A Wimmics & Forum Numerica seminar by Smaranda MURESAN Columbia University, USA
Abstract: Large language models (LLMs) constitute a paradigm shift in Natural Language Processing and its applications across all domains. To move towards human-centric NLP designed for social good and responsible computing, I argue we need knowledge-aware NLP systems and human-AI collaboration frameworks. NLP systems that interact with humans need to be knowledge aware (e.g., linguistic, commonsense, sociocultural norms) and context aware (e.g., social, perceptual) so that they communicate better and in a safer and more responsible fashion with humans. Moreover, NLP systems should be able to collaborate with humans to create high-quality datasets for training and/or evaluating NLP models, to help humans solve tasks, and ultimately to align better with human values. In this talk, I will give a brief overview of my lab’s research around NLP for social good and responsible computing (e.g., misinformation detection, NLP for education and public health, building NLP technologies with language and culture diversity in mind). I will highlight key innovations on theory-guided and knowledge-aware models that allow us to address two important challenges: lack of training data, and the need to model commonsense knowledge. I will also present some of our recent work on human-AI collaboration frameworks for building high-quality datasets for various tasks such as generating visual metaphors or modeling cross-cultural norms similarities and differences.
