantify lexical semantic change through time-sensitive Valence-Arousal-Dominance (VAD) analysis and to construct historically calibrated affective lexicons to support temporally grounded interpretation. With the lexicons at hand, we demonstrate a need for modern LLM-based tools to better situate their detection of discriminatory language and contextualization of sentiment across various time-periods. In fact, we show how language models trained sequentially on CHRONOBERG struggle to encode diachronic shifts in meaning, emphasizing the need for temporally aware training and evaluation pipelines, and positioning CHRONOBERG as a scalable resource for the study of linguistic change and temporal generalization. Disclaimer: This paper includes language and display of samples that could be offensive to readers. Open Access: Chronoberg is available publicly on HuggingFace at ( https://huggingface.co/datasets/spaul25/Chronoberg). Code is available at (https://github.com/paulsubarna/Chronoberg).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
