Large language models (LLM) have become state of the art in many benchmarks and
conversational LLM applications like ChatGPT are now widely used by the public. Those …

As AI model size grows, neural scaling laws have become a crucial tool to predict the
improvements of large models when increasing capacity and the size of original (human or …

The performance of conversational Large Language Models (LLMs) in general, and of
ChatGPT in particular, is currently being evaluated on many different tasks, from logical …

Synthesized data from generative models is increasingly considered as an alternative to
human-annotated data for fine-tuning Large Language Models. This raises concerns about …

Recommendation systems and assistants (in short, recommenders) are ubiquitous in online
platforms and influence most actions of our day-to-day lives, suggesting items or providing …

The rapid progress in generative models has resulted in impressive leaps in generation
quality, blurring the lines between synthetic and real data. Web-scale datasets are now …

Within the scaling laws paradigm, which underpins the training of large neural networks like
ChatGPT and Llama, we consider a supervised regression setting and establish the …

The advent of generative AI (GenAI) technology produces transformative impact on the
content creation landscape, offering alternative approaches to produce diverse, high-quality …

In the era of large language models like ChatGPT, the phenomenon of" model collapse"
refers to the situation whereby as a model is trained recursively on data generated from …

What happens if we train a new Large Language Model (LLM) using data that are at least
partially generated by other LLMs? The explosive success of LLMs means that a substantial …