As humans and other animals experience new things, their brains continuously update their memory of past events. These ...
Text-prompted image segmentation enables fine-grained visual understanding and is critical for applications such as human-computer interaction and robotics. However, existing supervised fine-tuning ...
Ouroboros is an unified framework that seamlessly integrates representation learning with molecular generation and therefore allows efficient chemical space exploration through pre-trained molecular ...
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Psychologists say people who still use paper calendars aren’t stubborn or old-fashioned. Their brains are wired to process information in a richer way
A pen presses grooves into a paper calendar while someone scribbles down an appointment. An hour later, that person recalls ...
The sheer volume of medical curriculum has long forced students into inefficient cycles of re-reading and manual flashcard creation, a method that research shows fails to build long-term retention.
Large Language Models (LLMs) such as GPT-4, Gemini-Pro, Llama 2, and medical-domain-tuned variants like Med-PaLM 2 have ...
Abstract: The Contrastive Language-Image Pretraining (CLIP) model has been widely used in various downstream vision tasks. The few-shot learning paradigm has been widely adopted to augment its ...
Retrieval-augmented generation (RAG) technology can empower large language models (LLMs) to generate more accurate, professional, and timely responses without fine-tuning. However, due to the complex ...
Abstract: Vision-language models (VLMs) have achieved impressive progress in natural image reasoning, yet their potential in medical imaging remains underexplored. Medical vision-language tasks demand ...
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