4 papers
Surprisal and Metaphor Novelty Judgments: Moderate Correlations and Divergent Scaling Effects Revealed by Corpus-Based and Synthetic Datasets
Omar Momen, Emilie Sitter, Berenike Herrmann +1
Novel metaphor comprehension involves complex semantic processes and linguistic creativity, making it an interesting task for studying language models (LMs). This study investigate…
Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language Models
Raha Askari, Sina Zarrieß, Özge Alacam +1
Implicit meanings are integral to human communication, making it essential for language models to be capable of identifying and interpreting them. Grice (1975) proposed a set of co…
The InviTE Corpus: Annotating Invectives in Tudor English Texts for Computational Modeling
Sophie Spliethoff, Sanne Hoeken, Silke Schwandt +2
In this paper, we aim at the application of Natural Language Processing (NLP) techniques to historical research endeavors, particularly addressing the study of religious invectives…
Implicit Causality-biases in humans and LLMs as a tool for benchmarking LLM discourse capabilities
Florian Kankowski, Torgrim Solstad, Sina Zarriess +1
In this paper, we compare data generated with mono- and multilingual LLMs spanning a range of model sizes with data provided by human participants in an experimental setting invest…