December 29, 2024

Large language models (LLMs) encounter significant difficulties in performing efficient and logically consistent reasoning. Existing methods, such as CoT prompting,

Large language models (LLMs) built using transformer architectures heavily depend on pre-training with large-scale data to predict sequential tokens. This

In today’s world, Multimodal large language models (MLLMs) are advanced systems that process and understand multiple input forms, such as

Social media platforms have revolutionized human interaction, creating dynamic environments where millions of users exchange information, form communities, and influence

Formal mathematical reasoning represents a significant frontier in artificial intelligence, addressing fundamental logic, computation, and problem-solving challenges. This field focuses

Hypernetworks have gained attention for their ability to efficiently adapt large models or train generative models of neural representations. Despite

Agentic AI systems have revolutionized industries by enabling complex workflows through specialized agents working in collaboration. These systems streamline operations,

Operator learning is a transformative approach in scientific computing. It focuses on developing models that map functions to other functions,

The development of Transformer models has significantly advanced artificial intelligence, delivering remarkable performance across diverse tasks. However, these advancements often

Large Language Models (LLMs) have shown significant potential in reasoning tasks, using methods like Chain-of-Thought (CoT) to break down complex