Differentiable Adaptive Merging (DAM): A Novel AI Approach to Model Integration
Model merging, particularly within the realm of large language models (LLMs), presents an intriguing challenge that addresses …
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Equipping doctors with AI co-pilots | MIT News
Most doctors go into medicine because they want to help patients. But today’s health care system requires that …
Neural Magic Unveils Machete: A New Mixed-Input GEMM Kernel for NVIDIA Hopper GPUs
The rapid growth of large language models (LLMs) and their increasing computational requirements have prompted a pressing …
When to trust an AI model | MIT News
Because machine-learning models can give false predictions, researchers often equip them with the ability to tell a …
Stanford Researchers Propose LoLCATS: A Cutting Edge AI Method for Efficient LLM Linearization
The problem with efficiently linearizing large language models (LLMs) is multifaceted. The quadratic attention mechanism in traditional …
Reasoning skills of large language models are often overestimated | MIT News
When it comes to artificial intelligence, appearances can be deceiving. The mystery surrounding the inner workings of …
Holistic Evaluation of Vision Language Models (VHELM): Extending the HELM Framework to VLMs
One of the most pressing challenges in the evaluation of Vision-Language Models (VLMs) is related to not …
Marking a milestone: Dedication ceremony celebrates the new MIT Schwarzman College of Computing building | MIT News
The MIT Stephen A. Schwarzman College of Computing recently marked a significant milestone as it celebrated the …
Researchers at Stanford University Propose ExPLoRA: A Highly Effective AI Technique to Improve Transfer Learning of Pre-Trained Vision Transformers (ViTs) Under Domain Shifts
Parameter-efficient fine-tuning (PEFT) methods, like low-rank adaptation (LoRA), allow large pre-trained foundation models to be adapted to …
How to assess a general-purpose AI model’s reliability before it’s deployed | MIT News
Foundation models are massive deep-learning models that have been pretrained on an enormous amount of general-purpose, unlabeled …