---
title: "Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language — Liu 2023"
description: "For practitioners, the paper offers an early map of where LLMs help and where they fail. 112 references, cited by 89 papers here."
authors: ["Yiheng Liu", "Tianle Han", "Siyuan Ma", "Jiayue Zhang", "Yuanyuan Yang", "Jiaming Tian", "Hao He", "Antong Li", "Mengshen He", "Zhengliang Liu", "Zihao Wu", "Lin Zhao", "Dajiang Zhu", "Xiang Li", "Ning Qiang", "Dingang Shen", "Tianming Liu", "Bao Ge"]
year: 2023
venue: "arXiv:2304.01852 · Meta-Radiology (2023)100017"
source: "https://arxiv.org/abs/2304.01852"
doi: "10.1016/j.metrad.2023.100017"
arxiv: "2304.01852"
licence: "CC BY 4.0 (arXiv)"
licence_url: "http://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/liu-2023-summary-chatgpt-related-research-perspective/"
---
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# Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models

**Authors:** Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, [Zhengliang Liu](https://md.research.elamur.ai/free/en/authors/zhengliang-liu/), Zihao Wu, Lin Zhao, Dajiang Zhu, [Xiang Li](https://md.research.elamur.ai/free/en/authors/xiang-li/), Ning Qiang, Dingang Shen, Tianming Liu and Bao Ge · **Year:** 2023 · **Venue:** arXiv:2304.01852 · Meta-Radiology (2023)100,017 · **Licence:** [CC BY 4.0 (arXiv)](http://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://doi.org/10.1016/j.metrad.2023.100017) · [PDF](https://arxiv.org/pdf/2304.01852) · [DOI 10.1016/j.metrad.2023.100017](https://doi.org/10.1016/j.metrad.2023.100017) · [arXiv 2304.01852](https://arxiv.org/abs/2304.01852) · [OpenAlex](https://openalex.org/W4385988359)

**Citations:** 847 citations (OpenAlex, 2026-10-14) · [89](https://md.research.elamur.ai/free/en/papers/liu-2023-summary-chatgpt-related-research-perspective/cited-by/) in our library, of the 140,884 papers whose bibliographies we read

## Summary
This survey maps the early wave of research on ChatGPT (GPT-3.5 and GPT-4) after its December 2022 release. The authors collected every arXiv paper that mentioned ChatGPT up to 1 April 2023, which came to 194 papers. They analysed this set in three ways: monthly submission trends, a word cloud of frequent terms, and a breakdown by application field.

The review then groups the reported uses into several areas:
- question answering
- text classification and generation
- code generation
- inference
- data extraction and processing
- human–ChatGPT collaboration
- tool integration
- medicine
- AI ethics

It also covers studies that evaluate the model's capabilities and its limitations.

The analysis shows that work is concentrated on core NLP tasks. Education, history, mathematics, medicine and physics remain comparatively underexplored despite encouraging early findings. The authors attribute the model's versatility to web-scale pre-training, instruction fine-tuning and RLHF. They close with a research agenda covering data filtering, cheaper training, real-time data and local domain-specific deployment. For practitioners, the paper offers an early map of where LLMs help and where they fail.

## Key points
- The corpus is 194 arXiv papers mentioning ChatGPT, collected up to 1 April 2023. A live companion webpage tracks newer trends: https://snnubiai.github.io/chatgpt_arxiv_analysis/
- **Mathematics:** On the GHOSTS dataset of graduate-level problems, ChatGPT stayed below the level of typical math graduate students. It scored well on only 26% of the MATH subset and earned the lowest score on Holes-in-Proofs.
- **Physics:** On the Force Concept Inventory, ChatGPT scored about 50–65%. A cohort of 415 students averaged 56%.
- **Math word problems and tutoring:**
  - On DRAW-1K, introspection-based performance prediction raised accuracy from 34% to 69%.
  - In an OATutor study, 70% of ChatGPT-generated algebra hints passed manual quality checks. Human-written hints still scored higher.
- **Ethics and outlook:** The listed risks include bias, misinformation, and privacy (ChatGPT was banned in Italy in April 2023). The proposed remedies include interdisciplinary ethical frameworks and localized LLM deployment in sensitive domains such as medicine.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Natural language processing](https://md.research.elamur.ai/free/en/shelves/nlp/) · [AI & machine learning](https://md.research.elamur.ai/free/en/shelves/ai/)

Topics: [🧠 Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/)

## Institutions

- [Harvard University](https://md.research.elamur.ai/free/en/universities/harvard-university/) — University, Cambridge, United States · 64 works · 35,670 citations
- [Xi'an Jiaotong University](https://md.research.elamur.ai/free/en/universities/xi-an-jiaotong-university/) — University, Xi'an, China · 6 works · 35,595 citations
- [University of Georgia](https://md.research.elamur.ai/free/en/universities/university-of-georgia/) — University, Athens, United States · 7 works · 25,973 citations
- [Massachusetts General Hospital](https://md.research.elamur.ai/free/en/hospitals/massachusetts-general-hospital/) — Hospital, Boston, United States · 3 works · 5,392 citations
- [The University of Texas at Arlington](https://md.research.elamur.ai/free/en/universities/the-university-of-texas-at-arlington/) — University, Arlington, United States · 4 works · 1,474 citations
- [ShanghaiTech University](https://md.research.elamur.ai/free/en/universities/shanghaitech-university/) — University, Shanghai, China · 3 works · 1,412 citations

Also on the byline: [Shaanxi Normal University](https://ror.org/0170z8493) · [United Imaging Intelligence](https://ror.org/01s8ddd88).

## Cite

Cite as: Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, Zihao Wu, Lin Zhao, Dajiang Zhu, Xiang Li, Ning Qiang, Dingang Shen, Tianming Liu and Bao Ge. 2023. Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models. arXiv:2304.01852 · Meta-Radiology (2023)100,017.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@misc{liu2023summary,
  title = {{Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models}},
  author = {Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, Zihao Wu, Lin Zhao, Dajiang Zhu, Xiang Li, Ning Qiang, Dingang Shen, Tianming Liu and Bao Ge},
  year = {2023},
  doi = {10.1016/j.metrad.2023.100017},
  eprint = {2304.01852},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.1016/j.metrad.2023.100017}
}
```

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## References

112 references, 20 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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