Zobrazeno 1 - 10
of 124
pro vyhledávání: '"Deusser, A."'
Autor:
Doering, Elena, Hönig, Merle C., Deußer, Tobias, Bischof, Gerard N., van Eimeren, Thilo, Drzezga, Alexander, Ellingsen, Lotta M.
Publikováno v:
Medical Imaging 2024: Clinical and Biomedical Imaging
Alzheimer's disease (AD) is a progressive neurodegenerative disorder leading to cognitive decline. [$^{18}$F]-Fluorodeoxyglucose positron emission tomography ([$^{18}$F]-FDG PET) is used to monitor brain metabolism, aiding in the diagnosis and assess
Externí odkaz:
http://arxiv.org/abs/2402.04299
Autor:
Deußer, Tobias, Zhao, Cong, Krämer, Wolfgang, Leonhard, David, Bauckhage, Christian, Sifa, Rafet
During the pre-training step of natural language models, the main objective is to learn a general representation of the pre-training dataset, usually requiring large amounts of textual data to capture the complexity and diversity of natural language.
Externí odkaz:
http://arxiv.org/abs/2310.13526
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 are still largely unaffected by this progress as they are primarily b
Externí odkaz:
http://arxiv.org/abs/2308.07791
Autor:
Hillebrand, Lars, Berger, Armin, Deußer, Tobias, Dilmaghani, Tim, Khaled, Mohamed, Kliem, Bernd, Loitz, Rüdiger, Pielka, Maren, Leonhard, David, Bauckhage, Christian, Sifa, Rafet
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 passages from a report for each legal requirement of rigorous accounting s
Externí odkaz:
http://arxiv.org/abs/2308.06111
Autor:
Hillebrand, Lars, Pielka, Maren, Leonhard, David, Deußer, Tobias, Dilmaghani, Tim, Kliem, Bernd, Loitz, Rüdiger, Morad, Milad, Temath, Christian, Bell, Thiago, Stenzel, Robin, Sifa, Rafet
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' sustainability reports. The tool leverages an end-to-end trainable ar
Externí odkaz:
http://arxiv.org/abs/2305.08711
Autor:
Hillebrand, Lars, Deußer, Tobias, Dilmaghani, Tim, Kliem, Bernd, Loitz, Rüdiger, Bauckhage, Christian, Sifa, Rafet
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 real-world German financial reports. It combines a financial named en
Externí odkaz:
http://arxiv.org/abs/2211.06112
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 hard to comprehend for a machine learning model. To this end, we also
Externí odkaz:
http://arxiv.org/abs/2210.10434
Autor:
Deußer, Tobias, Ali, Syed Musharraf, Hillebrand, Lars, Nurchalifah, Desiana, Jacob, Basil, Bauckhage, Christian, Sifa, Rafet
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, and Retrieval (EDGAR) system, where the main objective is to extract
Externí odkaz:
http://arxiv.org/abs/2210.09163
Autor:
Hillebrand, Lars, Deußer, Tobias, Dilmaghani, Tim, Kliem, Bernd, Loitz, Rüdiger, Bauckhage, Christian, Sifa, Rafet
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. "revenue" or "interest expenses", of companies from real-world German
Externí odkaz:
http://arxiv.org/abs/2208.02140
Balancing the load in content addressing schemes for route-restricted networks represents a challenge with a wide range of applications. Solutions based on greedy embeddings maintain minimal state information and enable efficient routing, but any suc
Externí odkaz:
http://arxiv.org/abs/1701.03522