In this interview series, we're meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. We sat down with Maxime Meyer to chat about his current research, future plans, and how he found the doctoral consortium experience. Could you start with an introduction to yourself, where you're studying and the topic of your research? My research focuses on large language models. Which aspect of large language models are you looking at?

For learning Boolean concept classes, we show that the entangled and separable sample complexity are polynomially related .

Quantum Algorithms (VQAs) have emerged to obtain possible quantum advantage. In particular, how to effectively incorporate hard constraints in VQAs remains a critical and open question.

Both of the techniques assume bitwise access to the oracle as a classical function.

Computing gradients through backpropagation is crucial to the success of modern deep neural networks.