CLOct 31, 2023

Defining a New NLP Playground

arXiv:2310.20633v1138 citationsh-index: 24
Originality Synthesis-oriented
AI Analysis

It aims to diversify NLP research to benefit academic researchers, especially PhD students, by suggesting new problems and paradigms.

The paper addresses concerns about the homogenization and resource intensity of NLP due to large language models by proposing over 20 research directions suitable for PhD dissertations, including theoretical analysis and interdisciplinary applications.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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