mlsanityData to 14 Oct 2026

Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models

arXiv 2305.12544 ↗First posted 21 May 2023cs.CL cs.AIcited by 7

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Abstract (arXiv)

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

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 265 of its 529 references that are in the map. First posted on arXiv 21 May 2023.

Builds on

265 of 529 references.

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Citing papers per year: 2023: 4; 2024: 2; 2025: 1.

7 papers.