806 citations · 1.1k across the 47 of their papers we have counts for
48 papers
Certified decoding of quantum LDPC codes
Ragavi Krishnamoorthy, Florian Gerhardt, Johannes Knaute +8
Quantum low-density parity-check (qLDPC) codes reduce the qubit overhead of fault-tolerant quantum computation by an order of magnitude, but their decoding is harder than its class…
Interpretable Topic Extraction and Word Embedding Learning using row-stochastic DEDICOM
Lars Hillebrand, David Biesner, Christian Bauckhage +1
The DEDICOM algorithm provides a uniquely interpretable matrix factorization method for symmetric and asymmetric square matrices. We employ a new row-stochastic variation of DEDICO…
Controlled Randomness Improves the Performance of Transformer Models
Tobias Deußer, Cong Zhao, Wolfgang Krämer +3
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 tex…
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…
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…
Solving Subset Sum Problems using Quantum Inspired Optimization Algorithms with Applications in Auditing and Financial Data Analysis
David Biesner, Thore Gerlach, Christian Bauckhage +2
Many applications in automated auditing and the analysis and consistency check of financial documents can be formulated in part as the subset sum problem: Given a set of numbers an…
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…
Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization
Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kianté Brantley +5
We tackle the problem of aligning pre-trained large language models (LMs) with human preferences. If we view text generation as a sequential decision-making problem, reinforcement…
Full Kullback-Leibler-Divergence Loss for Hyperparameter-free Label Distribution Learning
Maurice Günder, Nico Piatkowski, Christian Bauckhage
The concept of Label Distribution Learning (LDL) is a technique to stabilize classification and regression problems with ambiguous and/or imbalanced labels. A prototypical use-case…
A New Aligned Simple German Corpus
Vanessa Toborek, Moritz Busch, Malte Boßert +2
"Leichte Sprache", the German counterpart to Simple English, is a regulated language aiming to facilitate complex written language that would otherwise stay inaccessible to differe…
Gradient Flows for L2 Support Vector Machine Training
Christian Bauckhage, Helen Schneider, Benjamin Wulff +1
We explore the merits of training of support vector machines for binary classification by means of solving systems of ordinary differential equations. We thus assume a continuous t…
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.…
Predict better with less training data using a QNN
Barry D. Reese, Marek Kowalik, Christian Metzl +2
Over the past decade, machine learning revolutionized vision-based quality assessment for which convolutional neural networks (CNNs) have now become the standard. In this paper, we…
Informed Pre-Training on Prior Knowledge
Laura von Rueden, Sebastian Houben, Kostadin Cvejoski +2
When training data is scarce, the incorporation of additional prior knowledge can assist the learning process. While it is common to initialize neural networks with weights that ha…
Towards Bundle Adjustment for Satellite Imaging via Quantum Machine Learning
Nico Piatkowski, Thore Gerlach, Romain Hugues +3
Given is a set of images, where all images show views of the same area at different points in time and from different viewpoints. The task is the alignment of all images such that…
QUBOs for Sorting Lists and Building Trees
Christian Bauckhage, Thore Gerlach, Nico Piatkowski
We show that the fundamental tasks of sorting lists and building search trees or heaps can be modeled as quadratic unconstrained binary optimization problems (QUBOs). The idea is t…
Agricultural Plant Cataloging and Establishment of a Data Framework from UAV-based Crop Images by Computer Vision
Maurice Günder, Facundo R. Ispizua Yamati, Jana Kierdorf +3
UAV-based image retrieval in modern agriculture enables gathering large amounts of spatially referenced crop image data. In large-scale experiments, however, UAV images suffer from…
Evolutionary Hierarchical Harvest Schedule Optimization for Food Waste Prevention
Maurice Günder, Nico Piatkowski, Laura von Rueden +2
In order to avoid disadvantages of monocropping for soil and environment, it is advisable to practice intercropping of various plant species whenever possible. However, intercroppi…
Dynamic Review-based Recommenders
Kostadin Cvejoski, Ramses J. Sanchez, Christian Bauckhage +1
Just as user preferences change with time, item reviews also reflect those same preference changes. In a nutshell, if one is to sequentially incorporate review content knowledge in…
Street-Map Based Validation of Semantic Segmentation in Autonomous Driving
Laura von Rueden, Tim Wirtz, Fabian Hueger +3
Artificial intelligence for autonomous driving must meet strict requirements on safety and robustness, which motivates the thorough validation of learned models. However, current v…
Recurrent Point Review Models
Kostadin Cvejoski, Ramses J. Sanchez, Bogdan Georgiev +2
Deep neural network models represent the state-of-the-art methodologies for natural language processing. Here we build on top of these methodologies to incorporate temporal informa…
Quantum Circuit Evolution on NISQ Devices
Lukas Franken, Bogdan Georgiev, Sascha Mücke +4
Variational quantum circuits build the foundation for various classes of quantum algorithms. In a nutshell, the weights of a parametrized quantum circuit are varied until the empir…
Towards Map-Based Validation of Semantic Segmentation Masks
Laura von Rueden, Tim Wirtz, Fabian Hueger +2
Artificial intelligence for autonomous driving must meet strict requirements on safety and robustness. We propose to validate machine learning models for self-driving vehicles not…