no, basically nothing in terms of fundamental research

Matrix completion is part of it, also determinant processes, reinforcement learning, clustering, ...

[citation needed]

Some are non-profit, but for example most of the IEEE conferences are for-profit... Another common theme is conference non-profits subcontracting a lot of organizational aspects to for-profits.

No, never used them

I am not sure what you would consider SOTA in few-shot RL. The benchmarks I know are quite ad-hoc and don't actually impact much outside of computer science research papers.

The people that work on applying RL for actual applications don't seem to use meta-RL.

(I have published myself in the meta-learning field, and worked a lot on robotics)

I see no applications of meta learning appearing, outside of self-citations within the field. The SOTA in supervised learning doesn't use any meta-learning. The SOTA in RL neither. The promise of learning to learn never really came true...

... until large supervised language models seemed to suddenly meta-learn as an emergent property.

So not only did nothing in the meta-learning field really take off and had some impact outside of computer science research papers, its original reason of being has been subsumed by a completely different line of research.

Meta-learning is no longer a goal, it's understood to be a side-effect of sufficiently large models.

Hundreds of Phd students were in their positions. Few made such an impact.

It's not easy to be impactful, even with a good supervisor. In Krizhevsky's case, one could even argue he had a big impact, despite having Hinton as a supervisor. Alexnet was kind of built behind Hinton's back as he didn't approve of the research direction. Hinton did turn around later and recognize the importance though.

Yes, MAML is on top. But I don't think it has been very impactful, neither has the whole field of meta-learning really been.

Any concrete papers you have in mind?

Chelsea Finn? I knew very little people who were using MAML during her Phd, and even fewer after.

I reckon e.g. Ian Goodfellow had a lot of impact during his Phd. Alex Krizhevsky is another name with big impact.