Wrapping up my internship at @Apple MLR. It was a great experience to work with the team on agent training. We have explored how MoE architectures behave in agentic post-training, and a general framework to steer the expert selection, to align with agents' operations. Specifically, we find that off-the-shelf MoE models tend to re-use experts for the same operation, while different operations are more likely to be accomplished by diverging experts. Our framework strengthens this operation-expert association, and achieves significant improvement on both task performance and inference efficiency. arxiv.org/abs/2610.07332 Huge thanks to my mentors @cydhsieh and Ting-Yao Hu, as well as all collaborators in the team: Raviteja Vemulapalli, Sanjoy Chowdhury, @OncelTuzel. Right now, I am going to defend my PhD by the end of 2026, and am searching for full-time research scientist roles in the industry. Feel free to message me if you find me to be a good fit for your team.