LLMs are widely used in complex AI applications. These applications underscore the need
for LLM outputs to adhere to a specific format, for their integration with other components in …

One of the most striking findings in modern research on large language models (LLMs) is
that scaling up compute during training leads to better results. However, less attention has …

The ability of Large Language Models (LLMs) to generate structured outputs, such as JSON,
is crucial for their use in Compound AI Systems. However, evaluating and improving this …

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 …

Large language models (LLMs) have demonstrated remarkable capabilities in document
processing, data analysis, and code generation. However, the generation of spatial …

Nowadays, large language models (LLMs) are an extremely useful and fast tool to
complement and help in many jobs and current problems. However, there are cases where …

Decision-making agents based on pre-trained Large Language Models (LLMs) are
increasingly being deployed across various domains of human activity. While their …

While large language models (LLMs) have seen unprecedented advancements in
capabilities and applications across a variety of use-cases, safety alignment of these models …

Large language models (LLMs) have revolutionized natural language interfaces for
databases, particularly in text-to-SQL conversion. However, current approaches often …

Logical reasoning is a critical component of Large Language Models (LLMs), and
substantial research efforts in recent years have aimed to enhance their deductive …