Therapeutic decision-making in clinical medicine constitutes a high-stakes domain in which AI guidance interacts with complex interactions among patient charact...
When I signed up for the Kaggle AI Agents Intensive course, I had a basic understanding of AI but little practical experience with agentic systems. Five days la...
Large Language Models (LLMs) are increasingly embedded in academic writing practices. Although numerous studies have explored how researchers employ these tools...
Extracting coherent and human-understandable themes from large collections of unstructured historical newspaper archives presents significant challenges due to ...
Retrieval-augmented generation (RAG) models rely on retrieved evidence to guide large language model (LLM) generators, yet current systems treat retrieval as a ...
We consider the problem of auditing black-box large language models (LLMs) to ensure they behave reliably when deployed in production settings, particularly in ...
Reliable interpretation of multimodal data in dentistry is essential for automated oral healthcare, yet current multimodal large language models (MLLMs) struggl...
The growing demand for real-time DNN applications on edge devices necessitates faster inference of increasingly complex models. Although many devices include sp...
Large Language Models (LLMs) exhibit remarkable capabilities in natural language understanding and reasoning, but suffer from hallucination: the generation of f...
Large language models specialized for code (CodeLLMs) have demonstrated remarkable capabilities in generating code snippets, documentation, and test cases. Howe...
Introduction How do we identify latent groups of patients in a large cohort? How can we find similarities among patients that go beyond the well-known comorbidi...
The automated translation of C code to Java code is a notoriously difficult task, fraught with challenges stemming from fundamental paradigm shifts (procedural ...
