Publications (9)
Do Large GPT Models Discover Moral Dimensions in Language Representations? A Topological Study Of Sentence Embeddings
Stephen Fitz
As Large Language Models are deployed within Artificial Intelligence systems, that are increasingly integrated with human society, it becomes more important than ever to study thei…
Testing the Machine Consciousness Hypothesis
Stephen Fitz
The Machine Consciousness Hypothesis states that consciousness is a substrate-free functional property of computational systems capable of second-order perception. I propose a rese…
Personality Traits in Large Language Models
Greg Serapio-GarcÃa, Mustafa Safdari, Clément Crepy +6
The advent of large language models (LLMs) has revolutionized natural language processing, enabling the generation of coherent and contextually relevant human-like text. As LLMs in…
Psychometric Personality Shaping Modulates Capabilities and Safety in Language Models
Stephen Fitz, Peter Romero, Steven Basart +2
Large Language Models increasingly mediate high-stakes interactions, intensifying research on their capabilities and safety. While recent work has shown that LLMs exhibit consisten…
Parameter-Efficient Neural Question Answering Models via Graph-Enriched Document Representations
Louis Castricato, Stephen Fitz, Won Young Shin
As the computational footprint of modern NLP systems grows, it becomes increasingly important to arrive at more efficient models. We show that by employing graph convolutional docu…
Hidden Holes: topological aspects of language models
Stephen Fitz, Peter Romero, Jiyan Jonas Schneider
We explore the topology of representation manifolds arising in autoregressive neural language models trained on raw text data. In order to study their properties, we introduce tool…