Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning. The ...

With the emergence of huge amounts of heterogeneous multi-modal data, including images, videos, texts/languages, audios, and multi-sensor data, deep learning-based methods have shown promising ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Cross-modal reasoning tasks face persistent challenges such as cross-modal inference of causal dependencies with coarse-grained, weak resistance to noise, and weak interaction of spatial-temporal ...

As large language models (LLMs) become increasingly integrated into clinical decision-making, ensuring trustworthy reasoning is paramount. However, current evaluation strategies of LLMs’ medical ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I continue my ongoing analysis of the ...

Researchers at Nvidia have developed a new technique that flips the script on how large language models (LLMs) learn to reason. The method, called reinforcement learning pre-training (RLP), integrates ...

Many are aware of the popular Chain of Thoughts (CoT) method of prompting generative AI in order to obtain better and more sophisticated responses. Researchers from Google DeepMind and Princeton ...