no code implementations • 7 Mar 2023 • Dell Zhang, Frank Schilder, Jack G. Conrad, Masoud Makrehchi, David von Rickenbach, Isabelle Moulinier
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 capable of helping human lawyers with a wide range of complex high-level legal tasks such as drafting legal briefs for the prosecution or defense in court.
no code implementations • 7 Dec 2022 • Beichen Zhang, Frank Schilder, Kelly Helm Smith, Michael J. Hayes, Sherri Harms, Tsegaye Tadesse
The model was then applied to California tweets and validated with keyword-based labels.
no code implementations • 5 Dec 2022 • 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.
no code implementations • 2 Dec 2022 • 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.
no code implementations • NAACL 2019 • Thomas Vacek, Dezhao Song, Hugo Molina-Salgado, Ronald Teo, Conner Cowling, Frank Schilder
In addition to a keyword search for judges, lawyers, law firms, parties and courts, we also implemented a question answering interface that offers targeted questions in order to get to the respective answers quicker.
no code implementations • WS 2019 • Thomas Vacek, Ronald Teo, Dezhao Song, Timothy Nugent, Conner Cowling, Frank Schilder
Dockets contain a wealth of information for planning a litigation strategy, but the information is locked up in semi-structured text.
no code implementations • WS 2018 • Charese Smiley, Elnaz Davoodi, Dezhao Song, Frank Schilder
This paper presents the two systems we entered into the 2017 E2E NLG Challenge: TemplGen, a templated-based system and SeqGen, a neural network-based system.
no code implementations • WS 2017 • Frank Schilder
This talk will present a few NLG systems developed within Thomson Reuters providing information to professionals such as lawyers, accountants or traders.
no code implementations • WS 2017 • Charese Smiley, Frank Schilder, Vassilis Plachouras, Jochen L. Leidner
We discuss the ethical implications of Natural Language Generation systems.