3 papers
cs.CL2024
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…
cs.CL2024
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,…
cs.CL2024
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…