The use and creation of machine‐learning‐based solutions to solve problems or reduce
their computational costs are becoming increasingly widespread in many domains. Deep …

Large language models (LLMs) have demonstrated impressive capabilities in natural
language processing. However, their internal mechanisms are still unclear and this lack of …

Transformer is a promising neural network learner, and has achieved great success in
various machine learning tasks. Thanks to the recent prevalence of multimodal applications …

Large Language Models (LLMs) have gained widespread popularity due to their ability to
perform ad-hoc Natural Language Processing (NLP) tasks with a simple natural language …

State-of-the-art neural language models can now be used to solve ad-hoc language tasks
through zero-shot prompting without the need for supervised training. This approach has …

Transformer models are revolutionizing machine learning, but their inner workings remain
mysterious. In this work, we present a new visualization technique designed to help …

High-quality visualization collections are beneficial for a variety of applications including
visualization reference and data-driven visualization design. The visualization community …

The past decade has witnessed a plethora of works that leverage the power of visualization
(VIS) to interpret machine learning (ML) models. The corresponding research topic, VIS4ML …

Identifying important neurons for final predictions is essential for understanding the
mechanisms of large language models. Due to computational constraints, current attribution …

AI Safety is an emerging area of critical importance to the safe adoption and deployment of
AI systems. With the rapid proliferation of AI and especially with the recent advancement of …