33 citations · 88 across the 25 of their papers we have counts for
5 papers · 1 filter
On Meta-Prompting
Adrian de Wynter, Xun Wang, Qilong Gu +1
Modern large language models (LLMs) are capable of interpreting input strings as instructions, or prompts, and carry out tasks based on them. Unlike traditional learners, LLMs cann…
"I'd Like to Have an Argument, Please": Argumentative Reasoning in Large Language Models
Adrian de Wynter, Tangming Yuan
We evaluate two large language models (LLMs) ability to perform argumentative reasoning. We experiment with argument mining (AM) and argument pair extraction (APE), and evaluate th…
Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?
Rishav Hada, Varun Gumma, Adrian de Wynter +5
Large Language Models (LLMs) excel in various Natural Language Processing (NLP) tasks, yet their evaluation, particularly in languages beyond the top , remains inadequate due t…
A User-Centered Evaluation of Spanish Text Simplification
Adrian de Wynter, Anthony Hevia, Si-Qing Chen
We present an evaluation of text simplification (TS) in Spanish for a production system, by means of two corpora focused in both complex-sentence and complex-word identification. W…
An Evaluation on Large Language Model Outputs: Discourse and Memorization
Adrian de Wynter, Xun Wang, Alex Sokolov +2
We present an empirical evaluation of various outputs generated by nine of the most widely-available large language models (LLMs). Our analysis is done with off-the-shelf, readily-…