# On the Military Applications of Large Language Models

arXiv: https://arxiv.org/abs/2511.10093 · HTML: https://mlsanity.com/paper/2511.10093/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Nov 2025.

## Built on by (most cited first, 2 of 2)

- [Overtrained, Not Misaligned](https://mlsanity.com/paper/2605.12199/) (2026)
- [LLMs Contain Multitudes: How Deployment Context Reshapes Model-Level Preferences and Values](https://mlsanity.com/paper/2606.13944/) (2026)

## Abstract (arXiv)

In this paper, military use cases or applications and implementation thereof are considered for natural language processing and large language models, which have broken into fame with the invention of the generative pre-trained transformer (GPT) and the extensive foundation model pretraining done by OpenAI for ChatGPT and others. First, we interrogate a GPT-based language model (viz. Microsoft Copilot) to make it reveal its own knowledge about their potential military applications and then critically assess the information. Second, we study how commercial cloud services (viz. Microsoft Azure) could be used readily to build such applications and assess which of them are feasible. We conclude that the summarization and generative properties of language models directly facilitate many applications at large and other features may find particular uses.