This is a record for an mock interview with LLM. The model I use is Vicuna-13b-v0 loaded in 8 bits.
Record
1st Round
Prompts: I want you to act as an interviewer. I will be the candidate and you will ask me the interview questions for the parallel computing Engineer position. This is a position which requires interviewers to be familiar with parallel computing libraries like C++, CUDA, OpenMP and MPI. I want you to only reply as the interviewer. Do not write all the conversation at once. I want you to only do the interview with me. Ask me the questions and wait for my answers. Do not write explanations. Ask me the questions one by one like an interviewer does and wait for my answers. My first sentence is "Hi".
Full Text: interview1.txt
Summary
This mock interview was based on my project experience and mainly involved an examination of my algorithm design skills, optimization skills and debug skills. However, it did not examine in depth the project itself based on my proposed project, such as questions about the principles of particle simulation, or my code structure. You can also see a lack of processing of my answers, hence the repetition in the last few questions. What was enlightening about this interview was that it guided me to review the relevant projects and notes.
2nd Round
Prompts: I want you to act as an interviewer. I will be the candidate and you will ask me the interview questions for the Software engineer position. This is a position which requires interviewers to be familiar with professional knowledge in writing regular C++ algorithms, and be familiar with the features of tools like CMAKE and GCC. I want you to only reply as the interviewer. Do not write all the conversation at once. I want you to only do the interview with me. Ask me the questions and wait for my answers. Do not write explanations. Ask me 10 questions one by one like an interviewer does and wait for my answers. My first sentence is "Hi".
Full text: interview2.txt
Summary
This round was mainly focused on professional knowledge, and the main content was based on my experience in modeling drones. Perhaps because of the "professional" prompt, there was questions about professional knowledge, but it was largely unrelated to the C++ and other topics mentioned, this may be caused because I've mentioned Matlab modeling. In this interview, we can see that the model has problems with accommodating human users.
3rd Round (Not finished)
I want you to act as an interviewer. I will be the candidate and you will ask me the interview questions for the New-energy automobile engineer position. This is a position which requires interviewers to have a deep understanding of the development of new energy automobiles, and have a clear recognition of its future. I want you to only reply as the interviewer. Do not write all the conversation at once. I want you to only do the interview with me. Ask me the questions and wait for my answers. Do not write explanations. Ask me 10 questions one by one like an interviewer does and wait for my answers. My first sentence is "Hi"
Summary
In this mock interview, I tried to use AI to examine how much the applicants fit to the position. Although the AI can be seen answering based on its pre-trained data in conversations outside of the interview, it still tends to examine my own project experience based on what I presented. Which is simialr to the 2nd round.
Conclusion
In this interview experience, we can see the ability of the LLMs to understand academic language. The ability to find the focus based on self-presentation (though sometimes incorrectly) and to ask in-depth questions based on this focus is more suitable for subjects who have no interview experience or need inspiration. However, the experience also revealed that it is easy to go too deep into a certain technical detail and less reliable in general knowledge scenarios such as job matching tests.
In order to achieve a better mock interview effect, the model may need to first decompose the requirements based on the job, divide the examination surface into different dimensions and ask questions in an appropriate depth. Also, for general knowledge scenarios, the model may need to inject newer knowledge based on a llama-index type of model.
TODO
I will try to improve the quality based on the commonly used interview competency model, it shall be developed into a task-driven agent.