Topic: modality

A new survey and roadmap for omnimodal embeddings aim to bridge the gap between different modalities (e.g., text, images) in AI research, unifying disparate communities to enhance the performance of embedding models across various applications. This work is crucial as it could lead to more versatile and powerful AI systems that can better understand and process diverse types of data.

arxiv.org↗

LongCat-2.5, a new multimodal AI model, has been developed to perform agentic tasks more effectively. This advancement is significant as it enhances AI's ability to handle diverse inputs and outputs, potentially improving applications in fields like virtual assistants and creative content generation.

longcat.ai↗