6 papers · 1 filter
Word Class Representations Spontaneously Emerge from Successor Representations Trained on Natural Language
Mathis Immertreu, Achim Schilling, Thomas Kinfe +1
Language models are typically trained to predict the next token in a sequence. Here, we explore an alternative predictive principle from reinforcement learning: Successor Represent…
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…
Analysis and Visualization of Linguistic Structures in Large Language Models: Neural Representations of Verb-Particle Constructions in BERT
Hassane Kissane, Achim Schilling, Patrick Krauss
This study investigates the internal representations of verb-particle combinations within transformer-based large language models (LLMs), specifically examining how these models ca…