Alongside huge volumes of research on deep learning models in NLP in the recent years,
there has been much work on benchmark datasets needed to track modeling progress …

Mathematical reasoning is a fundamental aspect of human intelligence and is applicable in
various fields, including science, engineering, finance, and everyday life. The development …

This survey reviews works in which language models (LMs) are augmented with reasoning
skills and the ability to use tools. The former is defined as decomposing a potentially …

Abstract Language models have achieved remarkable performance on a wide range of
tasks that require natural language understanding. Nevertheless, state-of-the-art models …

Reasoning, as an essential ability for complex problem-solving, can provide back-end
support for various real-world applications, such as medical diagnosis, negotiation, etc. This …

Humans (eg, crowdworkers) have a remarkable ability in solving different tasks, by simply
reading textual instructions that define them and looking at a few examples. Despite the …

Recently, growing interest has been aroused in extending the multimodal capability of large
language models (LLMs), eg, vision-language (VL) learning, which is regarded as the next …

Pre-trained language models can be surprisingly adept at tasks they were not explicitly
trained on, but how they implement these capabilities is poorly understood. In this paper, we …

We introduce MAmmoTH, a series of open-source large language models (LLMs)
specifically tailored for general math problem-solving. The MAmmoTH models are trained on …

Large language models (LLMs) have achieved remarkable performance on a variety of
natural language understanding tasks. However, existing benchmarks are inadequate in …