Researchers have highlighted concerns regarding hallucinations in LLMs due to their generation of plausible but inaccurate or unrelated content. However, these ...

Large language models (LLMs) have revolutionized artificial intelligence by demonstrating remarkable capabilities in text generation and problem-solving. However, a critical limitation persists in ...

Large language models (LLMs) have revolutionized artificial intelligence by demonstrating remarkable capabilities in text generation and problem-solving. However, a critical limitation persists in ...

Large language models (LLMs) have revolutionized artificial intelligence by demonstrating remarkable capabilities in text generation and problem-solving. However, a critical limitation persists in ...

Chemical reasoning involves intricate, multi-step processes requiring precise calculations, where small errors can lead to significant issues. LLMs often struggle with domain-specific challenges, such ...

Edge devices like smartphones, IoT gadgets, and embedded systems process data locally, improving privacy, reducing latency, and enhancing responsiveness, and AI is getting integrated into these ...

Edge devices like smartphones, IoT gadgets, and embedded systems process data locally, improving privacy, reducing latency, and enhancing responsiveness, and AI is getting integrated ...

Large Language Models (LLMs) are primarily designed for text-based tasks, limiting their ability to interpret and generate multimodal content such as images, videos, and audio. Conventionally, ...

Large Language Models (LLMs) have demonstrated notable reasoning capabilities in mathematical problem-solving, logical inference, and programming. However, their effectiveness is often contingent on ...

Vision-language models (VLMs) face a critical challenge in achieving robust generalization beyond their training data while maintaining computational resources and cost efficiency. Approaches, such ...