[legothief]

I'm also quite excited about that - there's existing research, quite a few papers that are using graph-based models for MLOnCode: https://proceedings.neurips.cc/paper/2021/file/c2937f3a1b3a1... https://arxiv.org/abs/2203.05181 https://arxiv.org/abs/2005.02161 https://arxiv.org/abs/2012.07023 https://arxiv.org/abs/2005.10636v2 https://arxiv.org/abs/2106.10918

Definitely check them out! There are also tools that were made available by some of the authors: https://github.com/google-research/python-graphs

[algo_trader]

Are these papers somehow "curated" or "recommended"?!

Unfortunately, GNNs are lagging LLMs in the code domain. Maybe because

a. LLMs and transformers rulezz OR b. there is far more source code than there are compiled code graphs

[davidatbu]

I wouldn't rule out the fact that transformers are very amenable to parallel computation as the reason

[davidatbu]

Thank you!! I've been looking to get my feet wet with SoTA research for MLONCode, so this is very helpful!