31 citations · 39 across the 7 of their papers we have counts for
9 papers · 1 filter
Measuring the Groundedness of Legal Question-Answering Systems
Dietrich Trautmann, Natalia Ostapuk, Quentin Grail +4
In high-stakes domains like legal question-answering, the accuracy and trustworthiness of generative AI systems are of paramount importance. This work presents a comprehensive benc…
Large Language Model Prompt Chaining for Long Legal Document Classification
Dietrich Trautmann
Prompting is used to guide or steer a language model in generating an appropriate response that is consistent with the desired outcome. Chaining is a strategy used to decompose com…
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…
Active Learning for Argument Mining: A Practical Approach
Nikolai Solmsdorf, Dietrich Trautmann, Hinrich Schütze
Despite considerable recent progress, the creation of well-balanced and diverse resources remains a time-consuming and costly challenge in Argument Mining. Active Learning reduces…
Aspect-Based Argument Mining
Dietrich Trautmann
Computational Argumentation in general and Argument Mining in particular are important research fields. In previous works, many of the challenges to automatically extract and to so…
Multipurpose Intelligent Process Automation via Conversational Assistant
Alena Moiseeva, Dietrich Trautmann, Michael Heimann +1
Intelligent Process Automation (IPA) is an emerging technology with a primary goal to assist the knowledge worker by taking care of repetitive, routine and low-cognitive tasks. Con…