CHRONOBERG: Capturing Language Evolution and Temporal Awareness in Foundation Models

Fuente: arXiv
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Autori principali: Hegde, Niharika, Paul, Subarnaduti, Joel-Frey, Lars, Brack, Manuel, Kersting, Kristian, Mundt, Martin, Schramowski, Patrick
Natura: Preprint
Pubblicazione: 2025
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author Hegde, Niharika
Paul, Subarnaduti
Joel-Frey, Lars
Brack, Manuel
Kersting, Kristian
Mundt, Martin
Schramowski, Patrick
author_facet Hegde, Niharika
Paul, Subarnaduti
Joel-Frey, Lars
Brack, Manuel
Kersting, Kristian
Mundt, Martin
Schramowski, Patrick
contents 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).
format Preprint
id arxiv_https___arxiv_org_abs_2509_22360
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle CHRONOBERG: Capturing Language Evolution and Temporal Awareness in Foundation Models
Hegde, Niharika
Paul, Subarnaduti
Joel-Frey, Lars
Brack, Manuel
Kersting, Kristian
Mundt, Martin
Schramowski, Patrick
Computation and Language
Artificial Intelligence
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).
title CHRONOBERG: Capturing Language Evolution and Temporal Awareness in Foundation Models
topic Computation and Language
Artificial Intelligence
url https://arxiv.org/abs/2509.22360