Summary of A Survey on Deep Learning For Theorem Proving, by Zhaoyu Li et al.
A Survey on Deep Learning for Theorem Proving
by Zhaoyu Li, Jialiang Sun, Logan Murphy, Qidong Su, Zenan Li, Xian Zhang, Kaiyu Yang, Xujie Si
First submitted to arxiv on: 15 Apr 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This comprehensive survey provides a thorough review of existing deep learning approaches for theorem proving, covering tasks such as autoformalization, premise selection, proofstep generation, and proof search. The paper also summarizes curated datasets and strategies for synthetic data generation, analyzes evaluation metrics, and discusses the performance of state-of-the-art methods. Furthermore, it identifies persistent challenges and promising avenues for future exploration in this rapidly growing field. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This survey looks at how deep learning can help with theorem proving in math. It’s like a big guide that shows what people have tried so far to make this process better. The paper talks about different ways to do this, like making formulas from natural language and finding the next step in a proof. It also mentions datasets and metrics used to measure how well these methods work. Overall, it’s a helpful resource for researchers who want to learn more about using deep learning for theorem proving. |
Keywords
» Artificial intelligence » Deep learning » Synthetic data
