Graph generation is an important task across various fields, including molecular design and social network analysis, due to its ability to model complex relationships and structured data. Despite ...

The development of multimodal large language models (MLLMs) has brought new opportunities in artificial intelligence. However, significant challenges persist in integrating visual, linguistic, and ...

GUI agents face three critical challenges in professional environments: (1) the greater complexity of professional applications compared to general-use software, requiring detailed comprehension of ...

Latent diffusion models are advanced techniques for generating high-resolution images by compressing visual data into a latent space using visual tokenizers. These tokenizers reduce computational ...

Enhancing user experiences and boosting retention using recommendation systems is an effective and ever-evolving strategy used by many industries, such as e-commerce, streaming services, social media, ...

Artificial intelligence has come a long way, transforming the way we work, live, and interact. Yet, challenges remain. Many AI systems rely heavily on cloud-based infrastructure, which raises valid ...

Microsoft has released Phi-4, a compact and efficient small language model, on Hugging Face under the MIT license. This decision highlights a shift towards ...

In a time when global health faces persistent threats from emerging pandemics, the need for advanced biosurveillance and pathogen detection systems is increasingly evident. Traditional genomic ...

Protein docking, the process of predicting the structure of protein-protein complexes, remains a complex challenge in computational biology. While advances like AlphaFold have transformed ...

The development of Physical AI—AI systems designed to simulate, predict, and optimize real-world physics—has long been constrained by significant challenges. Building accurate models often demands ...