A direct correlation exists between an LLM’s training corpus quality and its capabilities. Consequently, researchers have invested a great deal of effort into curating extensive, high-quality datasets ...
Researchers are focusing increasingly on creating systems that can handle multi-modal data exploration, which combines structured and unstructured data. This involves analyzing text, images, videos, ...
LLMs have revolutionized software development by automating coding tasks and bridging the natural language and programming gap. While highly effective for general-purpose programming, they struggle ...
The development of Transformer models has significantly advanced artificial intelligence, delivering remarkable performance across diverse tasks. However, these advancements often come with steep ...
Operator learning is a transformative approach in scientific computing. It focuses on developing models that map functions to other functions, an essential aspect of solving partial differential ...
Agentic AI systems have revolutionized industries by enabling complex workflows through specialized agents working in collaboration. These systems streamline operations, automate decision-making, and ...
Machine unlearning is driven by the need for data autonomy, allowing individuals to request the removal of their data’s influence on machine learning models. This field complements data privacy ...
Large language models (LLMs) are integral to solving complex problems across language processing, mathematics, and reasoning domains. Enhancements in computational techniques focus on enabling LLMs to ...
Social media platforms have revolutionized human interaction, creating dynamic environments where millions of users exchange information, form communities, and influence one another. These platforms, ...
Formal mathematical reasoning represents a significant frontier in artificial intelligence, addressing fundamental logic, computation, and problem-solving challenges. This field focuses on enabling ...
Large language models (LLMs) built using transformer architectures heavily depend on pre-training with large-scale data to predict sequential tokens. This complex and resource-intensive process ...
Code generation using Large Language Models (LLMs) has emerged as a critical research area, but generating accurate code for complex problems in a single attempt remains a significant challenge. Even ...