Foundation models hold promise in medicine, especially in assisting complex tasks like Medical Decision-Making (MDM). MDM is a nuanced process requiring clinicians to analyze diverse data sources—like ...
In the fast-paced digital age, AI assistants have become essential tools for enhancing productivity, managing workflows, and providing personalized support in our everyday lives. From voice-activated ...
Large Language Models (LLMs) have demonstrated remarkable in-context learning (ICL) capabilities, where they can learn tasks from demonstrations without requiring additional training. A critical ...
The Evidence Lower Bound (ELBO) is a key objective for training generative models like Variational Autoencoders (VAEs). It parallels neuroscience, aligning with the Free Energy Principle (FEP) for ...
The development of Artificial Intelligence (AI) tools has transformed data processing, analysis, and visualization, increasing the efficiency and insight of data analysts’ work. With so many ...
In recent times, large language models (LLMs) built on the Transformer architecture have shown remarkable abilities across a wide range of tasks. However, these impressive capabilities usually come ...
Recent advancements in generative language modeling have propelled natural language processing, making it possible to create contextually rich and coherent text across various applications.
Large language models (LLMs) are getting better at scaling and handling long contexts. As they are being used on a large scale, there has been a growing demand for efficient support of high-throughput ...
Recent advancements in Large Language Models (LLMs) have demonstrated exceptional natural language understanding and generation capabilities. Research has explored the unexpected abilities of LLMs ...
Multi-Scale Geometric Analysis of Language Model Features: From Atomic Patterns to Galaxy Structures
Large Language Models (LLMs) have emerged as powerful tools in natural language processing, yet understanding their internal representations remains a significant challenge. Recent breakthroughs using ...
Mathematical reasoning within artificial intelligence has emerged as a focal area in developing advanced problem-solving capabilities. AI can revolutionize scientific discovery and engineering fields ...
Evaluating NLP models has become increasingly complex due to issues like benchmark saturation, data contamination, and the variability in test quality. As interest in language generation grows, ...
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