34 citations · 67 across the 4 of their papers we have counts for
4 papers
Making a Computational Attorney
Dell Zhang, Frank Schilder, Jack G. Conrad +3
This "blue sky idea" paper outlines the opportunities and challenges in data mining and machine learning involving making a computational attorney -- an intelligent software agent…
Legal Prompting: Teaching a Language Model to Think Like a Lawyer
Fangyi Yu, Lee Quartey, Frank Schilder
Large language models that are capable of zero or few-shot prompting approaches have given rise to the new research area of prompt engineering. Recent advances showed that for exam…
TweetDrought: A Deep-Learning Drought Impacts Recognizer based on Twitter Data
Beichen Zhang, Frank Schilder, Kelly Helm Smith +3
Acquiring a better understanding of drought impacts becomes increasingly vital under a warming climate. Traditional drought indices describe mainly biophysical variables and not im…
Legal Prompt Engineering for Multilingual Legal Judgement Prediction
Dietrich Trautmann, Alina Petrova, Frank Schilder
Legal Prompt Engineering (LPE) or Legal Prompting is a process to guide and assist a large language model (LLM) with performing a natural legal language processing (NLLP) skill. Ou…