Covers the basics of Natural Language Processing, from traditional to modern approaches, highlighting the challenges and importance of studying both methods.
Explores learning interactive policies from non-traditional sources of data for autonomous systems, including language-informed latent actions and the PLATO framework.
Explores coreference resolution models, challenges in scoring spans, graph refinement techniques, state-of-the-art results, and the impact of pretrained Transformers.
