  The recent explosion of performance of large language models (LLMs) has
changed the field of Natural Language Processing (NLP) more abruptly and
seismically than any other shift in the field's 80-year history. This has
resulted in concerns that the field will become homogenized and
resource-intensive. The new status quo has put many academic researchers,
especially PhD students, at a disadvantage. This paper aims to define a new NLP
playground by proposing 20+ PhD-dissertation-worthy research directions,
covering theoretical analysis, new and challenging problems, learning
paradigms, and interdisciplinary applications.
