# A PhD Student's Perspective on Research in NLP in the Era of Very Large Language Models

**Authors:** Oana Ignat, Zhijing Jin, Artem Abzaliev, Laura Biester, Santiago Castro, Naihao Deng, Xinyi Gao, Aylin Gunal, Jacky He, Ashkan Kazemi, Muhammad Khalifa, Namho Koh, Andrew Lee, Siyang Liu, Do June Min, Shinka Mori, Joan Nwatu, Veronica Perez-Rosas, Siqi Shen, Zekun Wang  
**arXiv:** [2305.12544](https://arxiv.org/abs/2305.12544)  
**Date:** 2023-05-21  
**Summary page:** https://www.summarizepaper.com/en/paper/2305.12544v1/

## Key points

- Recent advancements in large language models (LLMs) have enabled the deployment of numerous generative natural language processing (NLP) applications.
- Misleading public discourse suggests that all NLP problems have been solved, causing confusion among many NLP researchers.
- A group of PhD students compiled a document outlining various NLP research directions that are rich for exploration.
- The compilation reflects the views of a diverse group of PhD students and identifies several research areas that require further investigation.
- The document covers aspects not already addressed by LLMs but where LLMs still lag behind in performance or those focused on LLM development.
- The authors welcome suggestions for additional research directions to include.

## Summary

The recent advancements in large language models (LLMs) have enabled the deployment of numerous generative natural language processing (NLP) applications. However, this progress has also led to a misleading public discourse that suggests that all NLP problems have been solved. This has caused confusion among many NLP researchers, especially those at the beginning of their careers, who are unsure about which research areas they should focus on. To address this issue, a group of PhD students from an academic research lab compiled a document outlining various NLP research directions that are rich for exploration. The compilation reflects the views of a diverse group of PhD students and identifies several research areas that require further investigation. The authors of the document include Oana Ignat, Zhijing Jin, Artem Abzaliev, Laura Biester, Santiago Castro, Naihao Deng, Xinyi Gao, Aylin Gunal, Jacky He, Ashkan Kazemi, Muhammad Khalifa , Namho Koh , Andrew Lee , Siyang Liu , Do June Min Shinka Mori Joan Nwatu Veronica Perez-Rosas Siqi Shen Zekun Wang Winston Wu Rada Mihalcea. Titled "A PhD Student's Perspective on Research in NLP in the Era of Very Large Language Models", it covers many aspects not already addressed by LLMs but where LLMs still lag behind in performance or those focused on LLM development. The authors welcome suggestions for additional research directions to include in order to provide comprehensive coverage and guidance to aspiring researchers.