The Natural Language Processing community affiliated with various departments and institutes within the University of Southern California. Our research areas span a wide range of topics within NLP and beyond. We invite you to explore the different research labs in the Thomas Lord Department of Computer Science and affiliated groups under ISI, ICT and other departments to learn about us, our work, and how you can get involved.
Intelligence and Knowledge Discovery Lab is a group of reseachers working on next-generation machine intelligence techniques for label-efficient machine learning, knowledge-guided natural language processing and knowledge reasoning. Our research spans across machine learning, natural language processing and data mining, with a focus on weak-supervision methods for modeling natural-language text data and graph-structured data.
The AI, Language, Learning, Generalization, and Robustness (ALLeGRo) Lab studies natural language processing and machine learning with a focus building reliable NLP systems for a wide range of scenarios. We aim for a deeper understanding of how NLP systems work, when they fail, and how they can be improved.
DILL is a lab dedicated to the study of Data, Interpretability, Language and Learning. DILL is focused on automatically estimating the difficulty of datasets for models, efficient pretraining, and semi-automatically building datasets that help models learn better. We also emphasize on measuring how interpretable model decisions are to human users.
Our lab studies machine learning approaches to advance the frontiers of artificial intelligence. We use techniques from deep learning, reinforcement learning, probabilistic graphical models, information theory and (sometimes) take inspirations from cognitive science and neuroscience to achieve this goal.
We delve into the realms of language, intelligence, and model ethics. Our team's primary focus is on creating trustworthy NLP models. We meticulously investigate the ethical consequences and broader societal effects of NLP models, striving to ensure that language technologies are constructed and employed in ways that align with ethical guidelines and uphold human values.