12 citations · 17 across the 4 of their papers we have counts for
4 papers · 1 filter
Your Large Language Models Are Leaving Fingerprints
Hope McGovern, Rickard Stureborg, Yoshi Suhara +1
It has been shown that finetuned transformers and other supervised detectors effectively distinguish between human and machine-generated text in some situations arXiv:2305.13242, b…
Large Language Models are Inconsistent and Biased Evaluators
Rickard Stureborg, Dimitris Alikaniotis, Yoshi Suhara
The zero-shot capability of Large Language Models (LLMs) has enabled highly flexible, reference-free metrics for various tasks, making LLM evaluators common tools in NLP. However,…
Source Identification in Abstractive Summarization
Yoshi Suhara, Dimitris Alikaniotis
Neural abstractive summarization models make summaries in an end-to-end manner, and little is known about how the source information is actually converted into summaries. In this p…
mEdIT: Multilingual Text Editing via Instruction Tuning
Vipul Raheja, Dimitris Alikaniotis, Vivek Kulkarni +2
We introduce mEdIT, a multi-lingual extension to CoEdIT -- the recent state-of-the-art text editing models for writing assistance. mEdIT models are trained by fine-tuning multi-lin…