AI Shorts

Language models have become increasingly complex, posing a unique challenge to interpret their inner workings. To mitigate this issue, research has shifted towards the concept of mechanistic interpretability, where the focus is on identifying and analyzing 'circuits'. These circuits refer to sparse computational subgraphs that encapsulate certain aspects of the model's behavior. The existing methodologies for…

Mental illness constitutes a critical public health issue globally with one in eight people affected and many lacking access to adequate treatment. Mental health professional training often contends with a significant difficulty: the disconnection between formal education and real-world patient interactions. A potential solution to this problem might lay in the use of Large Language…

Researchers focused on Multimodal Large Language Models (MLLMs) are striving to enhance AI's reasoning capabilities by integrating visual and textual data. Even though these models can interpret complex information from diverse sources such as images and text, they often struggle with complicated mathematical problems that contain visual content. To solve this issue, researchers are working…