Publications

This paper presents a method to analyze the inference patterns used by Large Language Models (LLMs) for judgment in a case study on …

Transformers are the cornerstone of modern large language models, but their quadratic computational complexity limits efficiency in …

To advance the mathematical proficiency of large language models (LLMs), the DeepMath team has launched an open-source initiative aimed …

The fusion of speech and language in the era of large language models has garnered significant attention. Discrete speech token is …

In the field of large language models (LLMs), Knowledge Distillation (KD) is a critical technique for transferring capabilities from …

Low-precision training is considered an effective strategy for reducing both training and downstream inference costs. Previous scaling …

Action understanding matters for intelligent agents and has attracted long-term attention. It can be formed as the mapping from the …