This comprehensive survey explored the evolving landscape of generative Artificial
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …

In recent years, there has been remarkable progress in leveraging Language Models (LMs),
encompassing Pre-trained Language Models (PLMs) and Large-scale Language Models …

Verifiers or reward models are often used to enhance the reasoning performance of large
language models (LLMs). A common approach is the Best-of-N method, where N candidate …

Large-scale vision-and-language models, such as CLIP, are typically trained on web-scale
data, which can introduce inappropriate content and lead to the development of unsafe and …

Mathematical reasoning serves as a cornerstone for assessing the fundamental cognitive
capabilities of human intelligence. In recent times, there has been a notable surge in the …

Mathematical reasoning presents a significant challenge for Large Language Models
(LLMs) due to the extensive and precise chain of reasoning required for accuracy. Ensuring …

Comparative reasoning plays a crucial role in predicting text preferences; however, large
language models (LLMs) often demonstrate inconsistencies in their reasoning, leading to …

Achieving human-level intelligence requires refining cognitive distinctions between System
1 and System 2 thinking. While contemporary AI, driven by large language models …

While Large Language Models (LLMs) have achieved tremendous success in various
applications, they are also susceptible to jailbreaking attacks. Several primary defense …

Accurate mathematical reasoning with Large Language Models (LLMs) is crucial in
revolutionizing domains that heavily rely on such reasoning. However, LLMs often …