AI for Mathematics (AI4Math) is not only intriguing intellectually but also crucial for AI-driven
discovery in science, engineering, and beyond. Extensive efforts on AI4Math have mirrored …

Mathematics has long been conveyed through natural language, primarily for human
understanding. With the rise of mechanized mathematics and proof assistants, there is a …

Autoformalization, the task of automatically translating natural language descriptions into a
formal language, poses a significant challenge across various domains, especially in …

Throughout the history of automated reasoning, mathematics has been viewed as a
prototypical domain of application. It is therefore surprising that the technology has had …

Mathematical reasoning, a core aspect of human cognition, is vital across many domains,
from educational problem-solving to scientific advancements. As artificial general …

While recent AI-for-math has made strides in pure mathematics, areas of applied
mathematics, particularly PDEs, remain underexplored despite their significant real-world …

The research in AI-based formal mathematical reasoning has shown an unstoppable growth
trend. These studies have excelled in mathematical competitions like IMO, showing …

Autoformalization involves automatically translating informal math into formal theorems and
proofs that are machine-verifiable. Euclidean geometry provides an interesting and …

Scaling automated formal verification to real-world projects requires resolving cross-module
dependencies and global contexts, which are challenges overlooked by existing function …

Much of classical artificial intelligence in the tradition of McCarthy (1959) pursued symbolic
theorem proving over carefully hand-crafted ontologies of facts and rules. Due to challenges …