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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
by legothief 4y ago
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/c2937f3a1b3a177d2408574da0245a19-Paper.pdf https://proceedings.neurips.cc/paper/2021/file/c2937f3a1b3a1...
https://arxiv.org/abs/2203.05181 https://arxiv.org/abs/2203.05181
https://arxiv.org/abs/2005.02161 https://arxiv.org/abs/2005.02161
https://arxiv.org/abs/2012.07023 https://arxiv.org/abs/2012.07023
https://arxiv.org/abs/2005.10636v2 https://arxiv.org/abs/2005.10636v2
https://arxiv.org/abs/2106.10918 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 https://github.com/google-research/python-graphs
- algo_trader 4y agoAre 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 4y agoI wouldn't rule out the fact that transformers are very amenable to parallel computation as the reason
- davidatbu 4y agoThank you!! I've been looking to get my feet wet with SoTA research for MLONCode, so this is very helpful!