MIT CSAIL researchers are using ideas from game theory to improve the reliability of language generation in language models.

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.

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.

The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.

MIT researchers uncover the structural properties and dynamics of deep classifiers, offering novel explanations for optimization, generalization, and approximation in deep networks.

MIT researchers trained logic-aware language models to reduce harmful stereotypes like gender and racial biases.

Built on recent advances in machine learning, the model predicts how well individuals will produce and comprehend sentences.

MIT researchers are discovering which parts of the brain are engaged when a person evaluates a computer program.

Researchers used a powerful deep-learning model to extract important data from electronic health records that could assist with personalized medicine.