8 citations · 14 across the 8 of their papers we have counts for
8 papers · 1 filter
[Vision Paper] PRObot: Enhancing Patient-Reported Outcome Measures for Diabetic Retinopathy using Chatbots and Generative AI
Maren Pielka, Tobias Schneider, Jan Terheyden +1
We present an outline of the first large language model (LLM) based chatbot application in the context of patient-reported outcome measures (PROMs) for diabetic retinopathy. By uti…
Generating Prototypes for Contradiction Detection Using Large Language Models and Linguistic Rules
Maren Pielka, Svetlana Schmidt, Rafet Sifa
We introduce a novel data generation method for contradiction detection, which leverages the generative power of large language models as well as linguistic rules. Our vision is to…
Improving Zero-Shot Text Matching for Financial Auditing with Large Language Models
Lars Hillebrand, Armin Berger, Tobias Deußer +8
Auditing financial documents is a very tedious and time-consuming process. As of today, it can already be simplified by employing AI-based solutions to recommend relevant text pass…
Improving Natural Language Inference in Arabic using Transformer Models and Linguistically Informed Pre-Training
Mohammad Majd Saad Al Deen, Maren Pielka, Jörn Hees +2
This paper addresses the classification of Arabic text data in the field of Natural Language Processing (NLP), with a particular focus on Natural Language Inference (NLI) and Contr…
sustain.AI: a Recommender System to analyze Sustainability Reports
Lars Hillebrand, Maren Pielka, David Leonhard +9
We present sustainAI, an intelligent, context-aware recommender system that assists auditors and financial investors as well as the general public to efficiently analyze companies'…
Towards Linguistically Informed Multi-Objective Pre-Training for Natural Language Inference
Maren Pielka, Svetlana Schmidt, Lisa Pucknat +1
We introduce a linguistically enhanced combination of pre-training methods for transformers. The pre-training objectives include POS-tagging, synset prediction based on semantic kn…