Screen-reader users can upload a dataset and create customized data representations that combine visualization, textual description, and sonification.
Researchers demonstrate a technique that can be used to probe a model to see what it knows about new subjects.
With help from a large language model, MIT engineers enabled robots to self-correct after missteps and carry on with their chores.
Researchers developed a simple yet effective solution for a puzzling problem that can worsen the performance of large language models such as ChatGPT.
PhD students interning with the MIT-IBM Watson AI Lab look to improve natural language usage.
Master's students Irene Terpstra ’23 and Rujul Gandhi ’22 use language to design new integrated circuits and make it understandable to robots.
MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.
Human Guided Exploration (HuGE) enables AI agents to learn quickly with some help from humans, even if the humans make mistakes.
By blending 2D images with foundation models to build 3D feature fields, a new MIT method helps robots understand and manipulate nearby objects with open-ended language prompts.
AI models that prioritize similarity falter when asked to design something completely new.
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