The computational complexity of the self-attention mechanism in popular transformer
architectures poses significant challenges for training and inference, and becomes the …

Recent advancements in artificial intelligence have led to the creation of highly capable
large language models (LLMs) that can perform tasks in a human-like manner. However …

Exploring open-vocabulary video action recognition is a promising venture, which aims to
recognize previously unseen actions within any arbitrary set of categories. Existing methods …

Characterizing the express power of the Transformer architecture is critical to understanding
its capacity limits and scaling law. Recent works provide the circuit complexity bounds to …

As Artificial Intelligence (AI) continues to advance rapidly, Friendly AI (FAI) has been
proposed to advocate for more equitable and fair development of AI. Despite its importance …

LMMs have shown impressive visual understanding capabilities, with the potential to be
applied in agents, which demand strong reasoning and planning abilities. Nevertheless …

Large vision language models (VLMs) have demonstrated significant potential for
integration into daily life, making it crucial for them to incorporate human values when …

Large language models (LLMs) are increasingly deployed via public-facing interfaces to
interact with millions of users, each with diverse preferences. Despite this, preference tuning …

Large language models (LLMs) with powerful generalization ability has been widely used in
many domains. A systematic and reliable evaluation of LLMs is a crucial step in their …

In this paper, we study the impact of AI and emerging technologies on the American labor
force by exploring AI's potential for substitution and complementarity with human workers …