16 citations · 42 across the 9 of their papers we have counts for
11 papers · 1 filter
Evaluating and Benchmarking the System One Model Jev
Tobias Deußer, Lorenz Sparrenberg, Rafet Sifa
Jev is a commercial System One model from TypeSafe AI that does not generate text: given a state and typed questions, it returns a choice from fixed options, a position on a rubric…
Automated Regulatory Compliance Question Answering in Financial Services with Domain-Adapted Retrieval-Augmented Generation
Tobias Deußer, Abhishek Pillai, Aurelio F. Bariviera +5
Financial institutions operate under dense, frequently amended rulebooks, and answering a compliance question correctly requires not only fluency but verifiable grounding in the au…
On the Impact of Anonymization on the Performance of Large Language Models
Tobias Deußer, Max Hahnbück, Lorenz Sparrenberg +3
As large language models are increasingly deployed in sensitive domains, anonymizing input data to protect personally identifiable information has become a critical practice. Howev…
A Survey on Current Trends and Recent Advances in Text Anonymization
Tobias Deußer, Lorenz Sparrenberg, Armin Berger +3
The proliferation of textual data containing sensitive personal information across various domains requires robust anonymization techniques to protect privacy and comply with regul…
Informed Named Entity Recognition Decoding for Generative Language Models
Tobias Deußer, Lars Hillebrand, Christian Bauckhage +1
Ever-larger language models with ever-increasing capabilities are by now well-established text processing tools. Alas, information extraction tasks such as named entity recognition…
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…
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 automating Numerical Consistency Checks in Financial Reports
Lars Hillebrand, Tobias Deußer, Tim Dilmaghani +4
We introduce KPI-Check, a novel system that automatically identifies and cross-checks semantically equivalent key performance indicators (KPIs), e.g. "revenue" or "total costs", in…
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…
KPI-EDGAR: A Novel Dataset and Accompanying Metric for Relation Extraction from Financial Documents
Tobias Deußer, Syed Musharraf Ali, Lars Hillebrand +4
We introduce KPI-EDGAR, a novel dataset for Joint Named Entity Recognition and Relation Extraction building on financial reports uploaded to the Electronic Data Gathering, Analysis…
KPI-BERT: A Joint Named Entity Recognition and Relation Extraction Model for Financial Reports
Lars Hillebrand, Tobias Deußer, Tim Dilmaghani +4
We present KPI-BERT, a system which employs novel methods of named entity recognition (NER) and relation extraction (RE) to extract and link key performance indicators (KPIs), e.g.…