2 citations · 12 across the 23 of their papers we have counts for
7 papers · 1 filter
Illuminating the Black Box of Reservoir Computing
Claus Metzner, Achim Schilling, Thomas Kinfe +2
Reservoir computers, based on large recurrent neural networks with fixed random connections, are known to perform a wide range of information processing tasks. However, the nature…
The Predictive Brain: Neural Correlates of Word Expectancy Align with Large Language Model Prediction Probabilities
Nikola Kölbl, Konstantin Tziridis, Andreas Maier +4
Predictive coding theory suggests that the brain continuously anticipates upcoming words to optimize language processing, but the neural mechanisms remain unclear, particularly in…
Organizational Regularities in Recurrent Neural Networks
Claus Metzner, Achim Schilling, Andreas Maier +1
Previous work has shown that the dynamical regime of Recurrent Neural Networks (RNNs) - ranging from oscillatory to chaotic and fixpoint behavior - can be controlled by the global…
Probing Internal Representations of Multi-Word Verbs in Large Language Models
Hassane Kissane, Achim Schilling, Patrick Krauss
This study investigates the internal representations of verb-particle combinations, called multi-word verbs, within transformer-based large language models (LLMs), specifically exa…
Author-Specific Linguistic Patterns Unveiled: A Deep Learning Study on Word Class Distributions
Patrick Krauss, Achim Schilling
Deep learning methods have been increasingly applied to computational linguistics to uncover patterns in text data. This study investigates author-specific word class distributions…
Refusal Behavior in Large Language Models: A Nonlinear Perspective
Fabian Hildebrandt, Andreas Maier, Patrick Krauss +1
Refusal behavior in large language models (LLMs) enables them to decline responding to harmful, unethical, or inappropriate prompts, ensuring alignment with ethical standards. This…
Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT
Awritrojit Banerjee, Achim Schilling, Patrick Krauss
This study investigates the internal mechanisms of BERT, a transformer-based large language model, with a focus on its ability to cluster narrative content and authorial style acro…