Large language models (LLMs) have revolutionized natural language processing with their
exceptional understanding, synthesizing, and reasoning capabilities. However, deploying …

Abstract Context: Pre-trained models (PTMs) have demonstrated significant potential in
automatic code translation. However, the vulnerability of these models in translation tasks …

We introduce MedXpertQA, a highly challenging and comprehensive benchmark to evaluate
expert-level medical knowledge and advanced reasoning. MedXpertQA includes 4,460 …

The current generation of large language models (LLMs) is typically designed for broad,
general-purpose applications, while domain-specific LLMs, especially in vertical fields like …

This paper presents a pioneering and comprehensive analysis of fake text, a pressing issue
in the digital age, by categorizing it into two main types: Misinformation and LM-generated …

The rise of superintelligent open-source generative AI (genAI) heralds both extraordinary
potential and unprecedented risk, exemplified by the rapid emergence of DeepSeek as a …

Autoregressive models (ARMs) are widely regarded as the cornerstone of large language
models (LLMs). We challenge this notion by introducing LLaDA, a diffusion model trained …

Despite increasing discussions on open-source Artificial Intelligence (AI), existing research
lacks a discussion on the transparency and accessibility of state-of-the-art (SoTA) Large …

We present a fundamental discovery that challenges our understanding of how complex
reasoning emerges in large language models. While conventional wisdom suggests that …

Artificial intelligence commonly refers to the science and engineering of artificial systems
that can carry out tasks generally associated with requiring aspects of human intelligence …