Video understanding has long presented unique challenges for AI researchers. Unlike static images, videos involve intricate temporal dynamics and spatial-temporal reasoning, making it difficult for ...

Agentic AI enables autonomous and collaborative problem-solving that mimics human cognition. By facilitating multi-agent cooperation with real-time communication, it holds promise across diverse ...

The study of artificial intelligence has witnessed transformative developments in reasoning and understanding complex tasks. The most innovative developments are large language models (LLMs) and ...

Generative Large Multimodal Models (LMMs), such as LLaVA and Qwen-VL, excel in vision-language (VL) tasks like image captioning and visual question answering (VQA). However, these models face ...

The growth of data in the digital age presents both opportunities and challenges. An immense volume of text, images, audio, and video is generated daily across platforms. Traditional machine learning ...

The growth of data in the digital age presents both opportunities and challenges. An immense volume of text, images, audio, and video is generated daily across platforms. Traditional machine learning ...

The study of artificial intelligence has witnessed transformative developments in reasoning and understanding complex tasks. The most innovative developments are large language models (LLMs) and ...

The growing reliance on AI models for edge and mobile devices has underscored significant challenges. Balancing computational efficiency, model size, and multilingual capabilities remains a persistent ...

Advances in large language and multimodal speech-text models have laid a foundation for seamless, real-time, natural, and human-like voice interactions. Achieving this requires systems to process ...

Scientific metadata in research literature holds immense significance, as highlighted by flourishing research in scientometrics—a discipline dedicated to analyzing scholarly literature. Metadata ...

Large Language Models (LLMs) and Vision-Language Models (VLMs) transform natural language understanding, multimodal integration, and complex reasoning tasks. Yet, one critical limitation remains: ...

Generating time series data is important for many applications, including data augmentation, synthetic datasets, and scenarios. However, when there is more than one, this process becomes too complex ...