activity
20222024
most citedsustain.AI: a Recommender System to analyze Sustainability Reports

8 citations · 14 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2024★ 1 cited

[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…

cs.CL2023

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…

cs.CL2023★ 2 cited

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…

cs.CL2023★ 1 cited

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…

cs.CL2023★ 8 cited

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'…

cs.CL2022★ 2 cited

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…

cs.CL2022

Zero-Shot Text Matching for Automated Auditing using Sentence Transformers

David Biesner, Maren Pielka, Rajkumar Ramamurthy +4

Natural language processing methods have several applications in automated auditing, including document or passage classification, information retrieval, and question answering. Ho…

cs.CL2022

A Linguistic Investigation of Machine Learning based Contradiction Detection Models: An Empirical Analysis and Future Perspectives

Maren Pielka, Felix Rode, Lisa Pucknat +2

We analyze two Natural Language Inference data sets with respect to their linguistic features. The goal is to identify those syntactic and semantic properties that are particularly…