@inproceedings{shafiabadi-wisniewski-2025-beyond,
title = "Beyond Surprisal: A Dual Metric Framework for Lexical Skill Acquisition in {LLM}s",
author = "Shafiabadi, Nazanin and
Wisniewski, Guillaume",
editor = "Rambow, Owen and
Wanner, Leo and
Apidianaki, Marianna and
Al-Khalifa, Hend and
Eugenio, Barbara Di and
Schockaert, Steven",
booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.coling-main.443/",
pages = "6636--6641",
abstract = "Many studies have explored when and how LLMs learn to use specific words, primarily by examining their learning curves. While these curves capture a model`s capacity to use words correctly in context, they often neglect the equally important skill of avoiding incorrect usage. In this paper, we introduce a new metric, anti-surprisal, which measures a model`s capacity to refrain from using words in inappropriate or unexpected contexts. By examining both correct usage and error avoidance, we offer a more comprehensive perspective on the learning dynamics of LLMs."
}
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<abstract>Many studies have explored when and how LLMs learn to use specific words, primarily by examining their learning curves. While these curves capture a model‘s capacity to use words correctly in context, they often neglect the equally important skill of avoiding incorrect usage. In this paper, we introduce a new metric, anti-surprisal, which measures a model‘s capacity to refrain from using words in inappropriate or unexpected contexts. By examining both correct usage and error avoidance, we offer a more comprehensive perspective on the learning dynamics of LLMs.</abstract>
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%0 Conference Proceedings
%T Beyond Surprisal: A Dual Metric Framework for Lexical Skill Acquisition in LLMs
%A Shafiabadi, Nazanin
%A Wisniewski, Guillaume
%Y Rambow, Owen
%Y Wanner, Leo
%Y Apidianaki, Marianna
%Y Al-Khalifa, Hend
%Y Eugenio, Barbara Di
%Y Schockaert, Steven
%S Proceedings of the 31st International Conference on Computational Linguistics
%D 2025
%8 January
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F shafiabadi-wisniewski-2025-beyond
%X Many studies have explored when and how LLMs learn to use specific words, primarily by examining their learning curves. While these curves capture a model‘s capacity to use words correctly in context, they often neglect the equally important skill of avoiding incorrect usage. In this paper, we introduce a new metric, anti-surprisal, which measures a model‘s capacity to refrain from using words in inappropriate or unexpected contexts. By examining both correct usage and error avoidance, we offer a more comprehensive perspective on the learning dynamics of LLMs.
%U https://aclanthology.org/2025.coling-main.443/
%P 6636-6641
Markdown (Informal)
[Beyond Surprisal: A Dual Metric Framework for Lexical Skill Acquisition in LLMs](https://aclanthology.org/2025.coling-main.443/) (Shafiabadi & Wisniewski, COLING 2025)
ACL