9 papers
Uncovering Hidden Systematics in Neural Network Models for High Energy Physics
Lucie Flek, Philipp Alexander Jungs, Akbar Karimi +6
Neural networks (NNs) are inherently multidimensional classifiers that learn complex, non-linear relationships among input observables. While their flexibility enables unprecedente…
Shapes are not enough: CONSERVAttack and its use for finding vulnerabilities and uncertainties in machine learning applications
Philip Bechtle, Lucie Flek, Philipp Alexander Jung +7
In High Energy Physics, as in many other fields of science, the application of machine learning techniques has been crucial in advancing our understanding of fundamental phenomena.…
Can LLM Agents Identify Spoken Dialects like a Linguist?
Tobias Bystrich, Lukas Hamm, Maria Hassan +3
Due to the scarcity of labeled dialectal speech, audio dialect classification is a challenging task for most languages, including Swiss German. In this work, we explore the ability…
Label-Consistent Data Generation for Aspect-Based Sentiment Analysis Using LLM Agents
Mohammad H. A. Monfared, Lucie Flek, Akbar Karimi
We propose an agentic data augmentation method for Aspect-Based Sentiment Analysis (ABSA) that uses iterative generation and verification to produce high quality synthetic training…
Encoder Fine-tuning with Stochastic Sampling Outperforms Open-weight GPT in Astronomy Knowledge Extraction
Shivam Rawat, Lucie Flek, Akbar Karimi
Scientific literature in astronomy is rapidly expanding, making it increasingly important to automate the extraction of key entities and contextual information from research papers…
More Agents Improve Math Problem Solving but Adversarial Robustness Gap Persists
Khashayar Alavi, Zhastay Yeltay, Lucie Flek +1
When LLM agents work together, they seem to be more powerful than a single LLM in mathematical question answering. However, are they also more robust to adversarial inputs? We inve…
MiniFool -- Physics-Constraint-Aware Minimizer-Based Adversarial Attacks in Deep Neural Networks
Lucie Flek, Oliver Janik, Philipp Alexander Jung +8
In this paper, we present a new algorithm, MiniFool, that implements physics-inspired adversarial attacks for testing neural network-based classification tasks in particle and astr…
Improving Low-Resource Dialect Classification Using Retrieval-based Voice Conversion
Lea Fischbach, Akbar Karimi, Caroline Kleen +2
Deep learning models for dialect identification are often limited by the scarcity of dialectal data. To address this challenge, we propose to use Retrieval-based Voice Conversion (…
Multi-Hop Reasoning for Question Answering with Hyperbolic Representations
Simon Welz, Lucie Flek, Akbar Karimi
Hyperbolic representations are effective in modeling knowledge graph data which is prevalently used to facilitate multi-hop reasoning. However, a rigorous and detailed comparison o…