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The Impact of Large Language Models in Academia: from Writing to Speaking

Mingmeng Geng, Caixi Chen, Yanru Wu, Dongping Chen, Yao Wan, Pan Zhou

TL;DR

This first large-scale study of how LLMs influence the two main modes of verbal communication and expression within the same group of people shows that LLM-style words such as "significant" have been used more frequently in abstracts and oral presentations.

Abstract

Large language models (LLMs) are increasingly impacting human society, particularly in textual information. Based on more than 30,000 papers and 1,000 presentations from machine learning conferences, we examined and compared the words used in writing and speaking, representing the first large-scale study of how LLMs influence the two main modes of verbal communication and expression within the same group of people. Our empirical results show that LLM-style words such as "significant" have been used more frequently in abstracts and oral presentations. The impact on speaking is beginning to emerge and is likely to grow in the future, calling attention to the implicit influence and ripple effect of LLMs on human society.

The Impact of Large Language Models in Academia: from Writing to Speaking

TL;DR

This first large-scale study of how LLMs influence the two main modes of verbal communication and expression within the same group of people shows that LLM-style words such as "significant" have been used more frequently in abstracts and oral presentations.

Abstract

Large language models (LLMs) are increasingly impacting human society, particularly in textual information. Based on more than 30,000 papers and 1,000 presentations from machine learning conferences, we examined and compared the words used in writing and speaking, representing the first large-scale study of how LLMs influence the two main modes of verbal communication and expression within the same group of people. Our empirical results show that LLM-style words such as "significant" have been used more frequently in abstracts and oral presentations. The impact on speaking is beginning to emerge and is likely to grow in the future, calling attention to the implicit influence and ripple effect of LLMs on human society.
Paper Structure (25 sections, 2 equations, 37 figures, 1 table)

This paper contains 25 sections, 2 equations, 37 figures, 1 table.

Table of Contents

  1. Introduction
  2. Data and Methods
  3. Datasets
  4. Word Frequency Analysis
  5. LLM Simulations and Impact Estimation
  6. Results
  7. AIGC Detectors
  8. Changes in Word Frequencies
  9. Distribution of Frequency Ratios
  10. LLM Simulations
  11. LLM Impact Estimations
  12. Conclusions and Discussions
  13. Related Works
  14. Impacts of LLMs
  15. Machine Generated Text Detection
  16. ...and 10 more sections

Figures (37)

  • Figure 1: Overview of processing and analysis.
  • Figure 2: Word frequency in abstracts and presentations.
  • Figure 3: Word frequency ratio in abstracts and talks of ICML oral papers. The error bars represent one standard deviation in each bin.
  • Figure 4: Word frequency in abstracts of ICML oral papers.
  • Figure 5: Estimation of LLM's impact on oral papers. Error bars indicate the standard deviation of the estimates using different groups of words.
  • ...and 32 more figures