Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models
Recent progress in large language models (LLMs) has enabled the deployment of many generative NLP applications. At the same time, it has also led to a misleading public discourse that ``it's all been solved.'' Not surprisingly, this has, in turn, made many NLP researchers -- especiall...
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Zusammenfassung: | Recent progress in large language models (LLMs) has enabled the deployment of
many generative NLP applications. At the same time, it has also led to a
misleading public discourse that ``it's all been solved.'' Not surprisingly,
this has, in turn, made many NLP researchers -- especially those at the
beginning of their careers -- worry about what NLP research area they should
focus on. Has it all been solved, or what remaining questions can we work on
regardless of LLMs? To address this question, this paper compiles NLP research
directions rich for exploration. We identify fourteen different research areas
encompassing 45 research directions that require new research and are not
directly solvable by LLMs. While we identify many research areas, many others
exist; we do not cover areas currently addressed by LLMs, but where LLMs lag
behind in performance or those focused on LLM development. We welcome
suggestions for other research directions to include:
https://bit.ly/nlp-era-llm |
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DOI: | 10.48550/arxiv.2305.12544 |